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Hedderson MM, Capra A, Lee C, Habel LA, Lee J, Gold EB, Badon SE, Mitro SD, El Khoudary SR. Longitudinal Changes in Sex Hormone Binding Globulin (SHBG) and Risk of Incident Diabetes: The Study of Women's Health Across the Nation (SWAN). Diabetes Care 2024; 47:676-682. [PMID: 38320264 PMCID: PMC10973900 DOI: 10.2337/dc23-1630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/23/2023] [Indexed: 02/08/2024]
Abstract
OBJECTIVE To investigate the associations of longitudinal changes in sex hormone binding globulin (SHBG) and testosterone (T) over the menopause transition with the risk of diabetes. RESEARCH DESIGN AND METHODS We followed 2,952 participants in the Study of Women's Health Across the Nation (SWAN) who were premenopausal or early perimenopausal and diabetes-free at baseline. SHBG,T, and estradiol (E2) levels were measured at up to 13 follow-up visits (over up to 17 years). We used complementary log-log-based discrete-time survival models anchored at baseline. RESULTS Diabetes developed in 376 women. A 5-unit increase in time-varying SHBG was associated with a 10% reduced risk of diabetes (hazard ratio [HR] 0.91, 95% CI 0.87-0.95), adjusting for covariates, and baseline SHBG,T, and E2 levels. Time-varying T was not associated with diabetes risk. Compared with the lowest quartile for annual rate of change of SHBG since baseline (quartile 1 [Q1] -92.3 to -1.5 nmol/L), all other quartiles were associated with a decreased risk of diabetes adjusting for covariates and baseline SHBG; associations persisted after adjusting for rate of change of T and E2 (Q2 [> -1.5 to -0.2 nmol/L] HR 0.33, 95% CI 0.23-0.48; Q3 [> -0.2 to 1.3 nmol/L] HR 0.37, 95% CI 0.25-0.55; Q4 [>1.3 to 82.0 nmol/L] HR 0.43, 95% CI 0.30-0.63). CONCLUSIONS Increasing levels of SHBG over the menopause transition were associated with a decreased risk of incident diabetes. Stable to increasing rates of change in SHBG were also independently associated with a decreased risk of diabetes compared with decreasing rates of change, suggesting SHBG may affect glucose through a mechanism beyond androgenicity.
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Affiliation(s)
| | - Angela Capra
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Catherine Lee
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Laurel A. Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | | | | | - Sylvia E. Badon
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Susanna D. Mitro
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
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Pan M, Zhou MY, Jiang C, Zhang Z, Bui NQ, Bien J, Siy A, Achacoso N, Solorzano AV, Tse P, Chung E, Thomas S, Habel LA, Ganjoo KN. Sex-dependent Prognosis of Patients with Advanced Soft Tissue Sarcoma. Clin Cancer Res 2024; 30:413-419. [PMID: 37831066 PMCID: PMC10792361 DOI: 10.1158/1078-0432.ccr-23-1990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/25/2023] [Accepted: 10/11/2023] [Indexed: 10/14/2023]
Abstract
PURPOSE To examine whether overall survival (OS) differs for male and female patients with advanced soft-tissue sarcoma (STS). EXPERIMENTAL DESIGN The study included patients from Kaiser Permanente Northern California and Stanford Cancer Center with grade 2 and 3 locally advanced or metastatic STS whose tumor underwent next-generation sequencing. We used Cox regression modeling to examine association of sex and OS adjusting for other important factors. RESULTS Among 388 eligible patients, 174 had leiomyosarcoma (LMS), 136 had undifferentiated pleomorphic sarcoma (UPS), and 78 had liposarcoma. OS for male versus female patients appeared to be slightly better among the full cohort [HR = 0.89; 95% confidence interval (CI), 0.66-1.20]; this association appeared to be stronger among the subsets of patients with LMS (HR = 0.76; 95% CI, 0.39-1.49) or liposarcoma (HR = 0.74; 95% CI, 0.32-1.70). Better OS for male versus female patients was also observed among all molecular subgroups except mutRB1 and mutATRX, especially among patients whose tumor retained wtTP53 (HR = 0.73; 95% CI, 0.44-1.18), wtCDKN2A (HR = 0.85; 95% CI, 0.59-1.23), wtRB1 (HR = 0.73; 95% CI, 0.51-1.04), and among patients whose tumor had mutPTEN (HR = 0.37; 95% CI, 0.09-1.62). OS also appeared to be better for males in the MSK-IMPACT and TCGA datasets. CONCLUSIONS A fairly consistent pattern of apparent better OS for males across histologic and molecular subgroups of STS was observed. If confirmed, our results could have implications for clinical practice for prognostic stratification and possibly treatment tailoring as well as for future clinical trials design.
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Affiliation(s)
- Minggui Pan
- Sarcoma Program, Division of Oncology, Stanford University School of Medicine, Stanford, California
- Division of Research, Kaiser Permanente, Oakland, California
| | - Maggie Yuxi Zhou
- Sarcoma Program, Division of Oncology, Stanford University School of Medicine, Stanford, California
| | - Chen Jiang
- Division of Research, Kaiser Permanente, Oakland, California
| | - Zheyang Zhang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University; and National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, China
| | - Nam Q. Bui
- Sarcoma Program, Division of Oncology, Stanford University School of Medicine, Stanford, California
| | - Jeffrey Bien
- Sarcoma Program, Division of Oncology, Stanford University School of Medicine, Stanford, California
| | - Amanda Siy
- Sarcoma Program, Division of Oncology, Stanford University School of Medicine, Stanford, California
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente, Oakland, California
| | | | - Pamela Tse
- Division of Research, Kaiser Permanente, Oakland, California
| | - Elaine Chung
- Division of Research, Kaiser Permanente, Oakland, California
| | - Sachdev Thomas
- Department of Oncology and Hematology, Kaiser Permanente, Vallejo, California
| | - Laurel A. Habel
- Division of Research, Kaiser Permanente, Oakland, California
| | - Kristen N. Ganjoo
- Sarcoma Program, Division of Oncology, Stanford University School of Medicine, Stanford, California
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Shim VC, Baker RJ, Jing W, Puentes R, Agersborg SS, Lee TK, GoreaI W, Achacoso N, Lee C, Villasenor M, Lin A, Kapali M, Habel LA. Evaluation of the international Ki67 working group cut point recommendations for early breast cancer: comparison with 21-gene assay results in a large integrated health care system. Breast Cancer Res Treat 2024; 203:281-289. [PMID: 37847456 PMCID: PMC10787679 DOI: 10.1007/s10549-023-07118-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 08/24/2023] [Indexed: 10/18/2023]
Abstract
PURPOSE The International Ki67 Working Group (IKWG) has developed training for immunohistochemistry (IHC) scoring reproducibility and recommends cut points of ≤ 5% and ≥ 30% for prognosis in ER+, HER2-, stage I/II breast cancer. We examined scoring reproducibility following IKWG training and evaluated these cut points for selecting patients for further testing with the 21-gene Recurrence Score (RS) assay. METHODS We included 307 women aged 50+ years with node-negative, ER+PR+HER2- breast cancer and with available RS results. Slides from the diagnostic biopsy were stained for Ki67 and scored using digital image analysis (IA). Two IHC pathologists underwent IKWG training and visually scored slides, blinded to each other and IA readings. Interobserver reproducibility was examined using intraclass correlation (ICC) and Kappa statistics. RESULTS Depending on reader, 8.8-16.0% of our cohort had Ki67 ≤ 5% and 11.4-22.5% had scores ≥ 30%. The ICC for Ki67 scores by the two pathologists was 0.82 (95% CI 0.78-0.85); it was 0.79 (95% CI 0.74-0.83) for pathologist 1 and IA and 0.76 (95% CI 0.71-0.80) for pathologist 2 and IA. For Ki67 scores ≤ 5%, the percentages with RS < 26 were 92.6%, 91.8%, and 90.9% for pathologist 1, pathologist 2, and IA, respectively. For Ki67 scores ≥ 30%, the percentages with RS ≥ 26 were 41.5%, 51.4%, and 27.5%, respectively. CONCLUSION The IKWG's Ki67 training resulted in moderate to strong reproducibility across readers but cut points had only moderate overlap with RS cut points, especially for Ki67 ≥ 30% and RS ≥ 26; thus, their clinical utility for a 21-gene assay testing pathway remains unclear.
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Affiliation(s)
- Veronica C Shim
- The Permanente Medical Group, Northern California Kaiser Permanente, Oakland, CA, USA
| | - Robin J Baker
- The Permanente Medical Group, Northern California Kaiser Permanente, San Francisco, CA, USA
| | - Wen Jing
- The Permanente Medicine, Northern California Kaiser Permanente, San Francisco, CA, USA
| | | | | | - Thomas K Lee
- NeoGenomics Laboratories, Inc., Aliso Viejo, CA, USA
| | - Wamda GoreaI
- NeoGenomics Laboratories, Inc., Aliso Viejo, CA, USA
| | - Ninah Achacoso
- The Division of Research, Northern California Kaiser Permanente, 2000 Broadway, Oakland, CA, 94612, USA
| | - Catherine Lee
- The Division of Research, Northern California Kaiser Permanente, 2000 Broadway, Oakland, CA, 94612, USA
| | - Marvella Villasenor
- The Division of Research, Northern California Kaiser Permanente, 2000 Broadway, Oakland, CA, 94612, USA
| | - Amy Lin
- The Permanente Medical Group, Northern California Kaiser Permanente, San Francisco, CA, USA
| | - Malathy Kapali
- The Permanente Medical Group, Northern California Kaiser Permanente, Sacramento, CA, USA
| | - Laurel A Habel
- The Division of Research, Northern California Kaiser Permanente, 2000 Broadway, Oakland, CA, 94612, USA.
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Waites BT, Lyon L, Kuehner G, Odele P, Habel LA, Liu R. Mode of Detection of Second Breast Cancers in Patients Undergoing Surveillance After Treatment of Ductal Carcinoma in Situ. J Natl Compr Canc Netw 2023; 22:e237082. [PMID: 38154251 DOI: 10.6004/jnccn.2023.7082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 09/01/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND For patients undergoing posttreatment surveillance after ductal carcinoma in situ (DCIS), the NCCN Guidelines for Breast Cancer recommend annual breast imaging and physical examination every 6 to 12 months for 5 years, and then annually. The aim of our study was to evaluate the modes of detection (imaging, patient reported, or physical examination) of second cancers in a cohort of patients undergoing surveillance after primary DCIS treatment to better inform surveillance recommendations. METHODS We performed a retrospective cohort study of patients with DCIS treated between January 1, 2008, and December 31, 2011, within a large integrated health care system. Information on patient demographics, index DCIS treatment, tumor characteristics, and mode of detection of second breast cancer was obtained from the electronic health record or chart review. RESULTS Our study cohort consisted of 1,550 women, with a median age of 59 years at diagnosis. Surgical treatment of DCIS included lumpectomy (75.0%; n=1,162), unilateral mastectomy (21.1%; n=327), or bilateral mastectomy (3.9%; n=61), with or without sentinel lymph node biopsy. Additionally, 44.4% (n=688) and 28.3% (n=438) received radiation and endocrine therapies, respectively. Median follow-up was 10 years, during which 179 (11.5%) women were diagnosed with a second breast cancer. Of the second cancers, 43.0% (n=77) were ipsilateral and 54.8% (n=98) contralateral, and 2.2% (n=4) presented with distant metastases; 61.5% (n=110) were invasive, 36.3% (n=65) were DCIS, and 2.2% (n=4) were Paget's disease. Second breast cancers were imaging-detected in 74.3% (n=133) of cases, patient-detected in 20.1% (n=36), physician-detected in 2.2% (n=4), and detected incidentally on imaging or pathology from procedures unrelated to oncologic care in 3.4% (n=6). CONCLUSIONS In our cohort of patients undergoing surveillance following diagnosis and treatment of DCIS, 2% of second breast cancers were detected by a clinical breast examination. This suggests that survivorship care should prioritize mammography and patient education regarding breast self-examination and symptoms that warrant evaluation to detect second breast cancers.
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Affiliation(s)
- Bethany T Waites
- 1Kaiser Permanente San Francisco Medical Center, San Francisco, California
| | - Liisa Lyon
- 2Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Gillian Kuehner
- 3Kaiser Permanente Vallejo Medical Center, Vallejo, California
| | - Patience Odele
- 4Kaiser San Rafael Medical Center, San Rafael, California
| | - Laurel A Habel
- 2Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Raymond Liu
- 1Kaiser Permanente San Francisco Medical Center, San Francisco, California
- 2Division of Research, Kaiser Permanente Northern California, Oakland, California
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Hsu DS, Jiang SF, Habel LA, Hoodfar E, Karlea A, Manace-Brenman L, Dzubnar JM, Shim VC. Germline Genetic Testing Among Women ≤ 45 Years of Age with Ductal Carcinoma In Situ Versus Invasive Breast Cancer in a Large Integrated Health Care System. Ann Surg Oncol 2023; 30:6454-6461. [PMID: 37386303 DOI: 10.1245/s10434-023-13745-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/31/2023] [Indexed: 07/01/2023]
Abstract
BACKGROUND We compared the results of hereditary cancer multigene panel testing among patients ≤ 45 years of age diagnosed with ductal carcinoma in situ (DCIS) versus invasive breast cancer (IBC) in a large integrated health care system. METHODS A retrospective cohort study of hereditary cancer gene testing among women ≤ 45 years of age diagnosed with DCIS or IBC at Kaiser Permanente Northern California between September 2019 and August 2020 was performed. During the study period, institutional guidelines recommended the above population be referred to genetic counselors for pretesting counseling and testing. RESULTS A total of 61 DCIS and 485 IBC patients were identified. Genetic counselors met with 95% of both groups, and 86.4% of DCIS patients and 93.9% of IBC patients (p = 0.0339) underwent gene testing. Testing differed by race/ethnicity (p = 0.0372). Among those tested, 11.76% (n = 6) of DCIS patients and 16.71% (n = 72) of IBC patients had a pathogenic variant (PV) or likely pathogenic variant (LPV) based on the 36-gene panel (p = 0.3650). Similar trends were seen in 13 breast cancer (BC)-related genes (p = 0.0553). Family history of cancer was significantly associated with both BC-related and non-BC-related PVs in IBC, but not DCIS. CONCLUSION In our study, 95% of patients were seen by a genetic counselor when age was used as an eligibility criterion for referral. While larger studies are needed to further compare the prevalence of PVs/LPVs among DCIS and IBC patients, our data suggest that even in younger patients, the prevalence of PVs/LPVs in BC-related genes is lower in DCIS patients.
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MESH Headings
- Humans
- Female
- Breast Neoplasms/epidemiology
- Breast Neoplasms/genetics
- Breast Neoplasms/pathology
- Carcinoma, Intraductal, Noninfiltrating/epidemiology
- Carcinoma, Intraductal, Noninfiltrating/genetics
- Carcinoma, Intraductal, Noninfiltrating/pathology
- Genetic Predisposition to Disease
- Retrospective Studies
- Carcinoma, Ductal, Breast/epidemiology
- Carcinoma, Ductal, Breast/genetics
- Carcinoma, Ductal, Breast/pathology
- Genetic Testing
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Affiliation(s)
- Diana S Hsu
- University of California San Francisco, East Bay, Oakland, CA, USA
| | | | - Laurel A Habel
- Division of Research, Kaiser Permanente, Oakland, CA, USA
| | | | - Audrey Karlea
- Department of Genetics, Kaiser Permanente, Oakland, CA, USA
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Vabistsevits M, Smith GD, Richardson TG, Richmond RC, Sieh W, Rothstein JH, Habel LA, Alexeeff SE, Lloyd-Lewis B, Sanderson E. The mediating role of mammographic density in the protective effect of early-life adiposity on breast cancer risk: a multivariable Mendelian randomization study. medRxiv 2023:2023.09.01.23294765. [PMID: 37693539 PMCID: PMC10491349 DOI: 10.1101/2023.09.01.23294765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Observational studies suggest that mammographic density (MD) may have a role in the unexplained protective effect of childhood adiposity on breast cancer risk. Here, we investigated a complex and interlinked relationship between puberty onset, adiposity, MD, and their effects on breast cancer using Mendelian randomization (MR). We estimated the effects of childhood and adulthood adiposity, and age at menarche on MD phenotypes (dense area (DA), non-dense area (NDA), percent density (PD)) using MR and multivariable MR (MVMR), allowing us to disentangle their total and direct effects. Next, we examined the effect of MD on breast cancer risk, including risk of molecular subtypes, and accounting for genetic pleiotropy. Finally, we used MVMR to evaluate whether the protective effect of childhood adiposity on breast cancer was mediated by MD. Childhood adiposity had a strong inverse effect on mammographic DA, while adulthood adiposity increased NDA. Later menarche had an effect of increasing DA and PD, but when accounting for childhood adiposity, this effect attenuated to the null. DA and PD had a risk-increasing effect on breast cancer across all subtypes. The MD single-nucleotide polymorphism (SNP) estimates were extremely heterogeneous, and examination of the SNPs suggested different mechanisms may be linking MD and breast cancer. Finally, MR mediation analysis estimated that 56% (95% CIs [32% - 79%]) of the childhood adiposity effect on breast cancer risk was mediated via DA. In this work, we sought to disentangle the relationship between factors affecting MD and breast cancer. We showed that higher childhood adiposity decreases mammographic DA, which subsequently leads to reduced breast cancer risk. Understanding this mechanism is of great importance for identifying potential targets of intervention, since advocating weight gain in childhood would not be recommended.
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Affiliation(s)
- Marina Vabistsevits
- University of Bristol, MRC Integrative Epidemiology Unit, Bristol, United Kingdom
- University of Bristol, Population Health Sciences, Bristol, United Kingdom
| | - George Davey Smith
- University of Bristol, MRC Integrative Epidemiology Unit, Bristol, United Kingdom
- University of Bristol, Population Health Sciences, Bristol, United Kingdom
| | - Tom G. Richardson
- University of Bristol, MRC Integrative Epidemiology Unit, Bristol, United Kingdom
- University of Bristol, Population Health Sciences, Bristol, United Kingdom
| | - Rebecca C. Richmond
- University of Bristol, MRC Integrative Epidemiology Unit, Bristol, United Kingdom
- University of Bristol, Population Health Sciences, Bristol, United Kingdom
| | - Weiva Sieh
- Icahn School of Medicine at Mount Sinai, Department of Genetics and Genomic Sciences, Department of Population Health Science and Policy, New York, NY, United States
- University of Texas MD Anderson Cancer Center, Department of Epidemiology, Houston, TX, United States
| | - Joseph H. Rothstein
- Icahn School of Medicine at Mount Sinai, Department of Genetics and Genomic Sciences, Department of Population Health Science and Policy, New York, NY, United States
- University of Texas MD Anderson Cancer Center, Department of Epidemiology, Houston, TX, United States
| | - Laurel A. Habel
- Kaiser Permanente Northern California, Division of Research, Oakland, CA, United States
| | - Stacey E. Alexeeff
- Kaiser Permanente Northern California, Division of Research, Oakland, CA, United States
| | - Bethan Lloyd-Lewis
- University of Bristol, School of Cellular and Molecular Medicine, Bristol, United Kingdom
| | - Eleanor Sanderson
- University of Bristol, MRC Integrative Epidemiology Unit, Bristol, United Kingdom
- University of Bristol, Population Health Sciences, Bristol, United Kingdom
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Habel LA, Alexeeff SE, Achacoso N, Arasu VA, Gastounioti A, Gerstley L, Klein RJ, Liang RY, Lipson JA, Mankowski W, Margolies LR, Rothstein JH, Rubin DL, Shen L, Sistig A, Song X, Villaseñor MA, Westley M, Whittemore AS, Yaffe MJ, Wang P, Kontos D, Sieh W. Examination of fully automated mammographic density measures using LIBRA and breast cancer risk in a cohort of 21,000 non-Hispanic white women. Breast Cancer Res 2023; 25:92. [PMID: 37544983 PMCID: PMC10405373 DOI: 10.1186/s13058-023-01685-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 07/09/2023] [Indexed: 08/08/2023] Open
Abstract
BACKGROUND Breast density is strongly associated with breast cancer risk. Fully automated quantitative density assessment methods have recently been developed that could facilitate large-scale studies, although data on associations with long-term breast cancer risk are limited. We examined LIBRA assessments and breast cancer risk and compared results to prior assessments using Cumulus, an established computer-assisted method requiring manual thresholding. METHODS We conducted a cohort study among 21,150 non-Hispanic white female participants of the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California who were 40-74 years at enrollment, followed for up to 10 years, and had archived processed screening mammograms acquired on Hologic or General Electric full-field digital mammography (FFDM) machines and prior Cumulus density assessments available for analysis. Dense area (DA), non-dense area (NDA), and percent density (PD) were assessed using LIBRA software. Cox regression was used to estimate hazard ratios (HRs) for breast cancer associated with DA, NDA and PD modeled continuously in standard deviation (SD) increments, adjusting for age, mammogram year, body mass index, parity, first-degree family history of breast cancer, and menopausal hormone use. We also examined differences by machine type and breast view. RESULTS The adjusted HRs for breast cancer associated with each SD increment of DA, NDA and PD were 1.36 (95% confidence interval, 1.18-1.57), 0.85 (0.77-0.93) and 1.44 (1.26-1.66) for LIBRA and 1.44 (1.33-1.55), 0.81 (0.74-0.89) and 1.54 (1.34-1.77) for Cumulus, respectively. LIBRA results were generally similar by machine type and breast view, although associations were strongest for Hologic machines and mediolateral oblique views. Results were also similar during the first 2 years, 2-5 years and 5-10 years after the baseline mammogram. CONCLUSION Associations with breast cancer risk were generally similar for LIBRA and Cumulus density measures and were sustained for up to 10 years. These findings support the suitability of fully automated LIBRA assessments on processed FFDM images for large-scale research on breast density and cancer risk.
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Affiliation(s)
- Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, CA, Oakland, USA.
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, CA, Oakland, USA
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, CA, Oakland, USA
| | - Vignesh A Arasu
- Division of Research, Kaiser Permanente Northern California, CA, Oakland, USA
- Department of Radiology, Kaiser Permanente Northern California, Vallejo, CA, USA
| | - Aimilia Gastounioti
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Lawrence Gerstley
- Division of Research, Kaiser Permanente Northern California, CA, Oakland, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rhea Y Liang
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jafi A Lipson
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Walter Mankowski
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Laurie R Margolies
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joseph H Rothstein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Daniel L Rubin
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Li Shen
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, NY, New York, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Adriana Sistig
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, NY, New York, USA
| | - Xiaoyu Song
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Mark Westley
- Division of Research, Kaiser Permanente Northern California, CA, Oakland, USA
| | - Alice S Whittemore
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Martin J Yaffe
- Sunnybrook Research Institute and Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Despina Kontos
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Weiva Sieh
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
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8
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Vuong B, Darbinian J, Savitz A, Odele P, Perry LM, Sandhu L, Habel LA, Kuehner G. Breast Cancer Recurrence by Subtype in a Diverse, Contemporary Cohort of Young Women. J Am Coll Surg 2023; 237:13-23. [PMID: 37052317 DOI: 10.1097/xcs.0000000000000714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Abstract
BACKGROUND Young breast cancer (YBC) patients are a unique subpopulation that are often underrepresented in randomized clinical trials. Furthermore, large national cancer databases lack detailed information on recurrence, a meaningful oncologic outcome for young patients. STUDY DESIGN A retrospective review of YBC patients (age 40 years or younger) with stage I to III breast cancer diagnosed from 2008 to 2018 was performed. Information on clinicopathologic characteristics, demographics, and outcomes was obtained from the electronic health record and chart review. Chi-square and Fisher's exact tests were used for comparisons of categorical variables and parametric and nonparametric tests for continuous variables. RESULTS The cohort included 1,431 women with a median follow-up of 4.8 years (range 0.3 to 12.9 years). The median age was 37 years (interquartile range 34 to 39). The study population included 598 (41.8%) White, 112 (7.8%) Black, 420 (29.4%) Asian/Pacific Islander, 281 (19.6%) Hispanic, and 20 (1.4%) "other" race/ethnicity patients. Tumor subtype was as follows: [1] hormone receptor (HR) + /human epidermal growth factor 2 (HER2 - ), grade (G) 1 to 2 = 541 (37.8%); [2] HR + /HER2 - , G3 = 268 (18.7%); [3] HR + /HER2 + = 262 (18.3%); [4] HR - /HER2 + = 101 (7.1%); [5] HR - /HER2 - = 259 (18.1%). The majority (64.2%) presented with stage II/III disease. There were 230 (16.1%) recurrences during follow-up; 74.8% were distant. Locoregional-only recurrence was seen in 17 of 463 (3.7%) patients who underwent breast conservation vs 41 of 968 (4.2%) patients undergoing mastectomy (p < 0.001). Recurrence varied by tumor subtype: [1] HR + /HER2 - , G1 to 2 (14.0%); [2] HR + /HER2 - , G3 (20.9%); [3] HR + /HER2 + (11.1%); [4] HR - /HER2 + (22.8%); [5] HR - /HER2 - (17.8%) (p = 0.005). CONCLUSIONS In this large, diverse YBC cohort, recurrences were most frequent among HR + /HER2 - , G3, or HR - /HER2 + invasive tumors; most were distant. There were numerically similar locoregional-only recurrences after breast conservation vs mastectomy. Additional research is needed to identify predictors of recurrence.
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Affiliation(s)
- Brooke Vuong
- From the Department of Surgery, Kaiser Permanente South Sacramento Medical Center, Sacramento, CA (Vuong, Sandhu)
| | - Jeanne Darbinian
- the Division of Research, Kaiser Permanente Northern California, Oakland, CA (Darbinian, Habel)
| | - Alison Savitz
- the Department of Surgery, Kaiser Permanente Walnut Creek Medical Center, Walnut Creek, CA (Savitz)
| | - Patience Odele
- the Department of Surgery, Kaiser Permanente San Rafael Medical Center, San Rafael, CA (Odele)
| | - Lauren M Perry
- the Department of Surgery, University of California, Davis, Sacramento, CA (Perry)
| | - Lakhbir Sandhu
- From the Department of Surgery, Kaiser Permanente South Sacramento Medical Center, Sacramento, CA (Vuong, Sandhu)
| | - Laurel A Habel
- the Division of Research, Kaiser Permanente Northern California, Oakland, CA (Darbinian, Habel)
| | - Gillian Kuehner
- the Department of Surgery, Kaiser Permanente Vallejo Medical Center, Vallejo, CA (Kuehner)
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9
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Arasu VA, Habel LA, Achacoso NS, Buist DSM, Cord JB, Esserman LJ, Hylton NM, Glymour MM, Kornak J, Kushi LH, Lewis DA, Liu VX, Lydon CM, Miglioretti DL, Navarro DA, Pu A, Shen L, Sieh W, Yoon HC, Lee C. Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study. Radiology 2023; 307:e222733. [PMID: 37278627 DOI: 10.1148/radiol.222733] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Background Although several clinical breast cancer risk models are used to guide screening and prevention, they have only moderate discrimination. Purpose To compare selected existing mammography artificial intelligence (AI) algorithms and the Breast Cancer Surveillance Consortium (BCSC) risk model for prediction of 5-year risk. Materials and Methods This retrospective case-cohort study included data in women with a negative screening mammographic examination (no visible evidence of cancer) in 2016, who were followed until 2021 at Kaiser Permanente Northern California. Women with prior breast cancer or a highly penetrant gene mutation were excluded. Of the 324 009 eligible women, a random subcohort was selected, regardless of cancer status, to which all additional patients with breast cancer were added. The index screening mammographic examination was used as input for five AI algorithms to generate continuous scores that were compared with the BCSC clinical risk score. Risk estimates for incident breast cancer 0 to 5 years after the initial mammographic examination were calculated using a time-dependent area under the receiver operating characteristic curve (AUC). Results The subcohort included 13 628 patients, of whom 193 had incident cancer. Incident cancers in eligible patients (additional 4391 of 324 009) were also included. For incident cancers at 0 to 5 years, the time-dependent AUC for BCSC was 0.61 (95% CI: 0.60, 0.62). AI algorithms had higher time-dependent AUCs than did BCSC, ranging from 0.63 to 0.67 (Bonferroni-adjusted P < .0016). Time-dependent AUCs for combined BCSC and AI models were slightly higher than AI alone (AI with BCSC time-dependent AUC range, 0.66-0.68; Bonferroni-adjusted P < .0016). Conclusion When using a negative screening examination, AI algorithms performed better than the BCSC risk model for predicting breast cancer risk at 0 to 5 years. Combined AI and BCSC models further improved prediction. © RSNA, 2023 Supplemental material is available for this article.
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Affiliation(s)
- Vignesh A Arasu
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Laurel A Habel
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Ninah S Achacoso
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Diana S M Buist
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Jason B Cord
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Laura J Esserman
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Nola M Hylton
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - M Maria Glymour
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - John Kornak
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Lawrence H Kushi
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Donald A Lewis
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Vincent X Liu
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Caitlin M Lydon
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Diana L Miglioretti
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Daniel A Navarro
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Albert Pu
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Li Shen
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Weiva Sieh
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Hyo-Chun Yoon
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
| | - Catherine Lee
- From the Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612 (V.A.A., L.A.H., N.S.A., L.H.K., V.X.L., C.M.L., C.L.); Department of Radiology, Kaiser Permanente Northern California, Vallejo Medical Center, Vallejo, Calif (V.A.A.); Kaiser Permanente Washington Health Research Institute, Seattle, Wash (D.S.M.B.); Department of Radiology, Southern California Permanente Medical Group, Orange County, Irvine, Calif (J.B.C.); Department of Surgery (L.J.E.), Department of Radiology and Biomedical Imaging (N.M.H.), and Department of Epidemiology and Biostatistics (M.M.G., J.K.), University of California-San Francisco, San Francisco, Calif; Department of Medical Imaging Technology and Informatics, Southern California Permanente Medical Group, Pasadena, Calif (D.A.L.); Department of Biostatistics, University of California-Davis, Davis, Calif (D.L.M.); The Technology Group, The Permanente Medical Group, Oakland, Calif (D.A.N.); KP Information Technology, Kaiser Foundation Health Plan Inc and Kaiser Foundation Hospitals, Oakland, Calif (A.P.); Department of Artificial Intelligence and Human Health and Nash Family Department of Neuroscience (L.S.) and Department of Population Health Science and Policy, Department of Genetics and Genomic Sciences (W.S.), Icahn School of Medicine at Mount Sinai, New York, NY; and Department of Radiology, Hawaii Permanente Medical Group, Moanalua Medical Center, Honolulu, Hawaii (H.C.Y.)
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10
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Pan M, Jiang C, Zhang Z, Achacoso N, Solorzano-Pinto AV, Tse P, Chung E, Suga JM, Thomas S, Habel LA. Sex- and Co-Mutation-Dependent Prognosis in Patients with SMARCA4-Mutated Malignancies. Cancers (Basel) 2023; 15:2665. [PMID: 37345003 DOI: 10.3390/cancers15102665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/12/2023] [Accepted: 05/03/2023] [Indexed: 06/23/2023] Open
Abstract
BACKGROUND Whether sex and co-mutations impact prognosis of patients with SMARCA4-mutated (mutSMARCA4) malignancies is not clear. METHODS This cohort included patients from Northern California Kaiser Permanente with next-generation sequencing (NGS) performed from August 2020 to October 2022. We used Cox regression modeling to examine the association between sex and overall survival (OS), adjusting for demographics, performance status, Charlson comorbidity index, receipt of treatment, tumor mutation burden (TMB), and TP53, KRAS, CDKN2A, STK11, and Keap1 co-mutations. RESULTS Out of 9221 cases with NGS performed, 125 cases (1.4%) had a mutSMARCA4. The most common malignancies with a mutSMARCA4 were non-small cell lung cancer (NSCLC, 35.2%), esophageal and stomach adenocarcinoma (12.8%), and cancer of unknown primary (11.2%). The most common co-mutations were p53 (mutp53, 59.2%), KRAS (mutKRAS, 28.8%), CDKN2A (mutCDKN2A, 31.2%), STK11 (mutSTK11, 12.8%), and Keap1 (mutKeap1, 8.8%) mutations. Male patients had substantially worse OS than female patients both among the entire mutSMARCA4 cohort (HR = 1.71, [95% CI 0.92-3.18]) with a median OS of 3.0 versus 43.3 months (p < 0.001), and among the NSCLC subgroup (HR = 14.2, [95% CI 2.76-73.4]) with a median OS of 2.75 months versus un-estimable (p = 0.02). Among all patients with mutSMARCA4, mutp53 versus wtp53 (HR = 2.12, [95% CI 1.04-4.29]) and mutSTK11 versus wtSTK11 (HR = 2.59, [95% CI 0.87-7.73]) were associated with worse OS. Among the NSCLC subgroup, mutp53 versus wtp53 (HR = 0.35, [0.06-1.97]) and mutKRAS versus wtKRAS (HR = 0.04, [0.003-.45]) were associated with better OS, while mutCDKN2A versus wtCDKN2A (HR = 5.04, [1.12-22.32]), mutSTK11 versus wtSTK11 (HR = 13.10, [95% CI 1.16-148.26]), and mutKeap1 versus wtKeap1 (HR = 5.06, [95% CI 0.89-26.61}) were associated with worse OS. CONCLUSION In our cohort of patients with mutSMARCA4, males had substantially worse prognosis than females, while mutTP53, mutKRAS, mutCDKN2A, mutSTK11 and mutKeap1were differentially associated with prognosis among all patients and among the NSCLC subgroup. Our results, if confirmed, could suggest potentially unidentified mechanisms that underly this sex and co-mutation-dependent prognostic disparity among patients whose tumor bears a mutSMARCA4.
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Affiliation(s)
- Minggui Pan
- Department of Oncology and Hematology, Kaiser Permanente, Santa Clara, CA 94051, USA
- Division of Research, Kaiser Permanente, Oakland, CA 94612, USA
- Division of Oncology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Chen Jiang
- Division of Research, Kaiser Permanente, Oakland, CA 94612, USA
| | - Zheyang Zhang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, and National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361102, China
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente, Oakland, CA 94612, USA
| | | | - Pam Tse
- Division of Research, Kaiser Permanente, Oakland, CA 94612, USA
| | - Elaine Chung
- Division of Research, Kaiser Permanente, Oakland, CA 94612, USA
| | - Jennifer Marie Suga
- Department of Oncology and Hematology, Kaiser Permanente, Vallejo, CA 94589, USA
| | - Sachdev Thomas
- Department of Oncology and Hematology, Kaiser Permanente, Vallejo, CA 94589, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente, Oakland, CA 94612, USA
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11
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Hicks B, Kaye JA, Azoulay L, Kristensen KB, Habel LA, Pottegård A. The Application of Lag Times in Cancer Pharmacoepidemiology: A Narrative Review. Ann Epidemiol 2023:S1047-2797(23)00090-X. [PMID: 37169040 DOI: 10.1016/j.annepidem.2023.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 04/27/2023] [Accepted: 05/05/2023] [Indexed: 05/13/2023]
Abstract
With the increasing utilization of medications worldwide, coupled with the increasing availability of long-term data, there is a growing opportunity and need for robust studies evaluating drug-cancer associations. One methodology of importance in such studies is the application of lag times. In this review, we discuss the main reasons for using lag times. Namely, we discuss the typically long latency period of cancer concerning both tumor promoter and initiator effects and outline why cancer latency is a key consideration when choosing a lag time. We also discuss how the use of lag times can help reduce protopathic and detection bias. Finally, we present practical advice for implementing lag periods. In general, we recommend that researchers consider the information that generated the hypothesis as well as clinical and biological knowledge to inform lag period selection. In addition, given that latency periods are usually unknown, we also advocate that researchers examine multiple lag periods in sensitivity analyses as well as duration analyses and flexible modeling approaches.
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Affiliation(s)
- Blánaid Hicks
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK; RTI Health Solutions, Waltham, Massachusetts; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada; Centre for Clinical Epidemiology, Lady Davis Institute, Montreal, Québec, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Québec, Canada; Clinical Pharmacology,Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Denmark; Division of Research, Kaiser Permanente Northern California, Oakland, California.
| | - James A Kaye
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK; RTI Health Solutions, Waltham, Massachusetts; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada; Centre for Clinical Epidemiology, Lady Davis Institute, Montreal, Québec, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Québec, Canada; Clinical Pharmacology,Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Denmark; Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Laurent Azoulay
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK; RTI Health Solutions, Waltham, Massachusetts; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada; Centre for Clinical Epidemiology, Lady Davis Institute, Montreal, Québec, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Québec, Canada; Clinical Pharmacology,Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Denmark; Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Kasper Bruun Kristensen
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK; RTI Health Solutions, Waltham, Massachusetts; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada; Centre for Clinical Epidemiology, Lady Davis Institute, Montreal, Québec, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Québec, Canada; Clinical Pharmacology,Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Denmark; Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Laurel A Habel
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK; RTI Health Solutions, Waltham, Massachusetts; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada; Centre for Clinical Epidemiology, Lady Davis Institute, Montreal, Québec, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Québec, Canada; Clinical Pharmacology,Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Denmark; Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Anton Pottegård
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK; RTI Health Solutions, Waltham, Massachusetts; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada; Centre for Clinical Epidemiology, Lady Davis Institute, Montreal, Québec, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Québec, Canada; Clinical Pharmacology,Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Denmark; Division of Research, Kaiser Permanente Northern California, Oakland, California
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12
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Pan M, Jiang C, Zhang Z, Achacoso N, Alexeeff S, Solorzano AV, Tse P, Chung E, Sundaresan T, Suga JM, Thomas S, Habel LA. TP53 Gain-of-Function and Non-Gain-of-Function Mutations Are Associated With Differential Prognosis in Advanced Pancreatic Ductal Adenocarcinoma. JCO Precis Oncol 2023; 7:e2200570. [PMID: 37163715 DOI: 10.1200/po.22.00570] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023] Open
Abstract
PURPOSE To examine the impact of TP53 gain-of-function (GOF) and non-GOF mutations on prognosis of advanced pancreatic ductal adenocarcinoma (PDAC) among patients with KRAS, CDKN2A, and SMAD4 comutations. METHODS This cohort included patients with locally advanced, recurrent, and de novo metastatic PDAC with next-generation sequencing performed from November 2017 to May 2022. We defined R175H, R248W, R248Q, R249S, R273H, R273L, and R282W as GOF and all other p53 mutations (mutp53) as non-GOF. We used Cox regression modeling to examine the association between GOF and non-GOF mutp53 and overall survival (OS), adjusting for demographics, performance status, Charlson comorbidity index, receipt of chemotherapy, and KRAS, CDKN2A, and SMAD4 comutations. RESULTS Of 893 total eligible patients, 68.5% had tumors with mutp53, 90.1% had KRAS mutations (mutKRAS), 44.7% had CDKN2A mutations (mutCDKN2A), and 17.0% had SMAD4 mutations. Among patients with mutp53, 121 had GOF and 491 had non-GOF. GOF mutp53 was associated with worse OS than non-GOF mutp53 (hazard ratio [HR], 1.27; 95% CI, 1.02 to 1.59) and wild-type p53 (wtp53; HR, 1.24; 95% CI, 0.98 to 1.57), whereas non-GOF was not associated with worse OS than wtp53 (HR, 0.95; 95% CI, 0.80 to 1.13). In addition, mutKRAS was associated with worse OS than wild-type KRAS in patients with mutCDKN2A (HR, 1.57; 95% CI, 0.88 to 2.80) but not in patients with wild-type CDKN2A (HR, 1.03; 95% CI, 0.76 to 1.39). CONCLUSION GOF and non-GOF mutp53 were associated with differential prognosis in advanced PDAC. The adverse effect of mutKRAS on OS appeared to be primarily driven by patients with mutCDKN2A. Our results provide new insight that could be helpful for prognostic stratification in clinical practice and for aiding future clinical trial designs.
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Affiliation(s)
- Minggui Pan
- Department of Oncology and Hematology, Kaiser Permanente, Santa Clara, CA
- Division of Research, Kaiser Permanente, Oakland, CA
| | - Chen Jiang
- Division of Research, Kaiser Permanente, Oakland, CA
| | - Zheyang Zhang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, China
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, China
| | | | | | | | - Pam Tse
- Division of Research, Kaiser Permanente, Oakland, CA
| | - Elaine Chung
- Division of Research, Kaiser Permanente, Oakland, CA
| | - Tilak Sundaresan
- Department of Oncology and Hematology, Kaiser Permanente, San Francisco, CA
| | | | - Sachdev Thomas
- Department of Oncology and Hematology, Kaiser Permanente, Santa Clara, CA
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13
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Song X, Ji J, Rothstein JH, Alexeeff SE, Sakoda LC, Sistig A, Achacoso N, Jorgenson E, Whittemore AS, Klein RJ, Habel LA, Wang P, Sieh W. MiXcan: a framework for cell-type-aware transcriptome-wide association studies with an application to breast cancer. Nat Commun 2023; 14:377. [PMID: 36690614 PMCID: PMC9871010 DOI: 10.1038/s41467-023-35888-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 01/05/2023] [Indexed: 01/25/2023] Open
Abstract
Human bulk tissue samples comprise multiple cell types with diverse roles in disease etiology. Conventional transcriptome-wide association study approaches predict genetically regulated gene expression at the tissue level, without considering cell-type heterogeneity, and test associations of predicted tissue-level expression with disease. Here we develop MiXcan, a cell-type-aware transcriptome-wide association study approach that predicts cell-type-level expression, identifies disease-associated genes via combination of cell-type-level association signals for multiple cell types, and provides insight into the disease-critical cell type. As a proof of concept, we conducted cell-type-aware analyses of breast cancer in 58,648 women and identified 12 transcriptome-wide significant genes using MiXcan compared with only eight genes using conventional approaches. Importantly, MiXcan identified genes with distinct associations in mammary epithelial versus stromal cells, including three new breast cancer susceptibility genes. These findings demonstrate that cell-type-aware transcriptome-wide analyses can reveal new insights into the genetic and cellular etiology of breast cancer and other diseases.
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Affiliation(s)
- Xiaoyu Song
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Jiayi Ji
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joseph H Rothstein
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Adriana Sistig
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Alice S Whittemore
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Robert J Klein
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Pei Wang
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Weiva Sieh
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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14
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Cavazos TB, Kachuri L, Graff RE, Nierenberg JL, Thai KK, Alexeeff S, Van Den Eeden S, Corley DA, Kushi LH, Hoffmann TJ, Ziv E, Habel LA, Jorgenson E, Sakoda LC, Witte JS. Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies. BMC Med 2022; 20:332. [PMID: 36199081 PMCID: PMC9535845 DOI: 10.1186/s12916-022-02535-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 08/17/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored. METHODS To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers. RESULTS We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer. CONCLUSIONS Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.
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Affiliation(s)
- Taylor B Cavazos
- Biological and Medical Informatics, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Linda Kachuri
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, 94158, USA.,Department of Epidemiology and Population Health, Stanford University, Alway Building, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, 94158, USA.,Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA
| | - Jovia L Nierenberg
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, 94158, USA.,Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Khanh K Thai
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA
| | - Stacey Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA
| | - Stephen Van Den Eeden
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA
| | | | - Thomas J Hoffmann
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Elad Ziv
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA
| | - Eric Jorgenson
- Department of Medicine, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, 94612, USA.,Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, 91101, USA
| | - John S Witte
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, 94158, USA. .,Department of Epidemiology and Population Health, Stanford University, Alway Building, 300 Pasteur Drive, Stanford, CA, 94305, USA. .,Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA.
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15
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Grimes NP, Bertone-Johnson ER, Whitcomb BW, Sievert LL, Crawford SL, Gold EB, Avis NE, Greendale GA, Santoro N, Habel LA, Reeves KW. Anti-Müllerian hormone levels and breast cancer risk in the study of women's health across the nation. Cancer Causes Control 2022; 33:1039-1046. [PMID: 35768642 PMCID: PMC10683710 DOI: 10.1007/s10552-022-01596-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 06/10/2022] [Indexed: 10/17/2022]
Abstract
PURPOSE The relation of premenopausal anti-Müllerian hormone (AMH) levels with breast cancer risk has been evaluated in a few studies, but primarily in non-Hispanic White women. METHODS We evaluated the association of AMH levels with breast cancer risk in Study of Women's Health Across the Nation (SWAN), a multi-ethnic cohort of women. At enrollment, participants had an intact uterus and ≥ 1 ovary, and ≥ 1 menstrual period in the last 3 months. AMH at first measurement was assessed in 1,529 pre- or perimenopausal women using a high-sensitivity ELISA assay; values were natural log transformed. Breast cancer diagnoses were assessed at enrollment and subsequent follow-up visits through 2018 (median 6.1 years). RESULTS In total, 84 women reported an incident breast cancer diagnosis. In multivariable Cox regression models adjusting for age, race and ethnicity, body mass index, and other factors, higher AMH levels were associated with a non-significant increased breast cancer risk. Compared to women in the 1st quartile, the hazard ratio (95% confidence interval) for women in the 4th quartile was 1.77 (0.87-3.60). CONCLUSION Our results did not suggest a significant association between AMH and breast cancer risk; however, estimates were consistent with prior studies that reported positive associations.
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Affiliation(s)
- Nydjie P Grimes
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 715 North Pleasant Street, Amherst, MA, 01003, USA.
| | - Elizabeth R Bertone-Johnson
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 715 North Pleasant Street, Amherst, MA, 01003, USA
- Department of Health Promotion and Policy, University of Massachusetts Amherst, Amherst, MA, USA
| | - Brian W Whitcomb
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 715 North Pleasant Street, Amherst, MA, 01003, USA
| | - Lynnette L Sievert
- Department of Anthropology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Sybil L Crawford
- Graduate School of Nursing, University of Massachusetts Medical School, Worcester, MA, USA
| | - Ellen B Gold
- Department of Public Health Sciences, University of California Davis, Davis, CA, USA
| | - Nancy E Avis
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Gail A Greendale
- David Geffen School of Medicine, University of California, Los Angeles, USA
| | - Nanette Santoro
- Department of Obstetrics and Gynecology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Katherine W Reeves
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, 715 North Pleasant Street, Amherst, MA, 01003, USA
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Tang A, Neeman E, Kuehner GE, Savitz AC, Mentakis M, Vuong B, Arasu VA, Liu R, Lyon LL, Anshu P, Seaward SA, Patel MD, Habel LA, Kushi LH, Thomas ES, Kolevska T, Chang SB. Telehealth for Preoperative Evaluation of Patients With Breast Cancer During the COVID-19 Pandemic. Perm J 2022; 26:54-63. [DOI: 10.7812/tpp/21.126] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Annie Tang
- Department of Surgery, University of California San Francisco, Oakland, CA, USA
| | - Elad Neeman
- Department of Medical Oncology, Kaiser Permanente San Francisco Medical Center, San Francisco, CA, USA
| | - Gillian E Kuehner
- Department of Surgery, Kaiser Permanente Vallejo Medical Center, Vallejo, CA, USA
| | - Alison C Savitz
- Department of Surgery, Kaiser Permanente Walnut Creek Medical Center, Walnut Creek, CA, USA
| | - Margaret Mentakis
- Department of Surgery, Kaiser Permanente South Sacramento Medical Center, Sacramento, CA, USA
| | - Brooke Vuong
- Department of Surgery, Kaiser Permanente South Sacramento Medical Center, Sacramento, CA, USA
| | - Vignesh A Arasu
- Department of Radiation Oncology, Kaiser Permanente Vallejo Medical Center, Vallejo, CA, USA
| | - Raymond Liu
- Department of Medical Oncology, Kaiser Permanente San Francisco Medical Center, San Francisco, CA, USA
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Liisa L Lyon
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Prachi Anshu
- Drexel University School of Medicine, Philadelphia, USA
| | - Samantha A Seaward
- Department of Radiation Oncology, Kaiser Permanente Oakland Medical Center, Oakland, CA, USA
| | - Milan D Patel
- Department of Radiation Oncology, Kaiser Permanente South San Francisco Medical Center, South San Francisco, CA, USA
| | - Laurel A Habel
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Lawrence H Kushi
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Eva S Thomas
- Department of Medical Oncology, Kaiser Permanente Oakland Medical Center, Oakland, CA, USA
| | - Tatjana Kolevska
- Department of Medical Oncology, Kaiser Permanente Vallejo Medical Center, Vallejo, CA, USA
| | - Sharon B Chang
- Department of Surgery, Kaiser Permanente Fremont Medical Center, Fremont, CA, USA
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Kristensen KB, Friis S, Lund LC, Hallas J, Cardwell CR, Andreassen BK, Habel LA, Pottegård A. Identification of Drug-Cancer Associations: A Nationwide Screening Study. Cancer Res Commun 2022; 2:552-560. [PMID: 36923552 PMCID: PMC10010324 DOI: 10.1158/2767-9764.crc-22-0026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 03/24/2022] [Accepted: 06/09/2022] [Indexed: 11/16/2022]
Abstract
The main tool in drug safety monitoring, spontaneous reporting of adverse effects, is unlikely to detect delayed adverse drug effects including cancer. Hypothesis-free screening studies based on administrative data could improve ongoing drug safety monitoring. Using Danish health registries, we conducted a series of case-control studies by identifying individuals with incident cancer in Denmark from 2001 to 2018, matching each case with 10 population controls on age, sex, and calendar time. ORs were estimated using conditional logistic regression accounting for matching factors, educational level, and selected comorbidities. A total of 13,577 drug-cancer associations were examined for individual drugs and 8,996 for drug classes. We reviewed 274 drug-cancer pairs where an association with high use and a cumulative dose-response pattern was present. We classified 65 associations as not readily attributable to bias of which 20 were established as carcinogens by the International Agency for Research on Cancer and the remaining 45 associations may warrant further study. The screening program identified drugs with known carcinogenic effects and highlighted a number of drugs that were not established as carcinogens and warrant further study. The effect estimates in this study should be interpreted cautiously and will need confirmation targeted epidemiologic and translational studies. Significance This study provides a screening tool for drug carcinogenicity aimed at hypothesis generation and explorative purposes. As such, the study may help to identify drugs with unknown carcinogenic effects and, ultimately, improve drug safety as part of the ongoing safety monitoring of drugs.
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Affiliation(s)
- Kasper Bruun Kristensen
- Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Søren Friis
- Danish Cancer Society Research Center, Danish Cancer Society, Copenhagen, Denmark
| | - Lars Christian Lund
- Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jesper Hallas
- Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Chris R. Cardwell
- Centre for Public Health, Queen's University Belfast, Belfast, United Kingdom
| | | | - Laurel A. Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Anton Pottegård
- Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
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18
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Pan M, Jiang C, Zhang Z, Achacoso N, Tse P, Solorzano A, Chung E, Sundaresan TK, Suga JM, Huang J, Thomas SP, Habel LA. TP53 gain-of-function mutations and impact on CDKN2A mutation on prognosis of pancreatic ductal adenocarcinoma. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.e16294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e16294 Background: Developmentally pancreas head derives from ventral bud while pancreas neck, body and tail derive from dorsal bud. Pancreatic ductal adenocarcinoma (PDAC) frequently harbors multiple mutations including KRAS, TP53, CDKN2A, and others. It is unknown how TP53 gain-of-function (GOF) and non-gain-of-function (non-GOF) mutations affect the prognosis. Methods: We retrospectively examined a cohort of 741 Kaiser Permanente (KP) patients with locally advanced/metastatic PDAC who had NGS performed to determine the association of KRAS (mutKRAS), TP53 (mutp53) and CDKN2A (mutCDKN2A) mutations (individually and in combination) with overall survival (OS). We used Cox modeling to estimate hazard ratios (HR) adjusted for age, sex, ethnicity, performance status, Charlston Comorbidity Index, chemotherapy received, anatomic location and co-mutations. We also analyzed the TCGA PDAC dataset to examine the association of OS with these same mutations. Results: In the KP cohort, patient ages ranged from 36 to 94 years and approximately 50% were female. In 384 patients PDAC was on the head, and 357 patients had PDAC on a non-head location (neck, body, and tail). Those with head PDAC had modestly better OS compared to non-head PDAC (HR = 0.87), and this appeared to be driven by the subsets of patients with wtp53 (HR = 0.68), with wtKRAS (HR = .74) and with wtCDKN2A (HR = .78). Approximately 67.5% of patients had mutp53, 89.2% had mutKRAS and 44.8% had mutCDKN2A. Among all KP patients, OS was similar for patients with mutp53 vs. wtp53 (HR = 1.05); worse for patients with mutKRAS vs. wtKRAS (HR = 1.26), and worse for patients with mutCDKN2 vs. wtCDKN2A (HR = 1.51). Interestingly, among patients with a GOF mutp53, those with mutCDKN2A had substantially worse OS vs patients with wtCDKN2A (HR = 2.56, 95% CI 1.46-4.50). In contrast, among patients with a non-GOF mutp53, patients with mutCDKN2A had only moderately worse OS compared to patients with wtCDKN2A (HR = 1.37, 95% CI 1.06-1.79). Analysis of the TCGA PDAC dataset showed that the number of mutations (0, 1, 2, or 3, of p53, KRAS and CDKN2A) was associated with incrementally worse OS ( p < .001). Conclusions: Better OS of head vs. non-head PDAC was primarily driven by patients with wtp53, wtKRAS, and wtCDKN2A. The adverse effect of mutCDKN2A on OS appears to be most pronounced in patients with GOF mutp53. Our TCGA analysis suggests interactions among TP53, KRAS and CDKN2A mutations in affecting PDAC survival.
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Affiliation(s)
- Minggui Pan
- Kaiser Permanente, Dept of Medical Oncology, Santa Clara, CA
| | - Chen Jiang
- Kaiser Permanente Northern California, Division of Research, Oakland, CA
| | | | | | - Pamela Tse
- Kaiser Permanente, Division of Research, Oakland, CA
| | | | - Elaine Chung
- Kaiser Permanente, Division of Research, Oakland, CA
| | - Tilak Kumar Sundaresan
- The Permanente Medical Group, Gastrointestinal Oncology, Northern California, Oakland, CA
| | - Jennifer Marie Suga
- Kaiser Permanente NCI Community Oncology Research Program and NCORP, Vallejo, CA
| | | | - Sachdev P. Thomas
- The Permanente Medical Group, Department of Hematology Oncology, Vallejo, CA
| | - Laurel A. Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
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19
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Waites B, Lyon L, Kuehner G, Odele P, Habel LA, Shirazi A, Liu R. Mode of detection of second breast cancers in patients undergoing surveillance after treatment of ductal carcinoma in situ. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
571 Background: The incidence of ductal carcinoma in situ (DCIS) has increased, resulting in more women undergoing post-treatment surveillance for second breast cancers. National Comprehensive Cancer Network (NCCN) guidelines recommend annual breast imaging and physical exam every 6-12 months for five years, and then annually. We assessed mode of detection (imaging, patient-reported, or physical exam) of secondary DCIS and/or invasive breast cancer in a large cohort of DCIS patients undergoing surveillance after treatment of primary DCIS. Methods: We performed a retrospective cohort study of DCIS patients treated between 1/1/2008 and 1/1/2011 within a large integrated health care system. Patients had a minimum of 5 years of follow up. Patient demographics, treatment for primary DCIS, and tumor characteristics (of both primary DCIS and secondary cancer) were obtained from the electronic health record or from manual chart review. Chart review also included mode of detection of secondary breast cancers. Results: Our study cohort consisted of 1561 women with DCIS, with a median age of 59 years (range 32-92) at time of diagnosis. Among initial DCIS tumors, tumor grade was low/intermediate in 942 (60.3%) and high in 619 (39.7%); 1274 (81.6%) were estrogen receptor positive, and 988 (63.3%) progesterone receptor positive. Surgical treatment for the initial DCIS included lumpectomy (n=1134, 72.6%), unilateral mastectomy (n=320, 20.5%), or bilateral mastectomy (n=61, 3.9%), and included sentinel lymph node biopsy in 211 (14%) of patients. Additionally, 691 (44.3%) received radiation therapy and 440 (28.2%) received endocrine therapy. The cohort was followed for a median of 120 months, during which we identified 179 women (11.5%) with a secondary cancer detected at a median time of 57 months. Of the second breast cancers, 77 (43.0%) were ipsilateral, 98 (54.8%) contralateral, and 4 (2.2%) presented with distant metastases; 110 (61.5%) were invasive, 65 (36.3%) were DCIS, and 4 (2.2%) Paget’s disease. See table for mode of detection of second breast cancers. Conclusions: In our cohort of patients undergoing surveillance following initial diagnosis and treatment of DCIS, 2% of secondary breast cancers were detected by clinical breast exam, a rate similar to incidental detection at time of plastic surgery. These results can help inform future recommendations for surveillance of second breast cancers in DCIS patients. [Table: see text]
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Affiliation(s)
- Bethany Waites
- Department of Obstetrics and Gynecology, Kaiser Permanente San Francisco, San Francisco, CA
| | - Liisa Lyon
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Gillian Kuehner
- Department of Surgery, The Permanente Medical Group, El Cerrito, CA
| | - Patience Odele
- Department of Surgery, The Permanente Medical Group, San Francisco, CA
| | - Laurel A. Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Aida Shirazi
- Department of Graduate Medical Education, Kaiser San Francisco, San Francisco, CA
| | - Raymond Liu
- The Permanente Medical Group, Department of Hematology Oncology, San Francisco, CA
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20
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Shim VC, Baker RJ, Jing W, Agersborg SS, Lee TK, Goreal W, Achacoso N, Lee C, Villasenor M, Lin A, Kapali M, Habel LA. Abstract P1-08-10: Ki67 assessment based on international Ki67 working group recommendations and correlation with 21-gene assay results in a large integrated health care system: We might not be there yet. Cancer Res 2022. [DOI: 10.1158/1538-7445.sabcs21-p1-08-10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: While substantial evidence indicates that Ki67, a marker of proliferation, is strongly associated with breast cancer outcomes, its clinical utility has been limited given concerns about scoring inter-rater reliability and appropriate cut points. Nonetheless, Ki67 has been used in multiple clinical trials and results from POETIC indicated that low baseline Ki67 (ie, <10%) predicts good prognosis in postmenopausal women with hormone sensitive, early breast cancer. Further, the International Ki67 Working Group (IKWG) has developed website-based training materials to improve reproducibility of Ki67 scoring by immunohistochemistry (IHC) and recently considered the marker to be sufficiently validated to support treatment decisions in early ER+ breast cancer (≤ 5 no chemotherapy, ≥30 chemotherapy indicated). Our aims were to examine Ki67 scoring reproducibility following IKWG training and the extent to which low or high scores could accurately identify patients with low or high 21-gene assay Recurrence Scores (RS) who could selectively avoid this test. Methods: Setting and study population. The study was conducted within Kaiser Permanente Northern California (KPNC), an integrated health care system with over 4.4 million enrollees. We included a random sample of women aged 50+ years at diagnosis of node-negative, ER+PR+HER2- breast cancer with the 21-gene assay done on their surgical specimen from 2018-2020 (n=307). Ki67 staining, training and scoring. We retrieved archived core biopsy specimens, which were sent to NeoGenomics Laboratories, Inc for Ki67 staining and scoring by image analysis (IA) using the hot spot counting method. In addition, two KPNC pathologists specializing in semiquantitative IHC scoring underwent IKWG training and independently scored all slides using the global counting method, blinded to each other and to readings by AI; weighted Ki67 scores were calculated. Analysis. We examined inter-rater reliability across pathologists using intraclass correlation (ICC) and Kappa statistics. We also examined the percent of patients with low Ki67 scores (≤ 5, <10) by each pathologist and by AI who also had low RS (<26) and the percent who had high Ki67 scores (≥30) who also had high RS (≥26). Results: Approximately 83% of patients were ages 50-69 years (median 63), 61% were non-Hispanic white and 93% were stage 1A. The ICC for Ki67 scores (log-transformed) by the two pathologists was 0.82; using a dichotomous cut point of <10 vs ≥10%, the Kappa for the inter-rater reliability was 0.65. Among patients with Ki67 scores of <10% by IA (n=81), pathologist 1 (n=120) or pathologist 2 (n=111), the percent with a RS of <26 was 95.1% for IA, 95.8% for pathologist 1, and 94.6% for pathologist 2. Among patients with Ki67 scores ≤5, the percentages were 90.9%, 92.6% and 91.8% for IA, pathologist 1 and pathologist 2, respectively. Among patients with Ki67 scores ≥30 by AI (n=69), pathologist 1 (n=41) or pathologist 2 (n=35), the percent who had a RS ≥26 was 27.5% for IA, 41.5% for pathologist 1 and 51.4% for pathologist 2. Results are improved if we exclude all 50 patients with weak PR by IHC (1-10%); for example, among patients with Ki67 scores of <10%, the percent with a RS of <26 was 97.1% for IA, 98.1% for pathologist 1, and 97.9% for pathologist 2. Conclusion: Among women aged 50+ years with node-negative, ER+PR+HER2- breast cancer in our setting, approximately 5-10% of patients with Ki67 scores of ≤ 5% or <10% on core biopsies would have high RS (≥26) on surgical specimens and over 48% of cases with Ki67 scores ≥30 would have low RS (<26), which may be insufficiently accurate for avoiding the 21-gene or other multi-gene assays. Future studies are needed to examine whether restricting Ki67 testing to ER+HER2- patients with PR >10% would improve its clinical validity.
Citation Format: Veronica C. Shim, Robin J Baker, Wen Jing, Sally S Agersborg, Thomas K Lee, Wamda Goreal, Ninah Achacoso, Catherine Lee, Marvella Villasenor, Amy Lin, Malathy Kapali, Laurel A Habel. Ki67 assessment based on international Ki67 working group recommendations and correlation with 21-gene assay results in a large integrated health care system: We might not be there yet [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-10.
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Affiliation(s)
| | | | - Wen Jing
- The Permanente Medicine, San Francisco, CA
| | | | | | | | - Ninah Achacoso
- The Permanente Medical Group, Division of Research, Oakland, CA
| | - Catherine Lee
- The Permanente Medical Group, Division of Research, Oakland, CA
| | | | - Amy Lin
- The Permanente Medical Group, San Francisco, CA
| | | | - Laurel A Habel
- The Permanente Medical Group, Division of Research, Oakland, CA
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21
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Pan M, Jiang C, Tse P, Achacoso N, Alexeeff S, Solorzano AV, Chung E, Hu W, Truong TG, Arora A, Sundaresan T, Suga JM, Thomas S, Habel LA. TP53 Gain-of-Function and Non-Gain-of-Function Mutations Are Differentially Associated With Sidedness-Dependent Prognosis in Metastatic Colorectal Cancer. J Clin Oncol 2022; 40:171-179. [PMID: 34843402 PMCID: PMC8718185 DOI: 10.1200/jco.21.02014] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
PURPOSE To examine the association of gain-of-function (GOF) and non-gain-of-function (non-GOF) TP53 mutations with prognosis of metastatic right-sided (RCC) versus left-sided colorectal cancer (LCC). METHODS This cohort study included patients with metastatic colorectal cancer (CRC) who had next-generation sequencing performed from November 2017 to January 2021. We defined R175H, R248W, R248Q, R249S, R273H, R273L, and R282W as GOF and all other mutp53 as non-GOF. We used Cox regression modeling to examine the association between GOF and non-GOF mutp53 and overall survival (OS), adjusting for age, sex, ethnicity, performance status, Charlson comorbidity index and receipt of chemotherapy. RESULTS Of total 1,043 patients, 735 had tumors with mutp53 and 308 had wild-type p53 (wtp53). GOF was associated with worse OS than non-GOF mutp53 only in LCC (hazard ratio [HR] = 1.66 [95% CI, 1.20 to 2.29]), but not in RCC (HR = 0.79 [95% CI, 0.49 to 1.26]). Importantly, RCC was associated with worse OS than LCC only in the subset of patients whose CRC carried non-GOF (HR = 1.76 [95% CI, 1.30 to 2.39]), but not GOF mutp53 (HR = 0.92 [95% CI, 0.55 to 1.53]) or wtp53 (HR = 0.88 [95% CI, 0.60 to 1.28]). These associations were largely unchanged after also adjusting for RAS, BRAF, and PIK3CA mutations, and microsatellite instability-high. CONCLUSION Poorer survival of patients with metastatic RCC versus LCC appeared to be restricted to the subset with non-GOF mutp53, whereas GOF versus non-GOF mutp53 was associated with poorer survival only among patients with LCC. This approach of collectively classifying mutp53 into GOF and non-GOF provides new insight for prognostic stratification and for understanding the mechanism of sidedness-dependent prognosis. If confirmed, future CRC clinical trials may benefit from incorporating this approach.
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Affiliation(s)
- Minggui Pan
- Department of Oncology and Hematology, Kaiser Permanente, Santa Clara, CA,Division of Research, Kaiser Permanente, Oakland, CA,Minggui Pan, MD, PhD, Division of Research and Department of Oncology and Hematology, Kaiser Permanente, 710 Lawrence Expressway, Santa Clara, CA 95051; e-mail:
| | - Chen Jiang
- Division of Research, Kaiser Permanente, Oakland, CA
| | - Pam Tse
- Division of Research, Kaiser Permanente, Oakland, CA
| | | | | | | | - Elaine Chung
- Division of Research, Kaiser Permanente, Oakland, CA
| | - Wenwei Hu
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers, State University of New Jersey, New Brunswick, NJ
| | - Thach-Giao Truong
- Department of Oncology and Hematology, Kaiser Permanente, Vallejo, CA
| | - Amit Arora
- Department of Oncology and Hematology, Kaiser Permanente, Fremont, CA
| | - Tilak Sundaresan
- Department of Oncology and Hematology, Kaiser Permanente, San Francisco, CA
| | | | - Sachdev Thomas
- Department of Oncology and Hematology, Kaiser Permanente, Vallejo, CA
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22
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Tang A, Neeman E, Vuong B, Arasu VA, Liu R, Kuehner GE, Savitz AC, Lyon LL, Anshu P, Seaward SA, Patel MD, Habel LA, Kushi LH, Mentakis M, Thomas ES, Kolevska T, Chang SB. Care in the time of COVID-19: impact on the diagnosis and treatment of breast cancer in a large, integrated health care system. Breast Cancer Res Treat 2022; 191:665-675. [PMID: 34988767 PMCID: PMC8731186 DOI: 10.1007/s10549-021-06468-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 11/28/2021] [Indexed: 12/19/2022]
Abstract
PURPOSES To delineate operational changes in Kaiser Permanente Northern California breast care and evaluate the impact of these changes during the initial COVID-19 Shelter-in-Place period (SiP, 3/17/20-5/17/20). METHODS By extracting data from institutional databases and reviewing electronic medical charts, we compared clinical and treatment characteristics of breast cancer patients diagnosed 3/17/20-5/17/20 to those diagnosed 3/17/19-5/17/2019. Outcomes included time from biopsy to consultation and treatment. Comparisons were made using Chi-square or Wilcoxon rank-sum tests. RESULTS Fewer new breast cancers were diagnosed in 2020 during the SiP period than during a similar period in 2019 (n = 247 vs n = 703). A higher percentage presented with symptomatic disease in 2020 than 2019 (78% vs 37%, p < 0.001). Higher percentages of 2020 patients presented with grade 3 (37% vs 25%, p = 0.004) and triple-negative tumors (16% vs 10%, p = 0.04). A smaller percentage underwent surgery first in 2020 (71% vs 83%, p < 0.001) and a larger percentage had neoadjuvant chemotherapy (16% vs 11%, p < 0.001). Telehealth utilization increased from 0.8% in 2019 to 70.0% in 2020. Times to surgery and neoadjuvant chemotherapy were shorter in 2020 than 2019 (19 vs 26 days, p < 0.001, and 23 vs 28 days, p = 0.03, respectively). CONCLUSIONS During SiP, fewer breast cancers were diagnosed than during a similar period in 2019, and a higher proportion presented with symptomatic disease. Early-stage breast cancer diagnoses decreased, while metastatic cancer diagnoses remained similar. Telehealth increased significantly, and times to treatment were shorter in 2020 than 2019. Our system continued to provide timely breast cancer treatment despite significant pandemic-driven disruption.
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Affiliation(s)
- Annie Tang
- Department of Surgery, University of California San Francisco, San Francisco, USA
| | - Elad Neeman
- Department of Medical Oncology, San Francisco Medical Center, Kaiser Permanente, San Francisco, USA
| | - Brooke Vuong
- Department of Surgery, South Sacramento Medical Center, Kaiser Permanente, Sacramento, USA
| | - Vignesh A Arasu
- Department of Radiology, Kaiser Permanente Vallejo Medical Center, Vallejo, USA
| | - Raymond Liu
- Department of Medical Oncology, San Francisco Medical Center, Kaiser Permanente, San Francisco, USA.,Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Gillian E Kuehner
- Department of Surgery, Kaiser Permanente Vallejo Medical Center, Vallejo, USA
| | - Alison C Savitz
- Department of Surgery, Kaiser Permanente Walnut Creek Medical Center, Walnut Creek, USA
| | - Liisa L Lyon
- Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Prachi Anshu
- Department of Surgery, Fremont Medical Center, Kaiser Permanente, Fremont Medical Center - 39400 Paseo Padre Pkwy, Fremont, CA, 94538, USA
| | - Samantha A Seaward
- Department of Radiation Oncology, Kaiser Permanente Oakland Medical Center, Oakland, USA
| | - Milan D Patel
- Department of Radiation Oncology, Kaiser Permanente South San Francisco Medical Center, South San Francisco, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Margaret Mentakis
- Department of Surgery, South Sacramento Medical Center, Kaiser Permanente, Sacramento, USA
| | - Eva S Thomas
- Department of Medical Oncology, Kaiser Permanente Oakland Medical Center, Oakland, USA
| | - Tatjana Kolevska
- Department of Medical Oncology, Kaiser Permanente Vallejo Medical Center, Vallejo, USA
| | - Sharon B Chang
- Department of Surgery, Fremont Medical Center, Kaiser Permanente, Fremont Medical Center - 39400 Paseo Padre Pkwy, Fremont, CA, 94538, USA.
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23
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Chen H, Fan S, Stone J, Thompson DJ, Douglas J, Li S, Scott C, Bolla MK, Wang Q, Dennis J, Michailidou K, Li C, Peters U, Hopper JL, Southey MC, Nguyen-Dumont T, Nguyen TL, Fasching PA, Behrens A, Cadby G, Murphy RA, Aronson K, Howell A, Astley S, Couch F, Olson J, Milne RL, Giles GG, Haiman CA, Maskarinec G, Winham S, John EM, Kurian A, Eliassen H, Andrulis I, Evans DG, Newman WG, Hall P, Czene K, Swerdlow A, Jones M, Pollan M, Fernandez-Navarro P, McConnell DS, Kristensen VN, Rothstein JH, Wang P, Habel LA, Sieh W, Dunning AM, Pharoah PDP, Easton DF, Gierach GL, Tamimi RM, Vachon CM, Lindström S. Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci. Breast Cancer Res 2022; 24:27. [PMID: 35414113 PMCID: PMC9006574 DOI: 10.1186/s13058-022-01524-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 04/02/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.
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Affiliation(s)
- Hongjie Chen
- grid.34477.330000000122986657Department of Epidemiology, School of Public Health, University of Washington, 3980 15th Ave NE, Box 351619, Seattle, WA 98195 USA
| | - Shaoqi Fan
- grid.48336.3a0000 0004 1936 8075Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Jennifer Stone
- grid.1012.20000 0004 1936 7910School of Population and Global Health, University of Western Australia, Crawley, Australia
| | - Deborah J. Thompson
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Julie Douglas
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI USA ,grid.60094.3b0000 0001 2270 6467Department of Mathematics and Statistics, Skidmore College, Saratoga Springs, NY USA
| | - Shuai Li
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK ,grid.1008.90000 0001 2179 088XCentre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia ,grid.1002.30000 0004 1936 7857Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC Australia
| | - Christopher Scott
- grid.66875.3a0000 0004 0459 167XDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Manjeet K. Bolla
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Qin Wang
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- grid.417705.00000 0004 0609 0940Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus ,grid.417705.00000 0004 0609 0940Cyprus School of Molecular Medicine, Nicosia, Cyprus
| | - Christopher Li
- grid.34477.330000000122986657Department of Epidemiology, School of Public Health, University of Washington, 3980 15th Ave NE, Box 351619, Seattle, WA 98195 USA ,grid.270240.30000 0001 2180 1622Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA USA
| | - Ulrike Peters
- grid.34477.330000000122986657Department of Epidemiology, School of Public Health, University of Washington, 3980 15th Ave NE, Box 351619, Seattle, WA 98195 USA ,grid.270240.30000 0001 2180 1622Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA USA
| | - John L. Hopper
- grid.1008.90000 0001 2179 088XCentre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia
| | - Melissa C. Southey
- grid.1002.30000 0004 1936 7857Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC Australia
| | - Tu Nguyen-Dumont
- grid.1002.30000 0004 1936 7857Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC Australia
| | - Tuong L. Nguyen
- grid.1008.90000 0001 2179 088XCentre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia
| | - Peter A. Fasching
- grid.411668.c0000 0000 9935 6525Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Annika Behrens
- grid.411668.c0000 0000 9935 6525Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Gemma Cadby
- grid.1012.20000 0004 1936 7910School of Population and Global Health, University of Western Australia, Crawley, Australia
| | - Rachel A. Murphy
- grid.17091.3e0000 0001 2288 9830Cancer Control Research, BC Cancer and School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - Kristan Aronson
- grid.410356.50000 0004 1936 8331Public Health Sciences, Queen’s University, Kingston, Canada
| | - Anthony Howell
- grid.5379.80000000121662407Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Susan Astley
- grid.5379.80000000121662407Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, UK
| | - Fergus Couch
- grid.66875.3a0000 0004 0459 167XDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Janet Olson
- grid.66875.3a0000 0004 0459 167XDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Roger L. Milne
- grid.1008.90000 0001 2179 088XCentre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia ,grid.1002.30000 0004 1936 7857Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC Australia ,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC Australia
| | - Graham G. Giles
- grid.1008.90000 0001 2179 088XCentre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia ,grid.5379.80000000121662407Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, UK ,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC Australia
| | - Christopher A. Haiman
- grid.42505.360000 0001 2156 6853Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Gertraud Maskarinec
- grid.410445.00000 0001 2188 0957Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI USA
| | - Stacey Winham
- grid.66875.3a0000 0004 0459 167XDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Esther M. John
- grid.168010.e0000000419368956Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA USA ,grid.168010.e0000000419368956Department of Medicine (Oncology), Stanford University School of Medicine, Stanford, CA USA ,grid.168010.e0000000419368956Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA USA
| | - Allison Kurian
- grid.168010.e0000000419368956Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA USA ,grid.168010.e0000000419368956Department of Medicine (Oncology), Stanford University School of Medicine, Stanford, CA USA ,grid.168010.e0000000419368956Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA USA
| | - Heather Eliassen
- grid.38142.3c000000041936754XDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA ,grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA USA
| | - Irene Andrulis
- grid.250674.20000 0004 0626 6184Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Canada ,grid.17063.330000 0001 2157 2938Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - D. Gareth Evans
- grid.5379.80000000121662407Division of Evolution and Genomic Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK ,grid.462482.e0000 0004 0417 0074Genomic Medicine, St Mary’s Hospital, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK ,grid.498924.a0000 0004 0430 9101NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - William G. Newman
- grid.5379.80000000121662407Division of Evolution and Genomic Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Per Hall
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anthony Swerdlow
- grid.18886.3fDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Michael Jones
- grid.18886.3fDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Marina Pollan
- grid.413448.e0000 0000 9314 1427Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
| | - Pablo Fernandez-Navarro
- grid.413448.e0000 0000 9314 1427Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
| | - Daniel S. McConnell
- grid.214458.e0000000086837370Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI USA
| | - Vessela N. Kristensen
- grid.55325.340000 0004 0389 8485Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | | | - Joseph H. Rothstein
- grid.59734.3c0000 0001 0670 2351Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Pei Wang
- grid.59734.3c0000 0001 0670 2351Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Laurel A. Habel
- grid.280062.e0000 0000 9957 7758Division of Research, Kaiser Permanente Northern California, Oakland, CA USA
| | - Weiva Sieh
- grid.59734.3c0000 0001 0670 2351Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Alison M. Dunning
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul D. P. Pharoah
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Douglas F. Easton
- grid.5335.00000000121885934Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Gretchen L. Gierach
- grid.48336.3a0000 0004 1936 8075Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD USA
| | - Rulla M. Tamimi
- grid.5386.8000000041936877XDivision of Epidemiology, Population Health Science, Weill Cornell Medicine, New York, NY USA
| | - Celine M. Vachon
- grid.66875.3a0000 0004 0459 167XDepartment of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Sara Lindström
- grid.34477.330000000122986657Department of Epidemiology, School of Public Health, University of Washington, 3980 15th Ave NE, Box 351619, Seattle, WA 98195 USA ,grid.270240.30000 0001 2180 1622Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA USA
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Emerson MA, Achacoso NS, Benefield HC, Troester MA, Habel LA. Initiation and adherence to adjuvant endocrine therapy among urban, insured American Indian/Alaska Native breast cancer survivors. Cancer 2021; 127:1847-1856. [PMID: 33620753 PMCID: PMC8191495 DOI: 10.1002/cncr.33423] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 12/16/2020] [Accepted: 12/20/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND It has been shown that racial/ethnic disparities exist with regard to initiation of and adherence to adjuvant endocrine therapy (AET). However, the relationship among American Indian/Alaska Native (AIAN) individuals is poorly understood, particularly among those who reside in urban areas. We evaluated whether AET initiation and adherence were lower among AIAN individuals than those of other races/ethnicities who were enrolled in the Kaiser Permanente of Northern California (KPNC) health system. METHODS We identified 23,680 patients from the period 1997 to 2014 who were eligible for AET (first primary, stage I-III, hormone receptor-positive breast cancer) and used KPNC pharmacy records to identify AET prescriptions and refill dates. We assessed AET initiation (≥1 filled prescription within 1 year of diagnosis) and AET adherence (proportion of days covered ≥80%) every year up to 5 years after AET initiation. RESULTS At the end of the 5-year follow-up period, 83% of patients were AET initiators, and 58% were AET adherent. Compared with other races/ethnicities, AIAN women had the second-lowest rate of AET initiation (non-Hispanic Black [NHB], 78.0%; AIAN, 78.6%; Hispanic, 83.0%; non-Hispanic White [NHW], 82.5%; Asian/Pacific Islander [API], 84.7%), the lowest rate of AET adherence after 1 year and 5 years of follow-up (70.3% and 50.8%, respectively), and the greatest annual decline in AET adherence during the 4- to 5-year period of follow-up (a 13.8% decrease in AET adherence [from 64.6% to 50.8%]) after initiation of AET. In adjusted multivariable models, AIAN, Hispanic, and NHB women were less likely than NHW women to be AET adherent. At the end of the 5-year period, total underutilization (combining initiation and adherence) in AET-eligible patients was greatest among AIAN (70.6%) patients, followed by NHB (69.6%), Hispanic (63.2%), NHW (58.7%), and API (52.3%) patients, underscoring the AET treatment gap. CONCLUSION Our results suggest that AET initiation and adherence are particularly low for insured AIAN women.
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Affiliation(s)
- Marc A. Emerson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Ninah S. Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Halei C. Benefield
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Melissa A. Troester
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Laurel A. Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
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25
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Habel LA, Achacoso N, Fireman B, Pedersen SA, Pottegård A. Hydrochlorothiazide and risk of melanoma subtypes. Pharmacoepidemiol Drug Saf 2021; 30:1396-1401. [PMID: 33960576 DOI: 10.1002/pds.5266] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 04/30/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Hydrochlorothiazide (HCTZ), a common diuretic known to be photosensitizing and previously associated with non-melanoma skin cancer, was recently reported to be associated with two melanoma subtypes, nodular and lentigo, among residents of Denmark. Our goal was to examine whether Danish findings could be replicated in a US cohort, using a similar study design and analysis. METHODS Among non-Hispanic White enrollees of Kaiser Permanente Northern California, we conducted an analysis of 9176 melanoma cases and 264 781 controls, matched on age, sex and time in health plan. We examined use of HCTZ prior to cancer diagnosis (cases) or comparable date for controls, categorized as never use, ever use and high use (≥50 000 mg). Electronic health records provided data on prescriptions, cancer diagnoses, and covariates. Conditional logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusted for education, income and number of dermatology, internal medicine and urgent care visits. RESULTS We observed a small increase in risk of melanoma, all types combined, associated with high use (≥50 000 mg) of HCTZ (OR = 1.11, 95% CI 1.00-1.23) and no evidence of a dose-response. Risk was more elevated for lentigo subtype (OR = 1.57, 95% CI 1.01-2.42). The somewhat elevated risk for nodular subtype was not statistically significant (OR = 1.22, 95% CI 0.78-1.90). There was very little association of high use with the superficial spreading subtype (OR = 1.05, 95% CI 0.80-1.37). CONCLUSIONS Our findings support a recent report of an association between high use of HCTZ and increased risk of the lentigo subtype of melanoma.
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Affiliation(s)
- Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Bruce Fireman
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Sidsel Arnspang Pedersen
- Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Anton Pottegård
- Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
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Pan M, Jiang C, Tse P, Solorzano-Pinto AV, Chung E, Truong TG, Arora A, Sundaresan TK, Suga JMM, Habel LA, Thomas SP. Association of TP53 mutation with decreased prevalence of MSI-high, RAS and PI3KCA mutations in metastatic colorectal cancer. J Clin Oncol 2021. [DOI: 10.1200/jco.2021.39.15_suppl.e15578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e15578 Background: TP53 tumor suppressor gene is mutated in approximately 50% of colorectal cancer (CRC). How TP53 mutations are associated with the prevalence of the other common genomic alterations such as RAS (KRAS/NRAS), BRAF, PI3KCA, as well as microsatellite stability (MSI) is not clear. Methods: We investigated the impact of TP53 mutations on other common genomic alterations and survival in patients with metastatic CRC using the NGS data within Kaiser Permanente Northern California (KPNC). Results: From November 2017 to January 2021, genomic profiling was performed on 1056 patients with metastatic CRC, of whom 740 patients harbored a TP53 mutation (TP53mut) and 316 patients had wild-type TP53 (TP53wt). We found that median overall survival (OS) was similar between the TP53wt and TP53mut patients (50.1 vs 47.5 months, p = 0.9), however, the percent with a Ras mutation was significantly higher in patients with TP53wt compared to TP53mut (63.2 vs 45.2%, p = 0.0001). Interestingly, the percent with MSI-high was also significantly higher in TP53wt than TP53mut patients (11.1 vs 1.4%, p = 0.0001), however, the response rate of the MSI-high patients to immune checkpoint inhibitor (ICI) was similar (40 vs 37.5%). In addition, a significantly higher percent of patients with TP53wt had PI3KCA mutations and a significantly lower percent had c-Myc amplifications compared to patients with TP53mut (PI3KCA, 32 vs 10.7%, p = 0.0001; c-Myc, 1.26 vs 4.6%, p = 0.008). There was no significant difference in the percent of BRAF mutations between the two patient populations (6.2 vs 9.8%). A significantly higher percent of patients with TP53wt and a PI3KCA mutation had a Ras mutation compared to patients with TP53mut and a PI3KCA mutation (81.2 vs 57%, p = 0.0004). However, TP53 mutation status was not significantly associated with the OS of patients with either a Ras, or BRAF, or PI3KCA mutation, or combination of Ras and PI3KCA mutations. Conclusions: TP53 mutation is associated with decreased prevalence of Ras, PI3KCA mutation and MSI-high in patients with metastatic CRC, however, without impacting the OS or response rate to ICI.
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Affiliation(s)
- Minggui Pan
- Kaiser Permanente, Dept of Medical Oncology, Santa Clara, CA
| | - Chen Jiang
- Kaiser Permanente, Division of Research, Oakland, CA
| | - Pamela Tse
- Kaiser Permanente, Division of Research, Oakland, CA
| | | | - Elaine Chung
- Kaiser Permanente, Division of Research, Oakland, CA
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Pan M, Jiang C, Tse P, Chung E, Solorzano A, Hu W, Truong TG, Arora A, Sundaresan TK, Suga JMM, Habel LA, Thomas SP. Differential impact of different TP53 gain-of-function mutations on overall survival of patients with metastatic colorectal cancer: Results from a large integrated healthcare system. J Clin Oncol 2021. [DOI: 10.1200/jco.2021.39.15_suppl.3585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
3585 Background: TP53 mutation is present in approximately 50% of metastatic colorectal cancer (CRC). The spectrum of the TP53 mutations is extremely broad including approximately 80% missense mutations. Several missense mutations have been found to possess gain-of-function (GOF) properties in cell line and animal studies, however, confirmation of the concept of GOF in human malignancies is still lacking. Methods: We investigated the impact of TP53 GOF mutations in patients with metastatic CRC using the NGS data within Kaiser Permanente Northern California (KPNC), a large integrated healthcare system. Results: From November 2017 to January 2021, genomic profiling by StrataNGS was performed on 8658 patients, with 1056 patients being metastatic CRC, among whom 740 patients harbored a TP53 mutation (TP53mut) and 316 patients had wild-type TP53 (TP53wt). Ras (KRAS and NRAS) and BRAF mutation appropriately discriminated the overall survival (OS) of patient populations with either TP53wt or TP53mut, confirming the validity of our dataset. We identified seven GOF TP53 mutations (R175H, R248W, R248Q, R249S, R273H, R273L, R282W) in these CRC patients. We show that different GOF mutation differentially impacts the OS. Patients whose CRC harbored TP53mut R248W, R249S, and R282W (poor prognostic TP53mut, N = 47) had significantly worse OS versus patients whose CRC harbored TP53mut R248Q, R175H, R273H and R273L (N = 160, median OS 29.4 vs 44.2 months, HR 0.47, p = 0.007). The OS of the poor prognostic TP53mut patients was also significantly inferior compared to patients whose CRC harbored all other TP53 mutations (N = 1099, median OS 50.1 months, HR 0.55, p = 0.01) or TP53wt (N = 316, median OS 47,5 months, HR 0.54, p = 0.01). The demographics and the percent of Ras, BRAF, and PI3KCA mutations were similar except that the patients with the poor prognostic TP53mut had significantly higher percent of Ras mutation compared to the rest of the GOF TP53mut patients (p = 0.035). When compared to R248Q alone, R248W confers worse OS (median OS 36.3 vs 63.2 months, p = 0.05). Conclusions: Our data suggest that different TP53 GOF mutations are associated with very different clinical outcomes. Additional studies identifying specific TP53 GOF mutations that impact outcomes may provide further insight for drug development and clinical trial design.
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Affiliation(s)
- Minggui Pan
- Kaiser Permanente, Dept of Medical Oncology, Santa Clara, CA
| | - Chen Jiang
- Kaiser Permanente, Division of Research, Oakland, CA
| | - Pamela Tse
- Kaiser Permanente, Division of Research, Oakland, CA
| | - Elaine Chung
- Kaiser Permanente, Division of Research, Oakland, CA
| | | | - Wenwei Hu
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ
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Solomon DH, Ruppert K, Habel LA, Finkelstein JS, Lian P, Joffe H, Kravitz HM. Prescription medications for sleep disturbances among midlife women during 2 years of follow-up: a SWAN retrospective cohort study. BMJ Open 2021; 11:e045074. [PMID: 33975865 PMCID: PMC8127972 DOI: 10.1136/bmjopen-2020-045074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVE To examine the effects of prescription sleep medications on patient-reported sleep disturbances. DESIGN Retrospective cohort. SETTING Longitudinal cohort of community-dwelling women in the USA. PARTICIPANTS Racially and ethnically diverse middle-aged women who reported a sleep disturbance. INTERVENTIONS New users of prescription sleep medications propensity score matched to women not starting sleep medications. MAIN OUTCOMES AND MEASURES Self-reported sleep disturbance during the previous 2 weeks-difficulty initiating sleep, waking frequently and early morning awakening-using a 5-point Likert scale, ranging from no difficulty on any night (rating 1) to difficulty on 5 or more nights a week (rating 5). Sleep disturbances were compared at 1 year (primary outcome) and 2 years of follow-up. RESULTS 238 women who started sleep medications were matched with 447 non-users. Participants had a mean age of 49.5 years and approximately half were white. At baseline, sleep disturbance ratings were similar: medication users had a mean score for difficulty initiating sleep of 2.7 (95% CI 2.5 to 2.9), waking frequently 3.8 (95% CI 3.6 to 3.9) and early morning awakening 2.8 (95% CI 2.6 to 3.0); non-users ratings were 2.6 (95% CI 2.5 to 2.7), 3.7 (95% CI 3.6 to 3.9) and 2.7 (95% CI 2.6 to 2.8), respectively. After 1 year, ratings for medication users were 2.6 (95% CI 2.4 to 2.8) for initiating sleep, 3.6 (95% CI 3.4 to 3.8) for waking frequently and 2.8 (95% CI 2.6 to 3.0) for early morning awakening; for non-users, the mean ratings were 2.3 (95% CI 2.2 to 2.5), 3.5 (95% CI 3.3 to 3.6) and 2.5 (95% CI 2.3 to 2.6), respectively. None of the 1 year changes were statistically significant nor were they different between medication users and non-users. Two-year follow-up results were consistent, without statistically significant reductions in sleep disturbance in medication users compared with non-users. CONCLUSIONS These analyses suggest that women who initiated sleep medications rated their sleep disturbances similar after 1 and 2 years. The effectiveness of long-term sleep medication use should be re-examined.
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Affiliation(s)
- Daniel H Solomon
- Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Kristine Ruppert
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Joel S Finkelstein
- Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Pam Lian
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Hadine Joffe
- Psychiatry, Harvard Univerisity, Boston, Massachusetts, USA
| | - Howard M Kravitz
- Department of Psychiatry, Rush Medical College of Rush University, Chicago, Illinois, USA
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29
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Emami NC, Cavazos TB, Rashkin SR, Cario CL, Graff RE, Tai CG, Mefford JA, Kachuri L, Wan E, Wong S, Aaronson D, Presti J, Habel LA, Shan J, Ranatunga DK, Chao CR, Ghai NR, Jorgenson E, Sakoda LC, Kvale MN, Kwok PY, Schaefer C, Risch N, Hoffmann TJ, Van Den Eeden SK, Witte JS. A Large-Scale Association Study Detects Novel Rare Variants, Risk Genes, Functional Elements, and Polygenic Architecture of Prostate Cancer Susceptibility. Cancer Res 2021; 81:1695-1703. [PMID: 33293427 PMCID: PMC8137514 DOI: 10.1158/0008-5472.can-20-2635] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 10/27/2020] [Accepted: 12/02/2020] [Indexed: 11/16/2022]
Abstract
To identify rare variants associated with prostate cancer susceptibility and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we conducted an integrated study of prostate cancer genetic etiology in two cohorts using custom genotyping microarrays, large imputation reference panels, and functional annotation approaches. Specifically, 11,984 men (6,196 prostate cancer cases and 5,788 controls) of European ancestry from Northern California Kaiser Permanente were genotyped and meta-analyzed with 196,269 men of European ancestry (7,917 prostate cancer cases and 188,352 controls) from the UK Biobank. Three novel loci, including two rare variants (European ancestry minor allele frequency < 0.01, at 3p21.31 and 8p12), were significant genome wide in a meta-analysis. Gene-based rare variant tests implicated a known prostate cancer gene (HOXB13), as well as a novel candidate gene (ILDR1), which encodes a receptor highly expressed in prostate tissue and is related to the B7/CD28 family of T-cell immune checkpoint markers. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. In addition, a polygenic risk score (PRS) of 188 prostate cancer variants was strongly associated with risk (90th vs. 40th-60th percentile OR = 2.62, P = 2.55 × 10-191). Many of the 188 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a 6-fold difference in log-probability of androgen receptor binding at the variant rs2680708 (17q22). Rare variant and PRS associations, with concomitant functional interpretation of risk mechanisms, can help clarify the full genetic architecture of prostate cancer and other complex traits. SIGNIFICANCE: This study maps the biological relationships between diverse risk factors for prostate cancer, integrating different functional datasets to interpret and model genome-wide data from over 200,000 men with and without prostate cancer.See related commentary by Lachance, p. 1637.
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Affiliation(s)
- Nima C Emami
- Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
| | - Taylor B Cavazos
- Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California
| | - Sara R Rashkin
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
| | - Clinton L Cario
- Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
| | - Caroline G Tai
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
| | - Joel A Mefford
- Program in Pharmaceutical Sciences and Pharmacogenomics, University of California San Francisco, San Francisco, California
| | - Linda Kachuri
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
| | - Eunice Wan
- Institute for Human Genetics, University of California San Francisco, San Francisco, California
| | - Simon Wong
- Institute for Human Genetics, University of California San Francisco, San Francisco, California
| | - David Aaronson
- Department of Urology, Kaiser Oakland Medical Center, Oakland, California
| | - Joseph Presti
- Department of Urology, Kaiser Oakland Medical Center, Oakland, California
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Jun Shan
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Dilrini K Ranatunga
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Chun R Chao
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California
| | - Nirupa R Ghai
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Mark N Kvale
- Institute for Human Genetics, University of California San Francisco, San Francisco, California
| | - Pui-Yan Kwok
- Program in Pharmaceutical Sciences and Pharmacogenomics, University of California San Francisco, San Francisco, California
- Institute for Human Genetics, University of California San Francisco, San Francisco, California
| | - Catherine Schaefer
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Neil Risch
- Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
- Program in Pharmaceutical Sciences and Pharmacogenomics, University of California San Francisco, San Francisco, California
- Institute for Human Genetics, University of California San Francisco, San Francisco, California
- Division of Research, Kaiser Permanente Northern California, Oakland, California
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California
| | - Thomas J Hoffmann
- Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
- Institute for Human Genetics, University of California San Francisco, San Francisco, California
| | - Stephen K Van Den Eeden
- Division of Research, Kaiser Permanente Northern California, Oakland, California
- Department of Urology, University of California San Francisco, San Francisco, California
| | - John S Witte
- Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California.
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
- Program in Pharmaceutical Sciences and Pharmacogenomics, University of California San Francisco, San Francisco, California
- Institute for Human Genetics, University of California San Francisco, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California
- Department of Urology, University of California San Francisco, San Francisco, California
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30
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Graff RE, Cavazos TB, Thai KK, Kachuri L, Rashkin SR, Hoffman JD, Alexeeff SE, Blatchins M, Meyers TJ, Leong L, Tai CG, Emami NC, Corley DA, Kushi LH, Ziv E, Van Den Eeden SK, Jorgenson E, Hoffmann TJ, Habel LA, Witte JS, Sakoda LC. Cross-cancer evaluation of polygenic risk scores for 16 cancer types in two large cohorts. Nat Commun 2021; 12:970. [PMID: 33579919 PMCID: PMC7880989 DOI: 10.1038/s41467-021-21288-z] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 01/19/2021] [Indexed: 02/07/2023] Open
Abstract
Even distinct cancer types share biological hallmarks. Here, we investigate polygenic risk score (PRS)-specific pleiotropy across 16 cancers in European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and UK Biobank (48,969 cases, 359,802 controls). Within cohorts, each PRS is evaluated in multivariable logistic regression models against all other cancer types. Results are then meta-analyzed across cohorts. Ten positive and one inverse cross-cancer associations are found after multiple testing correction. Two pairs show bidirectional associations; the melanoma PRS is positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS is positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS is inversely associated with lung cancer. Overall, we validate known, and uncover previously unreported, patterns of pleiotropy that have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies.
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Affiliation(s)
- Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.,Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.,Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Taylor B Cavazos
- Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, CA, USA
| | - Khanh K Thai
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Linda Kachuri
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Sara R Rashkin
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Joshua D Hoffman
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Maruta Blatchins
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Travis J Meyers
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Lancelote Leong
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Caroline G Tai
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Nima C Emami
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.,Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, CA, USA
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Elad Ziv
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA.,Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.,Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Stephen K Van Den Eeden
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.,Department of Urology, University of California San Francisco, San Francisco, CA, USA
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Thomas J Hoffmann
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.,Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.,Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - John S Witte
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA. .,Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA. .,Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA. .,Department of Urology, University of California San Francisco, San Francisco, CA, USA.
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA. .,Department of Health System Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA.
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31
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Emerson MA, Achacoso N, Benefield HC, Troester MA, Habel LA. Abstract PO-114: Initiation and adherence to adjuvant endocrine therapy among urban, insured American Indian/Alaskan Native breast cancer survivors. Cancer Epidemiol Biomarkers Prev 2020. [DOI: 10.1158/1538-7755.disp20-po-114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
Background: Disparities in adjuvant endocrine therapy (AET) initiation and adherence have been shown by race/ethnicity, however the relationship among American Indian/Alaskan Natives (AIAN) is poorly understood, particularly among the 73% of urban residing AIAN. We evaluated whether AET-initiation and adherence were lower among AIAN than other races/ethnicities enrolled in Kaiser Permanente of Northern California (KPNC) health system. Methods: We identified 23,680 AET- eligible (first primary, stage I-III, hormone receptor-positive breast cancers) patients from 1997 to 2014 and used KPNC’s pharmacy records to identify AET-prescriptions and refill dates. We assessed AET-initiation (≥1 filled prescription within 1-year of diagnosis) and AET-adherence (proportion of days covered [PDC] ≥80%) every year up to 5-years post AET-initiation. Results: At the end of the 5-year period, 83% were AET-initiators and 58% were AET-adherent. Compared to all other races/ethnicities, AIAN women had the second lowest AET-initiation (Black=78.0%, AIAN=78.6%, Hispanic=83.0%, non-Hispanic white [NHW]=82.5%, Asian=84.7%), the lowest AET- adherence by the end of the 1-year and 5-year period (70.3% and 50.8% vs. NHW=76.4% and 58.8%, respectively), and the greatest AET-discontinuation in year period 4 to 5 (13.8% AET-adherence decrease, 64.6% to 50.8%), after AET-initiation. In the multivariable models adjusting for age, socioeconomic and clinical factors, AIAN, Hispanic, and Black women were less likely than NHW women to be AET- adherent although the number of AIAN was small leading to imprecise estimates. At the end of the 5-year period, total underutilization (combining initiation and adherence) in AET-eligible was greatest among AIAN (70.6%), followed by Black (69.6%), Hispanic (63.2%), NHW (58.7%), and Asian (52.3%), underscoring the AET- treatment gap. Conclusion: Our results suggest that AET-initiation and adherence are particularly low for insured AIAN women. Results suggest that interventions are needed, even for urban, insured AIAN women who tend to have greater geographic access and fewer financial issues than their rural counterparts.
Citation Format: Marc A. Emerson, Ninah Achacoso, Halei C. Benefield, Melissa A. Troester, Laurel A. Habel. Initiation and adherence to adjuvant endocrine therapy among urban, insured American Indian/Alaskan Native breast cancer survivors [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-114.
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Affiliation(s)
- Marc A. Emerson
- 1University of North Carolina at Chapel Hill, Chapel Hill, NC,
| | - Ninah Achacoso
- 2Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | | | | | - Laurel A. Habel
- 2Division of Research, Kaiser Permanente Northern California, Oakland, CA
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32
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Sieh W, Rothstein JH, Klein RJ, Alexeeff SE, Sakoda LC, Jorgenson E, McBride RB, Graff RE, McGuire V, Achacoso N, Acton L, Liang RY, Lipson JA, Rubin DL, Yaffe MJ, Easton DF, Schaefer C, Risch N, Whittemore AS, Habel LA. Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk. Nat Commun 2020; 11:5116. [PMID: 33037222 PMCID: PMC7547012 DOI: 10.1038/s41467-020-18883-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 09/17/2020] [Indexed: 11/09/2022] Open
Abstract
Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10-8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.
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Affiliation(s)
- Weiva Sieh
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Joseph H Rothstein
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Russell B McBride
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Valerie McGuire
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Luana Acton
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Rhea Y Liang
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jafi A Lipson
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Daniel L Rubin
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Martin J Yaffe
- Departments of Medical Biophysics and Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and Department of Oncology, University of Cambridge, Cambridge, UK
| | - Catherine Schaefer
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Neil Risch
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Alice S Whittemore
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
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33
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Rashkin SR, Graff RE, Kachuri L, Thai KK, Alexeeff SE, Blatchins MA, Cavazos TB, Corley DA, Emami NC, Hoffman JD, Jorgenson E, Kushi LH, Meyers TJ, Van Den Eeden SK, Ziv E, Habel LA, Hoffmann TJ, Sakoda LC, Witte JS. Pan-cancer study detects genetic risk variants and shared genetic basis in two large cohorts. Nat Commun 2020; 11:4423. [PMID: 32887889 PMCID: PMC7473862 DOI: 10.1038/s41467-020-18246-6] [Citation(s) in RCA: 102] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 08/13/2020] [Indexed: 12/14/2022] Open
Abstract
Deciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. Here, we undertake genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (408,786 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detect 21 genome-wide significant associations independent of previously reported results. Investigations of pleiotropy identify 12 cancer pairs exhibiting either positive or negative genetic correlations; 25 pleiotropic loci; and 100 independent pleiotropic variants, many of which are regulatory elements and/or influence cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.
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Affiliation(s)
- Sara R Rashkin
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.,Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Linda Kachuri
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Khanh K Thai
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Maruta A Blatchins
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Taylor B Cavazos
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.,Program in Biological and Medical Informatics, University of California, San Francisco, San Francisco, CA, USA
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Nima C Emami
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.,Program in Biological and Medical Informatics, University of California, San Francisco, San Francisco, CA, USA
| | - Joshua D Hoffman
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Travis J Meyers
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Stephen K Van Den Eeden
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.,Department of Urology, University of California, San Francisco, San Francisco, CA, USA
| | - Elad Ziv
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.,Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.,Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Thomas J Hoffmann
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.,Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.,Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
| | - John S Witte
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA. .,Department of Urology, University of California, San Francisco, San Francisco, CA, USA. .,Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. .,Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
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34
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Habel LA, Buist DSM. Re: Cancer Outcomes in DCIS Patients Without Locoregional Treatment. J Natl Cancer Inst 2020; 112:214-215. [PMID: 31199466 DOI: 10.1093/jnci/djz118] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 05/29/2019] [Indexed: 11/14/2022] Open
Affiliation(s)
- Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA (LAH)
| | - Diana S M Buist
- Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA (DSMB)
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Suga JM, Thomas SP, Truong TG, Sundaresan TK, Pan M, Kim W, Hoodfar E, Cheng L, Chung E, Tse P, Achacoso N, Jiang C, Goldstein D, Habel LA. Implementing a genomic oncology program in an integrated health care network with large scale genomic Next Generation Sequencing (NGS) testing of advanced cancers in a community setting. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.e19185] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
e19185 Background: The importance of NGS testing to help guide oncologic therapy decisions has grown over time, presenting a unique challenge for community oncologists to properly translate the NGS test results to treatment (Tx) recommendations for patients. Kaiser Permanente Northern California (KPNC) is a large, integrated health care system providing comprehensive primary and specialty care to 4.4 million members, with over 4000 patients (pts) diagnosed with advanced cancer each year. NGS testing at KPNC is performed in a collaboration with Strata Oncology, that provides systematized comprehensive NGS testing (StrataNGS) paired with a portfolio of genomically guided clinical trials. Methods: KPNC has established workflows for upfront empiric review of all NGS results by our KPNC Genomic Oncology Committee (GOC), that includes representatives from medical oncology subspecialists, genetics, pathology, and clinical trials. KPNC GOC reviews all StrataNGS test results in our KPNC network to identify patients that might benefit from either a clinical trial, appropriate on or off-label drug options and/or genetic counseling. In addition, GOC conducts an in-depth case review per request of the treating oncologist. A study nurse pre-screens all pts whose results match to a trial for eligibility. Results: The numbers of pts tested with StrataNGS has increased over time with around 300 pts tested monthly and 4,977 NGS tests performed since Nov 2017. Median age was 65.2 (Range 18.5-96.0). About 42.4% of Pts were non-white. Approximately, 39% of Pts had an actionable mutation including 21.7% eligible for a promising in or out of network trial. 1.6% and 10.9% pts were potentially eligible for off- or on-label approved drugs, respectively. 4.9% were recommended to receive genetic counseling. The 3 most frequently sequenced cancers were: lung, colon and breast. Conclusions: KPNC is providing systematic subspecialty review and management of NGS results for pts in a community setting. Our approach has allowed for greater adoption of routine NGS testing, especially for rare cancer types with less effective standard Tx options available. This model also helps accrual to genomic-based drug trials that have been a challenge for the field. Workflows to streamline automated centralized acquisition of prior Tx history and analysis of response to therapy are in development.
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Affiliation(s)
| | | | | | | | - Minggui Pan
- Kaiser Permanente, Dept of Medical Oncology, Santa Clara, CA
| | - Won Kim
- Kaiser Permanente, Dept of Medical Oncology, San Francisco, CA
| | | | - Lirong Cheng
- Kaiser Permanente, Dept of Pathology, Roseville, CA
| | - Elaine Chung
- Kaiser Permanente, Division of Research, Oakland, CA
| | - Pamela Tse
- Kaiser Permanente, Division of Research, Oakland, CA
| | | | - Chen Jiang
- Kaiser Permanente, Division of Research, Oakland, CA
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Thomas SP, Suga JM, Truong TG, Sundaresan TK, Pan M, Kim W, Jiang C, Hoodfar E, Chung E, Tse P, Achacoso N, Cheng L, Habel LA. The impact of tumor NGS testing on hereditary cancer risk assessment and population management in an integrated community health care system. J Clin Oncol 2020. [DOI: 10.1200/jco.2020.38.15_suppl.1517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
1517 Background: Next-generation sequencing (NGS) for tumor molecular profiling is used in Oncology to identify ‘actionable alterations’ for clinical trials or on/ off-label therapy. Tumor NGS can also reveal potentially heritable germline mutations. The frequency of such incidental germline mutations has been estimated to be 4-15%. The 2015 ASCO Statement supports communication of medically relevant incidental germline findings from somatic mutation profiling to patients (PTS). The impact of tumor NGS testing on hereditary cancer risk assessment programs in the context of a wider population management strategy is unknown. We sought to evaluate this within our Kaiser Permanente Northern California (KPNC) population with ready access to tumor NGS and an ongoing hereditary cancer risk assessment program. Methods: Kaiser Permanente Northern California (KPNC) is part of a large, integrated health care system. NGS at KPNC is performed in collaboration with STRATA Oncology, a precision oncology partnership. All NGS results are reviewed by a multidisciplinary KPNC Genomic Oncology Committee (GOC)which also includes genetic counselors and pathologists. We examined all NGS reports between November 2017 through December 2019 to determine the types of cancers tested, number with a possible germline mutation and number referred for genetic counseling and testing (GCT). Results: 4,825 PTS with advanced cancer underwent STRATA NGS testing. A total of 207 PTS (4.3%) were identified as potential germline mutation carriers, all 207 were recommended for GCT referral. Of these, 92 (45.0%) separately met 2020 NCCN Criteria for Genetic/Familial High-Risk Assessment (2020NG/FA), prior to tumor NGS; 115 (53.6%) did not and 3 (1.4%) had insufficient information. The cancers most frequently meeting NCCN criteria were pancreatic, breast and colon. Of the 92 PTS who met 2020NG/FA, 60 (65%) underwent GCT and 34 (57%) were confirmed to have a germline mutation. Of the 115 PTS that did not meet 2020NG/FA, 47 (41%) underwent GCT and 19 (40%) were confirmed to have a germline mutation. Overall germline mutations were confirmed in 16.5% of patients who did not meet 2020NG/FA and 37% who did. Conclusions: In our community-based integrated healthcare system, systematic review of next-generation sequencing results by an expert GOC led to more robust identification of germline mutation carriers and navigated them to appropriate GCT. Ongoing work will clarify data on cascade testing. We are currently developing automated workflows for GCT.
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Affiliation(s)
| | | | | | | | - Minggui Pan
- Kaiser Permanente, Dept of Medical Oncology, Santa Clara, CA
| | - Won Kim
- University of California San Francisco, San Francisco, CA
| | - Chen Jiang
- Kaiser Permanente, Division of Research, Oakland, CA
| | | | - Elaine Chung
- Kaiser Permanente, Division of Research, Oakland, CA
| | - Pamela Tse
- Kaiser Permanente, Division of Research, Oakland, CA
| | | | - Lirong Cheng
- Kaiser Permanente, Dept of Pathology, Roseville, CA
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McBride RB, Fei K, Rothstein JH, Alexeeff SE, Song X, Sakoda LC, McGuire V, Achacoso N, Acton L, Liang RY, Lipson JA, Yaffe MJ, Rubin DL, Whittemore AS, Habel LA, Sieh W. Alcohol and Tobacco Use in Relation to Mammographic Density in 23,456 Women. Cancer Epidemiol Biomarkers Prev 2020; 29:1039-1048. [PMID: 32066618 PMCID: PMC7196522 DOI: 10.1158/1055-9965.epi-19-0348] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Revised: 07/27/2019] [Accepted: 02/07/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Percent density (PD) is a strong risk factor for breast cancer that is potentially modifiable by lifestyle factors. PD is a composite of the dense (DA) and nondense (NDA) areas of a mammogram, representing predominantly fibroglandular or fatty tissues, respectively. Alcohol and tobacco use have been associated with increased breast cancer risk. However, their effects on mammographic density (MD) phenotypes are poorly understood. METHODS We examined associations of alcohol and tobacco use with PD, DA, and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric. MD was measured using Cumulus. Machine-specific effects were estimated using linear regression, and combined using random effects meta-analysis. RESULTS Alcohol use was positively associated with PD (P trend = 0.01), unassociated with DA (P trend = 0.23), and inversely associated with NDA (P trend = 0.02) adjusting for age, body mass index, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD (P trend = 0.0008), unassociated with DA (P trend = 0.93), and positively associated with NDA (P trend<0.0001). These trends were stronger in normal and overweight women than in obese women. CONCLUSIONS These findings suggest that associations of alcohol and tobacco use with PD result more from their associations with NDA than DA. IMPACT PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health.
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Affiliation(s)
- Russell B McBride
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Kezhen Fei
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Joseph H Rothstein
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Xiaoyu Song
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Valerie McGuire
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Luana Acton
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Rhea Y Liang
- Department of Radiology, Stanford University School of Medicine, Stanford, California
| | - Jafi A Lipson
- Department of Radiology, Stanford University School of Medicine, Stanford, California
| | - Martin J Yaffe
- Departments of Medical Biophysics and Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Daniel L Rubin
- Department of Radiology, Stanford University School of Medicine, Stanford, California
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Alice S Whittemore
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Weiva Sieh
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, New York.
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
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Reding KW, Aragaki AK, Cheng RK, Barac A, Wassertheil-Smoller S, Chubak J, Limacher MC, Hundley WG, D'Agostino R, Vitolins MZ, Brasky TM, Habel LA, Chow EJ, Jackson RD, Chen C, Morgenroth A, Barrington WE, Banegas M, Barnhart M, Chlebowski RT. Cardiovascular Outcomes in Relation to Antihypertensive Medication Use in Women with and Without Cancer: Results from the Women's Health Initiative. Oncologist 2020; 25:712-721. [PMID: 32250503 DOI: 10.1634/theoncologist.2019-0977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 02/14/2020] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Recent clinical trials have evaluated angiotensin-converting enzyme (ACE) inhibitors (ACEis), angiotensin receptor blockers (ARBs), and beta blockers (BBs) in relation to cardiotoxicity in patients with cancer, typically defined by ejection fraction declines. However, these trials have not examined long-term, hard clinical endpoints. Within a prospective study, we examined the risk of heart failure (HF) and coronary heart disease (CHD) events in relation to use of commonly used antihypertensive medications, including ACEis/ARBs, BBs, calcium channel blockers (CCB), and diuretics, comparing women with and without cancer. MATERIALS AND METHODS In a cohort of 56,997 Women's Health Initiative study participants free of cardiovascular disease who received antihypertensive treatment, we used multivariable-adjusted Cox regression models to calculate the hazard ratios (HRs) of developing CHD, HF, and a composite outcome of cardiac events (combining CHD and HF) in relation to use of ACEis/ARBs, CCBs, or diuretics versus BBs, separately in women with and without cancer. RESULTS Whereas there was no difference in risk of cardiac events comparing ACEi/ARB with BB use among cancer-free women (HR = 0.99 [0.88-1.12]), among cancer survivors ACEi/ARB users were at a 2.24-fold risk of total cardiac events (1.18-4.24); p-interaction = .06). When investigated in relation to CHD only, an increased risk was similarly observed in ACEi/ARB versus BB use for cancer survivors (HR = 1.87 [0.88-3.95]) but not in cancer-free women (HR = 0.91 [0.79-1.06]; p-interaction = .04). A similar pattern was also seen in relation to HF but did not reach statistical significance (p-interaction = .23). CONCLUSION These results from this observational study suggest differing risks of cardiac events in relation to antihypertensive medications depending on history of cancer. Although these results require replication before becoming actionable in a clinical setting, they suggest the need for more rigorous examination of the effect of antihypertensive choice on long-term cardiac outcomes in cancer survivors. IMPLICATIONS FOR PRACTICE Although additional research is needed to replicate these findings, these data from a large, nationally representative sample of postmenopausal women indicate that beta blockers are favorable to angiotensin-converting enzyme inhibitors in reducing the risk of cardiac events among cancer survivors. This differs from the patterns observed in a noncancer cohort, which largely mirrors what is found in the randomized clinical trials in the general population.
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Affiliation(s)
- Kerryn W Reding
- University of Washington School of Nursing, Seattle, Washington, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, Washington, USA
| | - Aaron K Aragaki
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, Washington, USA
| | - Richard K Cheng
- University of Washington School of Medicine, Seattle, Washington, USA
| | - Ana Barac
- MedStar Heart and Vascular Institute, MedStar Washington Hospital Center, Washington, DC, USA
| | | | - Jessica Chubak
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Marian C Limacher
- University of Florida College of Medicine, Gainesville, Florida, USA
| | - W Gregory Hundley
- Virginia Commonwealth University Pauley Heart Center, Richmond, Virginia, USA
- Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Ralph D'Agostino
- Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Mara Z Vitolins
- Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | | | - Laurel A Habel
- Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Eric J Chow
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, Washington, USA
- University of Washington School of Medicine, Seattle, Washington, USA
| | - Rebecca D Jackson
- The Ohio State University Department of Medicine, Columbus, Ohio, USA
| | - Chu Chen
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, Washington, USA
| | - April Morgenroth
- Seattle Pacific University College of Nursing, Seattle, Washington, USA
| | - Wendy E Barrington
- University of Washington School of Nursing, Seattle, Washington, USA
- Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, Washington, USA
| | - Matthew Banegas
- Kaiser Permanente Northwest Center for Health Research, Portland, Oregon, USA
| | - Matthew Barnhart
- Stony Brook University School of Medicine, Stony Brook, New York, USA
| | - Rowan T Chlebowski
- Harbor-University of California Los Angeles Medical Center, Los Angeles, California, USA
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McBride RB, Fei K, Rothstein JH, Alexeeff SE, Song X, Sakoda LC, McGuire V, Achacoso N, Acton L, Liang RY, Lipson JA, Yaffe MJ, Rubin DL, Whittemore AS, Habel LA, Sieh W. Abstract P2-08-01: Alcohol and tobacco use in relation to mammographic density in 23,456 women. Cancer Res 2020. [DOI: 10.1158/1538-7445.sabcs19-p2-08-01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: High percent density (PD) is common and is among the strongest risk factors for breast cancer. The prevalence of heterogeneously dense or extremely dense breasts is between 40% to 60% of screening age women, and is estimated to account for up to one third of all breast cancer (BC) diagnoses. PD decreases with age, body mass index (BMI), number of children, and menopause; and increases with age at menarche, age at first birth, and family history of breast cancer. Of particular interest are modifiable exposures believed to alter PD, such as the use of menopausal hormone therapy (MHT), tamoxifen and alcohol that could provide opportunities for women to reduce their BC risk. The dense area (DA) of the breast appears radiopaque on a mammogram and contains greater proportions of collagen, epithelial and stromal cells compared to the nondense area (NDA), which largely consists of fatty tissue. Recent studies have shown that NDA is inversely associated with BC risk, independently of DA, suggesting that normal breast fat may play a protective role. The underlying mechanisms through which mammographic density (MD) phenotypes are associated with BC risk are poorly understood.
Methods: We examined associations of alcohol and tobacco use with PD, DA and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric (GE). MD measurements were obtained using Cumulus an average of 2.9 years after the survey date. Machine-specific effects were estimated using linear regression, adjusted for known biologically plausible correlates of MD, and combined using random effects meta-analysis methods.
Results: Alcohol use was positively associated with PD (ptrend=0.01), unassociated with DA (ptrend=0.23), and inversely associated with NDA (ptrend=0.02) in models adjusted for age, BMI, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD (ptrend=0.0008), unassociated with DA (ptrend=0.93), and positively associated with NDA (ptrend<0.0001). These trends were stronger in normal and overweight women than in obese women.
Conclusions: This study provides the strongest evidence to date that association of alcohol and tobacco use with PD result from their associations with NDA rather than DA.
Impact: Alcohol consumption, and less consistently tobacco use, have been shown to increase risk of breast cancer. These findings indicate that PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health.
Citation Format: Russell B McBride, Kezhen Fei, Joseph H Rothstein, Stacey E Alexeeff, Xiaoyu Song, Lori C Sakoda, Valerie McGuire, Ninah Achacoso, Luana Acton, Rhea Y Liang, Jafi A Lipson, Martin J Yaffe, Daniel L Rubin, Alice S Whittemore, Laurel A Habel, Weiva Sieh. Alcohol and tobacco use in relation to mammographic density in 23,456 women [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-08-01.
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Affiliation(s)
| | - Kezhen Fei
- 1Icahn School of Medicine at Mount Sinai, New York, NY
| | | | | | - Xiaoyu Song
- 1Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lori C Sakoda
- 2Kaiser Permanente Division of Research, Oakland, CA
| | | | | | - Luana Acton
- 2Kaiser Permanente Division of Research, Oakland, CA
| | - Rhea Y Liang
- 3Stanford University School of Medicine, Stanford, CA
| | - Jafi A Lipson
- 4Stanford University School of Medicine, Oakland, CA
| | | | | | | | | | - Weiva Sieh
- 1Icahn School of Medicine at Mount Sinai, New York, NY
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Lee C, Check DK, Manace Brenman L, Kushi LH, Epstein MM, Neslund-Dudas C, Pawloski PA, Achacoso N, Laurent C, Fehrenbacher L, Habel LA. Adjuvant endocrine therapy for breast cancer patients: impact of a health system outreach program to improve adherence. Breast Cancer Res Treat 2020; 180:219-226. [PMID: 31975315 DOI: 10.1007/s10549-020-05539-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/17/2020] [Indexed: 11/30/2022]
Abstract
PURPOSE Reports suggest that up to 50% of women with hormone receptor-positive (HR+) breast cancer (BC) do not complete the recommended 5 years of adjuvant endocrine therapy (AET). We examined the impact of an outreach program at Kaiser Permanente Northern California (KPNC) on adherence and discontinuation of AET among patients who initiated AET. METHODS We assembled a retrospective cohort of all KPNC patients diagnosed with HR+, stage I-III BC initiating AET before (n = 4287) and after (n = 3580) implementation of the outreach program. We compared adherence proportions and discontinuation rates before and after program implementation, both crude and adjusted for age, race/ethnicity, education, income, and stage. We conducted a pooled analysis of data from six Cancer Research Network (CRN) sites that had not implemented programs for improving AET adherence, using identical methods and time periods, to assess possible secular trends. RESULTS In the pre-outreach period, estimated adherence in years 1, 2, and 3 following AET initiation was 75.2%, 71.0%, and 67.3%; following the outreach program, the estimates were 79.4%, 75.6%, and 72.2% (p-values < .0001 for pairwise comparisons). Results were comparable after adjusting for clinical and demographic factors. The estimated cumulative incidence of discontinuation was 0.22 (0.21-0.24) and 0.18 (0.17-0.19) at 3 years for pre- and post-outreach groups (p-value < .0001). We found no evidence of an increase in adherence between the study periods at the CRN sites with no AET adherence program. CONCLUSION Adherence and discontinuation after AET initiation improved modestly following implementation of the outreach program.
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Affiliation(s)
- Catherine Lee
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
| | - Devon K Check
- Department of Population Health Sciences, Duke University School of Medicine, Duke Cancer Institute, Durham, NC, USA
| | - Leslie Manace Brenman
- Kaiser Permanente Northern California Breast Cancer Tracking System, Oakland, CA, USA
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Mara M Epstein
- Meyers Primary Care Institute and the Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Christine Neslund-Dudas
- Department of Public Health Sciences, Henry Ford Health System and the Henry Ford Cancer Institute, Detroit, MI, USA
| | | | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Cecile Laurent
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Louis Fehrenbacher
- Kaiser Permanente Northern California Medical Oncology, Oakland, CA, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
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Watts EL, Perez‐Cornago A, Appleby PN, Albanes D, Ardanaz E, Black A, Bueno‐de‐Mesquita HB, Chan JM, Chen C, Chubb SP, Cook MB, Deschasaux M, Donovan JL, English DR, Flicker L, Freedman ND, Galan P, Giles GG, Giovannucci EL, Gunter MJ, Habel LA, Häggström C, Haiman C, Hamdy FC, Hercberg S, Holly JM, Huang J, Huang W, Johansson M, Kaaks R, Kubo T, Lane JA, Layne TM, Le Marchand L, Martin RM, Metter EJ, Mikami K, Milne RL, Morris HA, Mucci LA, Neal DE, Neuhouser ML, Oliver SE, Overvad K, Ozasa K, Pala V, Pernar CH, Pollak M, Rowlands M, Schaefer CA, Schenk JM, Stattin P, Tamakoshi A, Thysell E, Touvier M, Trichopoulou A, Tsilidis KK, Van Den Eeden SK, Weinstein SJ, Wilkens L, Yeap BB, Key TJ, Allen NE, Travis RC. The associations of anthropometric, behavioural and sociodemographic factors with circulating concentrations of IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 in a pooled analysis of 16,024 men from 22 studies. Int J Cancer 2019; 145:3244-3256. [PMID: 30873591 PMCID: PMC6745281 DOI: 10.1002/ijc.32276] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 01/28/2019] [Accepted: 02/04/2019] [Indexed: 12/24/2022]
Abstract
Insulin-like growth factors (IGFs) and insulin-like growth factor binding proteins (IGFBPs) have been implicated in the aetiology of several cancers. To better understand whether anthropometric, behavioural and sociodemographic factors may play a role in cancer risk via IGF signalling, we examined the cross-sectional associations of these exposures with circulating concentrations of IGFs (IGF-I and IGF-II) and IGFBPs (IGFBP-1, IGFBP-2 and IGFBP-3). The Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset includes individual participant data from 16,024 male controls (i.e. without prostate cancer) aged 22-89 years from 22 prospective studies. Geometric means of protein concentrations were estimated using analysis of variance, adjusted for relevant covariates. Older age was associated with higher concentrations of IGFBP-1 and IGFBP-2 and lower concentrations of IGF-I, IGF-II and IGFBP-3. Higher body mass index was associated with lower concentrations of IGFBP-1 and IGFBP-2. Taller height was associated with higher concentrations of IGF-I and IGFBP-3 and lower concentrations of IGFBP-1. Smokers had higher concentrations of IGFBP-1 and IGFBP-2 and lower concentrations of IGFBP-3 than nonsmokers. Higher alcohol consumption was associated with higher concentrations of IGF-II and lower concentrations of IGF-I and IGFBP-2. African Americans had lower concentrations of IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 and Hispanics had lower IGF-I, IGF-II and IGFBP-3 than non-Hispanic whites. These findings indicate that a range of anthropometric, behavioural and sociodemographic factors are associated with circulating concentrations of IGFs and IGFBPs in men, which will lead to a greater understanding of the mechanisms through which these factors influence cancer risk.
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Affiliation(s)
- Eleanor L. Watts
- Cancer Epidemiology UnitNuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Aurora Perez‐Cornago
- Cancer Epidemiology UnitNuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Paul N. Appleby
- Cancer Epidemiology UnitNuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaMD
| | - Eva Ardanaz
- Navarra Public Health InstitutePamplonaSpain
| | - Amanda Black
- Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaMD
| | - H. Bas Bueno‐de‐Mesquita
- Department for Determinants of Chronic DiseasesNational Institute for Public Health and the Environment (RIVM)BilthovenThe Netherlands
- Department of Gastroenterology and HepatologyUniversity Medical CentreUtrechtThe Netherlands
- Department of Epidemiology and BiostatisticsImperial College LondonLondonUnited Kingdom
- Department of Social & Preventive MedicineUniversity of MalayaKuala LumpurMalaysia
| | - June M. Chan
- Department of Epidemiology and BiostatisticsUniversity of California San FranciscoSan FranciscoCA
- Department UrologyUniversity of California‐San FranciscoSan FranciscoCA
| | - Chu Chen
- Public Health Sciences Division, Program in EpidemiologyFred Hutchinson Cancer Research CenterSeattleWA
| | - S.A. Paul Chubb
- PathWest Laboratory MedicineFiona Stanley HospitalPerthWAAustralia
- Medical SchoolUniversity of Western AustraliaPerthWAAustralia
| | - Michael B. Cook
- Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaMD
| | - Mélanie Deschasaux
- Sorbonne Paris Cité Epidemiology and Statistics Research Center (CRESS)Nutritional Epidemiology Research Team (EREN), Inserm U1153/Inra U1125/Cnam/Paris 13 UniversityParisFrance
| | - Jenny L. Donovan
- Department of Population Health SciencesBristol Medical School, University of BristolBristolUnited Kingdom
| | - Dallas R. English
- Cancer Epidemiology and Intelligence DivisionCancer Council VictoriaMelbourneVICAustralia
- Centre for Epidemiology and BiostatisticsMelbourne School of Population and Global Health, The University of MelbourneMelbourneVICAustralia
| | - Leon Flicker
- Medical SchoolUniversity of Western AustraliaPerthWAAustralia
- WA Centre for Health & Ageing, Centre for Medical ResearchHarry Perkins Institute of Medical ResearchPerthWAAustralia
- Department of Geriatric MedicineRoyal Perth HospitalPerthWAAustralia
| | - Neal D. Freedman
- Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaMD
| | - Pilar Galan
- Sorbonne Paris Cité Epidemiology and Statistics Research Center (CRESS)Nutritional Epidemiology Research Team (EREN), Inserm U1153/Inra U1125/Cnam/Paris 13 UniversityParisFrance
| | - Graham G. Giles
- Cancer Epidemiology and Intelligence DivisionCancer Council VictoriaMelbourneVICAustralia
- Centre for Epidemiology and BiostatisticsMelbourne School of Population and Global Health, The University of MelbourneMelbourneVICAustralia
| | - Edward L. Giovannucci
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMA
- Channing Division of Network MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMA
- Department of NutritionHarvard T.H. Chan School of Public HealthBostonMA
| | - Marc J. Gunter
- Section of Nutrition and MetabolismInternational Agency for Research on CancerLyonFrance
| | - Laurel A. Habel
- Division of ResearchKaiser Permanente Northern CaliforniaOaklandCA
| | | | | | - Freddie C. Hamdy
- Nuffield Department of SurgeryUniversity of OxfordOxfordUnited Kingdom
| | - Serge Hercberg
- Sorbonne Paris Cité Epidemiology and Statistics Research Center (CRESS)Nutritional Epidemiology Research Team (EREN), Inserm U1153/Inra U1125/Cnam/Paris 13 UniversityParisFrance
| | - Jeff M. Holly
- IGFs & Metabolic Endocrinology Group, Translational Health SciencesBristol Medical School, Faculty of Health Sciences, University of BristolBristolUnited Kingdom
| | - Jiaqi Huang
- Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaMD
| | - Wen‐Yi Huang
- Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaMD
| | - Mattias Johansson
- Genetic Epidemiology GroupInternational Agency for Research on CancerLyonFrance
| | - Rudolf Kaaks
- Division of Cancer EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Tatsuhiko Kubo
- Department of Environmental EpidemiologyUniversity of Occupational and Environmental HealthKitakyushuJapan
| | - J. Athene Lane
- Department of Population Health SciencesBristol Medical School, University of BristolBristolUnited Kingdom
- National Institute for Health Research Bristol Biomedical Research Unit in NutritionBristolUnited Kingdom
| | | | | | - Richard M. Martin
- Department of Population Health SciencesBristol Medical School, University of BristolBristolUnited Kingdom
- National Institute for Health Research Bristol Biomedical Research Unit in NutritionBristolUnited Kingdom
- Medical Research Council/University of Bristol Integrative Epidemiology Unit, University of BristolBristolUnited Kingdom
| | - E. Jeffrey Metter
- Department of NeurologyUniversity of Tennessee Health Science CenterMemphisTN
| | | | - Roger L. Milne
- Cancer Epidemiology and Intelligence DivisionCancer Council VictoriaMelbourneVICAustralia
- Centre for Epidemiology and BiostatisticsMelbourne School of Population and Global Health, The University of MelbourneMelbourneVICAustralia
| | | | - Lorelei A. Mucci
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMA
- Channing Division of Network MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMA
| | - David E. Neal
- Nuffield Department of SurgeryUniversity of OxfordOxfordUnited Kingdom
| | - Marian L. Neuhouser
- Cancer Prevention Program, Public Health Sciences DivisionFred Hutchinson Cancer Research CenterSeattleWA
| | - Steven E. Oliver
- Department of Health SciencesUniversity of York and the Hull York Medical SchoolYorkUK
| | - Kim Overvad
- Department of Public HealthSection for Epidemiology, Aarhus UniversityAarhusDenmark
| | - Kotaro Ozasa
- Radiation Effects Research FoundationHiroshimaJapan
| | - Valeria Pala
- Epidemiology and Prevention UnitFondazione IRCCS Istituto Nazionale dei Tumori di MilanoMilanItaly
| | - Claire H. Pernar
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMA
| | - Michael Pollak
- Department of Medicine and OncologyMcGill UniversityMontrealQCCanada
- Segal Cancer CentreJewish General HospitalMontrealQCCanada
| | - Mari‐Anne Rowlands
- Department of Population Health SciencesBristol Medical School, University of BristolBristolUnited Kingdom
| | | | - Jeannette M. Schenk
- Cancer Prevention Program, Public Health Sciences DivisionFred Hutchinson Cancer Research CenterSeattleWA
| | - Pär Stattin
- Department of Surgical SciencesUppsala UniversityUppsalaSweden
| | | | - Elin Thysell
- Department of Medical Biosciences and PathologyUmea UniversityUmeaSweden
| | - Mathilde Touvier
- Sorbonne Paris Cité Epidemiology and Statistics Research Center (CRESS)Nutritional Epidemiology Research Team (EREN), Inserm U1153/Inra U1125/Cnam/Paris 13 UniversityParisFrance
| | | | - Konstantinos K. Tsilidis
- Department of Epidemiology and BiostatisticsImperial College LondonLondonUnited Kingdom
- Department of Hygiene and Epidemiology, School of MedicineUniversity of IoanninaIoanninaGreece
| | | | - Stephanie J. Weinstein
- Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthBethesdaMD
| | | | - Bu B. Yeap
- Medical SchoolUniversity of Western AustraliaPerthWAAustralia
- Department of Endocrinology and DiabetesFiona Stanley HospitalPerthWAAustralia
| | - Timothy J. Key
- Cancer Epidemiology UnitNuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Naomi E. Allen
- Clinical Trial Service Unit and Epidemiological Studies UnitNuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Ruth C. Travis
- Cancer Epidemiology UnitNuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
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Alexeeff SE, Odo NU, McBride R, McGuire V, Achacoso N, Rothstein JH, Lipson JA, Liang RY, Acton L, Yaffe MJ, Whittemore AS, Rubin DL, Sieh W, Habel LA. Reproductive Factors and Mammographic Density: Associations Among 24,840 Women and Comparison of Studies Using Digitized Film-Screen Mammography and Full-Field Digital Mammography. Am J Epidemiol 2019; 188:1144-1154. [PMID: 30865217 DOI: 10.1093/aje/kwz033] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 01/29/2019] [Accepted: 02/04/2019] [Indexed: 11/14/2022] Open
Abstract
Breast density is a modifiable factor that is strongly associated with breast cancer risk. We sought to understand the influence of newer technologies of full-field digital mammography (FFDM) on breast density research and to determine whether results are comparable across studies using FFDM and previous studies using traditional film-screen mammography. We studied 24,840 screening-age (40-74 years) non-Hispanic white women who were participants in the Research Program on Genes, Environment and Health of Kaiser Permanente Northern California and underwent screening mammography with either Hologic (Hologic, Inc., Marlborough, Massachusetts) or General Electric (General Electric Company, Boston, Massachusetts) FFDM machines between 2003 and 2013. We estimated the associations of parity, age at first birth, age at menarche, and menopausal status with percent density and dense area as measured by a single radiological technologist using Cumulus software (Canto Software, Inc., San Francisco, California). We found that associations between reproductive factors and mammographic density measured using processed FFDM images were generally similar in magnitude and direction to those from prior studies using film mammography. Estimated associations for both types of FFDM machines were in the same direction. There was some evidence of heterogeneity in the magnitude of the effect sizes by machine type, which we accounted for using random-effects meta-analysis when combining results. Our findings demonstrate the robustness of quantitative mammographic density measurements across FFDM and film mammography platforms.
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Affiliation(s)
- Stacey E Alexeeff
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | | | - Russell McBride
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Valerie McGuire
- Department of Health Research and Policy, Division of Epidemiology, School of Medicine, Stanford University, Stanford, California
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Joseph H Rothstein
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Jafi A Lipson
- Department of Radiology, School of Medicine, Stanford University, Stanford, California
| | - Rhea Y Liang
- Department of Radiology, School of Medicine, Stanford University, Stanford, California
| | - Luana Acton
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Martin J Yaffe
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Alice S Whittemore
- Department of Health Research and Policy, Division of Epidemiology, School of Medicine, Stanford University, Stanford, California
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California
| | - Daniel L Rubin
- Department of Radiology, School of Medicine, Stanford University, Stanford, California
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California
| | - Weiva Sieh
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California
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Bradley MC, Ferrara A, Achacoso N, Ehrlich SF, Quesenberry CP, Habel LA. A Cohort Study of Metformin and Colorectal Cancer Risk among Patients with Diabetes Mellitus. Cancer Epidemiol Biomarkers Prev 2019; 27:525-530. [PMID: 29716927 DOI: 10.1158/1055-9965.epi-17-0424] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 09/05/2017] [Accepted: 11/22/2017] [Indexed: 12/29/2022] Open
Abstract
Background: Several epidemiologic studies have reported strong inverse associations between metformin use and risk of colorectal cancer, although time-related biases, such as immortal time bias, may in part explain these findings. We reexamined this association using methods to minimize these biases.Methods: A cohort study was conducted among 47,351 members of Kaiser Permanente Northern California with diabetes and no history of cancer or metformin use. Follow-up for incident colorectal cancer occurred from January 1, 1997, until June 30, 2012. Cox regression was used to calculate HRs and 95% confidence intervals (CIs) for colorectal cancer risk associated with metformin use (ever use, total duration, recency of use, and cumulative dose).Results: No association was observed between ever use of metformin and colorectal cancer risk (HR, 0.90; 95% CI, 0.76-1.07) and there was no consistent pattern of decreasing risk with increasing total duration, dose, or recency of use. However, long-term use (≥5.0 years) appeared to be associated with reduced risk of colorectal cancer in the full population (HR, 0.78; 95% CI, 0.60-1.02), among current users (HR, 0.78; 95% CI, 0.59-1.04), and in men (HR, 0.65; 95% CI, 0.45-0.94) but not in women. Higher cumulative doses of metformin were associated with reduced risk. In initial users of sulfonylureas, switching to or adding metformin was also associated with decreased colorectal cancer risk.Conclusions: Our findings showed an inverse association between long-term use of metformin and colorectal cancer risk. Findings, especially the risk reduction among men, need to be confirmed in large, well-conducted studies.Impact: If our findings are confirmed, metformin may have a role in the chemoprevention of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 27(5); 525-30. ©2018 AACRSee related commentary by Jackson and García-Albéniz, p. 520.
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Affiliation(s)
- Marie C Bradley
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland
| | - Assiamira Ferrara
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Samantha F Ehrlich
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | | | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, California.
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Abstract
CONTEXT Epidemiologic analyses of gabapentin use and cancer risk in Kaiser Permanente Northern California were previously carried out in a collaborative study and independently evaluated in a UK database. OBJECTIVE To update these epidemiologic analyses with 7.5 more years of follow-up. DESIGN Case-control analyses using conditional logistic regression to estimate relative risk by odds ratios using the prior collaboration's criteria for identifying positive drug-cancer associations and our more stringent criteria requiring stronger association, lower p values, and evidence of dose response. New associations were reanalyzed with additional control for limited measures of smoking and alcohol use. MAIN OUTCOME MEASURES Gabapentin-cancer associations. RESULTS No previously found associations met our stringent criteria, but cancers of the mouth/pharynx, esophagus, liver, and vagina did. All odds ratios for 3 or more and 8 or more prescriptions were moderately reduced by control for smoking and alcohol. Substantial elevations of risk of mouth/pharynx, liver, and vaginal cancers were associated with only 1 prescription dispensed. Sensitivity analyses aimed at possible confounding and other biases did not change our conclusions but did reveal a markedly increased risk of vaginal cancer in gabapentin users with epilepsy compared with users without. CONCLUSION The reduced magnitude of relative risk with control for smoking and alcohol use suggests confounding by known risk factors. Biologically implausible elevated risk from just 1 prescription suggests confounding by indication. Either or both of these concerns applies to each of the 4 cancer sites associated with gabapentin use. Updated analyses show little if any evidence for carcinogenic effects of gabapentin.
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Affiliation(s)
- Gary D Friedman
- Division of Research, Oakland, CA.,Department of Health Research and Policy, Stanford University School of Medicine, CA
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Su KA, Habel LA, Achacoso NS, Friedman GD, Asgari MM. Photosensitizing antihypertensive drug use and risk of cutaneous squamous cell carcinoma. Br J Dermatol 2018; 179:1088-1094. [PMID: 29723931 PMCID: PMC6223125 DOI: 10.1111/bjd.16713] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/20/2018] [Indexed: 12/15/2022]
Abstract
BACKGROUND Many antihypertensive drugs (ADs) are photosensitizing, heightening reactivity of the skin to sunlight. Photosensitizing ADs have been associated with lip cancer, but whether they impact the risk of cutaneous squamous cell carcinoma (cSCC) is unknown. OBJECTIVES To examine the association between AD use and cSCC risk among a cohort of non-Hispanic white individuals with hypertension enrolled in a comprehensive integrated healthcare delivery system in northern California (n = 28 357). METHODS Electronic pharmacy data were used to determine exposure to ADs, which were classified as photosensitizing, nonphotosensitizing or unknown, based on published literature. We identified patients who developed a cSCC during follow-up (n = 3010). We used Cox modelling to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs). Covariates included age, sex, smoking, comorbidities, history of cSCC and actinic keratosis, survey year, healthcare utilization, length of health plan membership and history of photosensitizing AD use. RESULTS Compared with nonuse of ADs, risk of cSCC was increased with ever having used photosensitizing ADs (aHR = 1·17, 95% CI 1·07-1·28) and ever having used ADs of unknown photosensitizing potential (aHR = 1·11, 95% CI 1·02-1·20), whereas no association was seen with ever having used nonphotosensitizing ADs (aHR = 0·99; 95% CI 0·91-1·07). Additionally, there was a modest increased risk with an increased number of prescriptions for photosensitizing ADs (aHR = 1·12, 95% CI 1·02-1·24; aHR = 1·19, 95% CI 1·06-1·34; aHR = 1·41, 95% CI 1·20-1·67 for one to seven, eight to 15 and ≥ 16 fills, respectively). CONCLUSIONS These findings provide moderate support for an increased cSCC risk among individuals treated with photosensitizing ADs.
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Affiliation(s)
- K A Su
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, U.S.A
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, U.S.A
| | - L A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, U.S.A
| | - N S Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, U.S.A
| | - G D Friedman
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, U.S.A
| | - M M Asgari
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, U.S.A
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, U.S.A
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Check DK, Albers KB, Uppal KM, Suga JM, Adams AS, Habel LA, Quesenberry CP, Sakoda LC. Examining the role of access to care: Racial/ethnic differences in receipt of resection for early-stage non-small cell lung cancer among integrated system members and non-members. Lung Cancer 2018; 125:51-56. [PMID: 30429038 PMCID: PMC6242353 DOI: 10.1016/j.lungcan.2018.09.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Revised: 08/21/2018] [Accepted: 09/09/2018] [Indexed: 12/31/2022]
Abstract
OBJECTIVES To examine the role of uniform access to care in reducing racial/ethnic disparities in receipt of resection for early stage non-small cell lung cancer (NSCLC) by comparing integrated health system member patients to demographically similar non-member patients. MATERIALS AND METHODS Using data from the California Cancer Registry, we conducted a retrospective cohort study of patients from four racial/ethnic groups (White, Black, Hispanic, Asian/Pacific Islander), aged 21-80, with a first primary diagnosis of stage I or II NSCLC between 2004 and 2011, in counties served by Kaiser Permanente Northern California (KPNC) at diagnosis. Our cohort included 1565 KPNC member and 4221 non-member patients. To examine the relationship between race/ethnicity and receipt of surgery stratified by KPNC membership, we used modified Poisson regression to calculate risk ratios (RR) adjusted for patient demographic and tumor characteristics. RESULTS Black patients were least likely to receive surgery regardless of access to integrated care (64-65% in both groups). The magnitude of the black-white difference in the likelihood of surgery receipt was similar for members (RR: 0.82, 95% CI: 0.73-0.93) and non-members (RR: 0.86, 95% CI: 0.80-0.94). Among members, roughly equal proportions of Hispanic and White patients received surgery; however, among non-members, Hispanic patients were less likely to receive surgery (non-members, RR: 0.93, 95% CI: 0.86-1.00; members, RR: 0.98, 95% CI: 0.89-1.08). CONCLUSION Disparities in surgical treatment for NSCLC were not reduced through integrated health system membership, suggesting that factors other than access to care (e.g., patient-provider communication) may underlie disparities. Future research should focus on identifying such modifiable factors.
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Affiliation(s)
- Devon K Check
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA.
| | - Kathleen B Albers
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA.
| | - Kanti M Uppal
- Vacaville Medical Center, Kaiser Permanente Northern California, 1 Quality Drive, Vacaville, CA, 95688, USA.
| | - Jennifer Marie Suga
- Vallejo Medical Center, Kaiser Permanente Northern California, 975 Sereno Drive, Vallejo, CA, 94589, USA.
| | - Alyce S Adams
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA.
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA.
| | - Charles P Quesenberry
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA.
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA.
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Banegas MP, Emerson MA, Adams AS, Achacoso NS, Chawla N, Alexeeff S, Habel LA. Patterns of medication adherence in a multi-ethnic cohort of prevalent statin users diagnosed with breast, prostate, or colorectal cancer. J Cancer Surviv 2018; 12:794-802. [PMID: 30338462 DOI: 10.1007/s11764-018-0716-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2018] [Accepted: 09/11/2018] [Indexed: 01/16/2023]
Abstract
PURPOSE To investigate the implications of a cancer diagnosis on medication adherence for pre-existing comorbid conditions, we explored statin adherence patterns prior to and following a new diagnosis of breast, colorectal, or prostate cancer among a multi-ethnic cohort. METHODS We identified adults enrolled at Kaiser Permanente Northern California who were prevalent statin medication users, newly diagnosed with breast, colorectal, or prostate cancer between 2000 and 2012. Statin adherence was measured using the proportion of days covered (PDC) during the 2-year pre-cancer diagnosis and the 2-year post-cancer diagnosis. Adherence patterns were assessed using generalized estimating equations, for all cancers combined and stratified by cancer type and race/ethnicity, adjusted for demographic, clinical, and tumor characteristics. RESULTS Among 10,177 cancer patients, statin adherence decreased from pre- to post-cancer diagnosis (adjusted odds ratio (ORadj):0.91, 95% confidence interval (95% CI):0.88-0.94). Statin adherence decreased from pre- to post-cancer diagnosis among breast (ORadj:0.94, 95% CI:0.90-0.99) and colorectal (ORadj:0.79, 95% CI:0.74-0.85) cancer patients. No difference in adherence was observed among prostate cancer patients (ORadj:1.01, 95% CI:0.97-1.05). Prior to cancer diagnosis, adherence to statins was generally higher among non-Hispanic whites and multi-race patients than other groups. However, statin adherence after diagnosis decreased only among these two populations (ORadj:0.85, 95% CI:0.85-0.92 and ORadj:0.86, 95% CI:0.76-0.97), respectively. CONCLUSIONS We found substantial variation in statin medication adherence following diagnosis by cancer type and race/ethnicity among a large cohort of prevalent statin users in an integrated health care setting. IMPLICATIONS FOR CANCER SURVIVORS Improving our understanding of comorbidity management and polypharmacy across diverse cancer patient populations is warranted to develop tailored interventions that improve medication adherence and reduce disparities in health outcomes.
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Affiliation(s)
- Matthew P Banegas
- Center for Health Research, Kaiser Permanente Northwest, 3800 N. Interstate Ave, Portland, OR, 97227-1110, USA.
| | - Marc A Emerson
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Alyce S Adams
- Division of Research, Kaiser Permanente, Oakland, CA, USA
| | | | - Neetu Chawla
- Division of Research, Kaiser Permanente, Oakland, CA, USA
| | | | - Laurel A Habel
- Division of Research, Kaiser Permanente, Oakland, CA, USA
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Kuehner G, Darbinian JA, Butler S, Chang S, Fehrenbacher L, Chen R, Habel LA, Axelsson K. Abstract P5-22-07: Upgrade to high risk lesions, in situ and invasive cancer among women with benign papillary lesions diagnosed on image-guided core needle biopsy (IGCNB). Cancer Res 2018. [DOI: 10.1158/1538-7445.sabcs17-p5-22-07] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Currently there is no consensus regarding the management of benign papillary breast lesions diagnosed on IGCNB. Recommendations vary as to whether all IGCNB papillary lesions require surgical excision or if IGCNB alone is adequate to confirm a benign diagnosis and patients can be followed with imaging.
Aims: To estimate percentage of patients with benign papilloma on IGNB who on surgical excision are upgraded to high risk lesion, in situ or invasive cancer and to identify patient, imaging, and/or pathologic features that are predictive of upgrade.
Methods: We conducted a study of 407 patients within Kaiser Permanente Northern California (KPNC) diagnosed with benign papillary breast lesions on IGCNB in 2012 and 2013. KPNC is a large integrated health care delivery system, racially and ethnically diverse, and representative of the underlying population. Patients were excluded from study if they were < 18 years, had atypia on IGCNB, had a prior history of breast cancer or high risk lesion, had a hereditary risk for developing breast cancer, or were noted to have papillomatosis or an incidental papilloma, or the target lesion was calcifications. Patients who did not have surgical excision of the IGCNB papilloma were followed for at least 2 years. Outcomes included in situ/invasive cancer and high risk lesions (atypical ductal or lobular hyperplasia, lobular carcinoma in-situ or papilloma with atypia). Outcomes were evaluated by review of medical records, including radiology, pathology, and surgical reports. The KPNC cancer registry and record review was used to exclude patients with a history of cancer.
Results: Among patients with benign papillary lesions, the average age was 56.4 years (range 20-93). Approximately 60% of lesions were 1 cm or less and 50% were centrally located (within 2 cm of nipple). There were 327 patients (80%) with surgical excision within 10 months of IGCNB, 61 patients (15%) with no surgical excision but follow-up imaging, and 19 patients (5%) with no surgery or follow-up imaging. Patients with and without surgical excision generally had similar age, breast density, and lesion location. However, surgical excision was more common among women with larger lesions. Among women with surgical excision, 9.5% (95% CI 6.3-12.7%) had a high risk lesion, 3.4% (95% CI 1.4-5.3-%) had an in situ lesion and 2.4% (95% CI 0.8-4.1%) had invasive cancer (all node negative). Less than 3% of women under 50 years, presenting with nipple discharge or with lesions less than 1 cm had invasive cancer on surgical excision. In contrast, over 10% of women with lesions greater than 1 cm, a palpable mass, or with lesions 5 or more cm from the nipple had invasive cancer on surgical excision. There were no cancers diagnosed among the 61 women followed by imaging; although 1 woman was upgraded to a high risk lesion.
Conclusions: In this large cohort of patients with benign papillary lesions on IGCNB, less than 3% had an invasive cancer on surgical excision. Upgrade was most common among patients with larger lesions, a palpable mass or lesions distant from the nipple and least common among women less than 50 years, with small lesions or presenting with nipple discharge.
Citation Format: Kuehner G, Darbinian JA, Butler S, Chang S, Fehrenbacher L, Chen R, Habel LA, Axelsson K. Upgrade to high risk lesions, in situ and invasive cancer among women with benign papillary lesions diagnosed on image-guided core needle biopsy (IGCNB) [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-22-07.
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Affiliation(s)
- G Kuehner
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
| | - JA Darbinian
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
| | - S Butler
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
| | - S Chang
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
| | - L Fehrenbacher
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
| | - R Chen
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
| | - LA Habel
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
| | - K Axelsson
- The Premanente Medical Group, Vallejo, CA; Kaiser Permanente Division of Research, Oakland, CA; The Permanent Medical Group, South San Francisco, CA; The Permanente Medical Group, Fremont, CA; The Permanente Medical Group, Oakland, CA
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49
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Krieger N, Nabavi S, Waterman PD, Achacoso NS, Acton L, Schnitt SJ, Habel LA. Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old? Cancer Causes Control 2018; 29:305-314. [PMID: 29427260 DOI: 10.1007/s10552-018-1006-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 01/30/2018] [Indexed: 10/18/2022]
Abstract
PURPOSE The purpose of the study was to assess the feasibility of quantifying long-term trends in breast tumor DNA copy number variation (CNV) profiles. METHODS We evaluated CNV profiles in formalin-fixed paraffin-embedded (FFPE) tumor specimens from 30 randomly selected Kaiser Permanente Northern California health plan women members diagnosed with breast cancer from 1950 to 2010. Assays were conducted for five cases per decade who had available tumor blocks and pathology reports. RESULTS As compared to the tumors from the 1970s to 2000s, the older tumors dating back to the 1950s and 1960s were much more likely to (1) fail quality control, and (2) have fewer CNV events (average 23 and 31 vs. 58 to 69), fewer CNV genes (average 5.1 and 3.7k vs. 8.1 to 10.3k), shorter CNV length (average 2,440 and 3,300k vs. 5,740 to 9,280k), fewer high frequency Del genes (37 and 25% vs. 54 to 76%), and fewer high frequency high_Amp genes (20% vs. 56 to 73%). On average, assay interpretation took an extra 60 min/specimen for cases from the 1960s versus 20 min/specimen for the most recent tumors. CONCLUSIONS Assays conducted in the mid-2010s for CNVs may be feasible for FFPE tumor specimens dating back to the 1980s, but less feasible for older specimens.
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Affiliation(s)
- Nancy Krieger
- Dept of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Kresge 717, Boston, MA, 02130, USA.
| | - Sheida Nabavi
- Dept of Computer Science and Engineering, University of Connecticut, 371 Fairfield Way, Storrs, CT, 06269, USA
| | - Pamela D Waterman
- Dept of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02130, USA
| | - Ninah S Achacoso
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA
| | - Luana Acton
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA
| | - Stuart J Schnitt
- Dana-Farber Cancer Institute/Brigham and Women's Hospital Breast Oncology Program, Department of Pathology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, 94612, USA
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50
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Friedman GD, Habel LA, Achacoso N, Sanders CM, Oyer HM, Fireman B, Van Den Eeden SK, Kim FJ. Haloperidol and Prostate Cancer Prevention: More Epidemiologic Research Needed. Perm J 2018; 24:18.313. [PMID: 31852040 DOI: 10.7812/tpp/18.313] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
CONTEXT The antipsychotic drug haloperidol has antiproliferative and growth-inhibiting properties on prostate cancer cell lines in vitro by binding the sigma 1 protein. Evidence is needed regarding a possible preventive association in men. OBJECTIVE To examine whether our epidemiologic data support an inverse association of haloperidol use with risk of prostate cancer. DESIGN These case-control analyses used conditional logistic regression to estimate relative risk by odds ratios (ORs) adjusting for race/ethnicity and aspects of medical care related to detection of prostate cancer. We tested 3 other commonly used antipsychotic drugs, risperidone, quetiapine, and olanzapine, for sigma 1 protein binding and inhibition of clonogenic growth of prostate cancer cells. Use of any of these by men was considered use of a comparator drug. MAIN OUTCOME MEASURES 1) association of haloperidol with prostate cancer; 2) sigma 1 binding and clonogenic growth. RESULTS Probably owing to small numbers of haloperidol recipients, evidence of a preventive association was inconsistent, depending on the definition of long-term use. If duration of use was greater than 1 year, the odds ratio (OR) was 0.38 (95% confidence interval (CI) = 0.14-1.01) for haloperidol and 0.80 (95% CI = 0.66-0.98) for the comparator drug; if the duration of use was greater than 2 years, the OR was 0.66 (95% CI = 0.24-1.76) for haloperidol and 0.84 (95% CI = 0.66-1.08) for the comparator drug. Unlike haloperidol, risperidone, quetiapine, and olanzapine did not bind sigma 1 or inhibit clonogenic growth. CONCLUSION Given the laboratory evidence, our ambiguous epidemiologic findings should encourage more epidemiologic evaluation of haloperidol use and risk of prostate cancer. Finding a negative association could be a scientific advance in prostate cancer prevention but would not be sufficient basis for recommending the prescription of haloperidol for that purpose.
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Affiliation(s)
- Gary D Friedman
- Division of Research, Kaiser Permanente Northern California, Oakland, CA.,Department of Health Research and Policy, Stanford University School of Medicine, CA
| | - Laurel A Habel
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Christina M Sanders
- Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA
| | - Halley M Oyer
- Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA
| | - Bruce Fireman
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | | | - Felix J Kim
- Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA
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