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Wang T, Dossett LA. Incorporating Value-Based Decisions in Breast Cancer Treatment Algorithms. Surg Oncol Clin N Am 2023; 32:777-797. [PMID: 37714643 DOI: 10.1016/j.soc.2023.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/17/2023]
Abstract
Given the excellent prognosis and availability of evidence-based treatment, patients with early-stage breast cancer are at risk of overtreatment. In this review, we summarize key opportunities to incorporate value-based decisions to optimize the delivery of high-value treatment across the breast cancer care continuum.
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Affiliation(s)
- Ton Wang
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Lesly A Dossett
- Department of Surgery, University of Michigan, Ann Arbor, MI, USA; Institute for Healthcare Policy and Innovation, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI 48109, USA.
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Louro J, Román M, Moshina N, Olstad CF, Larsen M, Sagstad S, Castells X, Hofvind S. Personalized Breast Cancer Screening: A Risk Prediction Model Based on Women Attending BreastScreen Norway. Cancers (Basel) 2023; 15:4517. [PMID: 37760486 PMCID: PMC10526465 DOI: 10.3390/cancers15184517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 09/06/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND We aimed to develop and validate a model predicting breast cancer risk for women targeted by breast cancer screening. METHOD This retrospective cohort study included 57,411 women screened at least once in BreastScreen Norway during the period from 2007 to 2019. The prediction model included information about age, mammographic density, family history of breast cancer, body mass index, age at menarche, alcohol consumption, exercise, pregnancy, hormone replacement therapy, and benign breast disease. We calculated a 4-year absolute breast cancer risk estimates for women and in risk groups by quartiles. The Bootstrap resampling method was used for internal validation of the model (E/O ratio). The area under the curve (AUC) was estimated with a 95% confidence interval (CI). RESULTS The 4-year predicted risk of breast cancer ranged from 0.22-7.33%, while 95% of the population had a risk of 0.55-2.31%. The thresholds for the quartiles of the risk groups, with 25% of the population in each group, were 0.82%, 1.10%, and 1.47%. Overall, the model slightly overestimated the risk with an E/O ratio of 1.10 (95% CI: 1.09-1.11) and the AUC was 62.6% (95% CI: 60.5-65.0%). CONCLUSIONS This 4-year risk prediction model showed differences in the risk of breast cancer, supporting personalized screening for breast cancer in women aged 50-69 years.
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Affiliation(s)
- Javier Louro
- Department of Epidemiology and Evaluation, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (J.L.); (M.R.); (X.C.)
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 48902 Barakaldo, Spain
| | - Marta Román
- Department of Epidemiology and Evaluation, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (J.L.); (M.R.); (X.C.)
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 48902 Barakaldo, Spain
| | - Nataliia Moshina
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Camilla F. Olstad
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Marthe Larsen
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Silje Sagstad
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
| | - Xavier Castells
- Department of Epidemiology and Evaluation, Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (J.L.); (M.R.); (X.C.)
- Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), 48902 Barakaldo, Spain
| | - Solveig Hofvind
- Section for Breast Cancer Screening, Cancer Registry of Norway, 0304 Oslo, Norway; (N.M.); (C.F.O.); (M.L.); (S.S.)
- Department of Health and Care Sciences, Faculty of Health Sciences, UiT, The Arctic University of Norway, 9037 Tromsø, Norway
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Siddique M, Liu M, Duong P, Jambawalikar S, Ha R. Deep Learning Approaches with Digital Mammography for Evaluating Breast Cancer Risk, a Narrative Review. Tomography 2023; 9:1110-1119. [PMID: 37368543 DOI: 10.3390/tomography9030091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/29/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023] Open
Abstract
Breast cancer remains the leading cause of cancer-related deaths in women worldwide. Current screening regimens and clinical breast cancer risk assessment models use risk factors such as demographics and patient history to guide policy and assess risk. Applications of artificial intelligence methods (AI) such as deep learning (DL) and convolutional neural networks (CNNs) to evaluate individual patient information and imaging showed promise as personalized risk models. We reviewed the current literature for studies related to deep learning and convolutional neural networks with digital mammography for assessing breast cancer risk. We discussed the literature and examined the ongoing and future applications of deep learning techniques in breast cancer risk modeling.
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Affiliation(s)
- Maham Siddique
- Department of Radiology, Columbia University Medical Center, New York, NY 10032, USA
| | - Michael Liu
- Department of Radiology, Columbia University Medical Center, New York, NY 10032, USA
| | - Phuong Duong
- Department of Radiology, Columbia University Medical Center, New York, NY 10032, USA
| | - Sachin Jambawalikar
- Department of Radiology, Columbia University Medical Center, New York, NY 10032, USA
| | - Richard Ha
- Department of Radiology, Columbia University Medical Center, New York, NY 10032, USA
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Ali KAS, Fateh SM. Mammographic breast density status in women aged more than 40 years in Sulaimaniyah, Iraq: a cross-sectional study. J Int Med Res 2022; 50:3000605221139712. [DOI: 10.1177/03000605221139712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Objective Mammography is the gold standard screening procedure for the early diagnosis of breast cancer. This study aimed to determine the distribution of breast density among women older than 40 years in Sulaimaniyah, Iraq, and to examine the correlations between breast density and various risk factors. Methods This cross-sectional study included 750 women who received routine mammographic breast screening at Sulaimaniyah Breast Center. Bilateral standard two-view mammographic images (craniocaudal and mediolateral oblique projections) were acquired and reported using a picture archiving and communication system. American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) assessment categories C and D were considered as dense. Results A total of 54.3% of breasts were classified as dense, with ACR-BI-RADS categories C or D. Breast density was significantly associated with age, body mass index, a family history of breast cancer, and pre-menopause, and women with no history of breastfeeding were more likely to have dense breasts than those with partial or complete breastfeeding. Conclusions This study revealed that women from Sulaimaniyah with a distinct breast-density profile at mammographic screening may have a significantly increased risk of breast cancer.
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Affiliation(s)
- Kalthum Abdullah Sofi Ali
- Department of Radiology/Surgery, College of Medicine, University of Sulaimani, 46001 Sulaimaniyah, Iraq
| | - Salah Muhammed Fateh
- Department of Radiology/Surgery, College of Medicine, University of Sulaimani, 46001 Sulaimaniyah, Iraq
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Flugelman AA, Burton A, Keinan-Boker L, Stein N, Kutner D, Shemesh L, Boyd N. Correlation between cumulative mammographic density and age-specific incidence of breast cancer: A biethnic study in Israel. Int J Cancer 2022; 150:1968-1977. [PMID: 35128649 DOI: 10.1002/ijc.33957] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 01/08/2022] [Accepted: 01/18/2022] [Indexed: 06/28/2024]
Abstract
Women with the most extensive breast density, have a 4- to 6-fold higher cancer risk than women with the lowest density. This cross-sectional study evaluated associations of cumulative mammographic density in two distinct ethnic groups with the respective age-specific breast cancer incidences in the population. The study compared four cohorts of 200 women each aged 35 to 49 and 50 to 74, representing Jewish and Arab ethnicity. Breast density measures were calculated from screening mammograms, using a thresholding software (Cumulus). Breast cancer specific incidence values were obtained from the National Cancer Registry. The percent mammographic density was lower for women aged 50 to 74 than 35 to 49 years, both for Jews: 11.7 vs 23.1 and for Arabs: 11.6 vs 18.3. In contrast, the cumulative density increased with age, from 37.30 to 181.24 in Jews, compared to 21.26 to 108.03 in Arabs. Similar trends in breast cancer incidence rates per 100 000 in the Israeli population were apparent, with an increase from 92.95 to 381.91 in Jews, compared to 48.6 to 244.44 in Arabs. Comparing cumulative density of the cohort with respective age-specific breast cancer incidence in the population yielded a highly significant correlation: Jews; r = .97, P < .0001 and Arabs: r = .86, P = .007. A strong association was found between the log of cumulative density and the log of cancer incidence, as well. Our study identified correlations between cumulative mammographic density and breast cancer incidence in two distinct populations. The findings should prompt research to enhance our understanding of the pathogenesis of breast cancer, and lead to novel insights into measures of prevention.
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Affiliation(s)
- Anath A Flugelman
- Rambam Health Care Campus, Technion-Israel Institute of Technology, Haifa, Israel
- Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Anya Burton
- National Cancer Registration and Analysis Service, Bristol, UK
| | - Lital Keinan-Boker
- National Cancer Registry, Center for Disease Control, Ministry of Health, Ramat Gan
- School of Public Health, University of Haifa, Haifa, Israel
| | - Nili Stein
- The Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa, Israel
- Clalit National Cancer Control Center, Haifa, Israel
| | - Dafna Kutner
- The Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa, Israel
- Clalit National Cancer Control Center, Haifa, Israel
| | - Lior Shemesh
- The Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa, Israel
- Clalit National Cancer Control Center, Haifa, Israel
| | - Norman Boyd
- Princess Margaret Cancer Center, Toronto, Ontario, Canada
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Classifying Breast Density from Mammogram with Pretrained CNNs and Weighted Average Ensembles. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
We are currently experiencing a revolution in data production and artificial intelligence (AI) applications. Data are produced much faster than they can be consumed. Thus, there is an urgent need to develop AI algorithms for all aspects of modern life. Furthermore, the medical field is a fertile field in which to apply AI techniques. Breast cancer is one of the most common cancers and a leading cause of death around the world. Early detection is critical to treating the disease effectively. Breast density plays a significant role in determining the likelihood and risk of breast cancer. Breast density describes the amount of fibrous and glandular tissue compared with the amount of fatty tissue in the breast. Breast density is categorized using a system called the ACR BI-RADS. The ACR assigns breast density to one of four classes. In class A, breasts are almost entirely fatty. In class B, scattered areas of fibroglandular density appear in the breasts. In class C, the breasts are heterogeneously dense. In class D, the breasts are extremely dense. This paper applies pre-trained Convolutional Neural Network (CNN) on a local mammogram dataset to classify breast density. Several transfer learning models were tested on a dataset consisting of more than 800 mammogram screenings from King Abdulaziz Medical City (KAMC). Inception V3, EfficientNet 2B0, and Xception gave the highest accuracy for both four- and two-class classification. To enhance the accuracy of density classification, we applied weighted average ensembles, and performance was visibly improved. The overall accuracy of ACR classification with weighted average ensembles was 78.11%.
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Ochi T, Tsunoda H, Yamauchi H, Takahashi O. Impact of childbirth history on dense breast in mammographic screening: a cross-sectional study. BMC Womens Health 2022; 22:194. [PMID: 35619123 PMCID: PMC9137205 DOI: 10.1186/s12905-022-01772-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/17/2022] [Indexed: 11/17/2022] Open
Abstract
Background The evaluation of breast density is important, because dense breast has been shown to be associated with increased risk of breast cancer and a greater risk of a false-negative diagnostic performance due to masking a tumor. Although the relationship between parity and dense breast is under investigation, conclusive evidence is lacking. We aimed to investigate whether parity affects breast density. Methods The study design is a cross-sectional study. The subjects are healthy Japanese women who underwent opportunistic mammographic screening at the center for preventive medicine at a single institution from January 2016 to December 2018. Clinical characteristics and lifestyle factors were obtained from questionnaires. Breast density was categorized into 4 groups, namely, almost entirely fatty dense, scattered fibroglandular dense, heterogeneously dense, and extremely dense, according to the Breast Imaging Reporting and Data System. Heterogeneously and extremely dense were considered collectively as dense breast. Multivariate logistic regression analysis was conducted to investigate the relationship between parity and dense breast among premenopausal and postmenopausal women separately. Results 7612 premenopausal and 9252 postmenopausal women were investigated. Dense breast was shown in 62.6% of nulliparity, 57.3% of single parity, 47.3% of two parity, 37.6% of more than two parity among premenopausal women, and in 41.6% of nulliparity, 31.1% of single parity, 19.3% of two parity, 10.1% of more than two parity among postmenopausal women. For premenopausal women, two parity, single parity and nulliparity showed a higher risk for dense breast with statistically significance (Odds Ratio (OR) adjusted for potential confounding factors: 1.458 (95% Confidence interval (CI); 1.123–1.894), 2.349 (95%CI; 1.801–3.064), 3.222 (95%CI; 2.500–4.151), respectively), compared with more than two parity. For postmenopausal women, two parity, single parity and nulliparity had a higher risk (OR: 1.849 (95%CI; 1.479–2.312), 3.023 (95%CI; 2.385–3.830), 4.954 (95%CI; 3.975–6.174), respectively) with statistically significance, compared with more than two parity. Conclusions Parity showed an inverse trend of having dense breast among both premenopausal and postmenopausal women. In particular, nulliparous women need to recognize their higher risk of dense breast. In the future, the declining fertility rate may affect the prevalence of dense breast in the world.
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Affiliation(s)
- Tomohiro Ochi
- Graduate School of Public Health, St. Luke's International University, 10-1 Akashi-cho, Chuo-ku, Tokyo, 104-0044, Japan. .,Department of Breast Surgical Oncology, St. Luke's International Hospital, Tokyo, Japan. .,Department of Breast Surgery and Oncology, Nippon Medical School Hospital, Tokyo, Japan.
| | - Hiroko Tsunoda
- Department of Radiology, St. Luke's International Hospital, Tokyo, Japan
| | - Hideko Yamauchi
- Department of Breast Surgical Oncology, St. Luke's International Hospital, Tokyo, Japan
| | - Osamu Takahashi
- Graduate School of Public Health, St. Luke's International University, 10-1 Akashi-cho, Chuo-ku, Tokyo, 104-0044, Japan.,Division of General Internal Medicine, Department of Internal Medicine, St. Luke's International Hospital, Tokyo, Japan
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Zhang F, Li G, Jin L, Jia C, Shi Q, Wu R. Diagnostic value of Doppler imaging for malignant non-mass breast lesions: with different diagnostic criteria for older and younger women: first results. Clin Hemorheol Microcirc 2022; 81:123-134. [PMID: 35147531 DOI: 10.3233/ch-211371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To evaluate and optimize the additional diagnostic value of Doppler imaging for malignant NMLs detected by US. MATERIALS AND METHODS The characteristics of 233 NMLs in Doppler imaging were analyzed, and different Adler grades of intralesional vessels were selected as the diagnostic cutoffs on Doppler imaging: grade 1 in the full cohort and in women < 40 years, and grade 0 in women ≥40 years. The diagnostic performance of US and US + Doppler imaging were calculated and compared with that of mammography. RESULTS The AUC of US + Doppler was larger than that of US alone in each group (P < 0.001). In the full cohort, addition of Doppler imaging increased specificity of US, but decreased sensitivity. However, by use of different diagnostic cutoffs in the two subgroups, it was possible to achieve high sensitivity and specificity simultaneously, which were 100% and 75.8% in women < 40 years, 94.7% and 69.5% in women ≥40 years, respectively. The AUC + Doppler was comparable to that of mammography in the full cohort and in women ≥40 years. In women < 40 years, the AUC of the combination was larger than that of mammography (P < 0.001). CONCLUSION Doppler imaging, with different Adler grades used as cutoffs in older versus younger women, can improve the specificity of US for the diagnosis of malignant NMLs without losing sensitivity. In younger women, US + Doppler imaging may be better than mammography.
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Affiliation(s)
- Fan Zhang
- Department of Ultrasound, Shanghai General Hospital, Xin Song Jiang Road, Shanghai, China
| | - Gang Li
- Department of Ultrasound, Shanghai General Hospital, Xin Song Jiang Road, Shanghai, China
| | - Lifang Jin
- Department of Ultrasound, Shanghai General Hospital, Xin Song Jiang Road, Shanghai, China
| | - Chao Jia
- Department of Ultrasound, Shanghai General Hospital, Xin Song Jiang Road, Shanghai, China
| | - Qiusheng Shi
- Department of Ultrasound, Shanghai General Hospital, Xin Song Jiang Road, Shanghai, China
| | - Rong Wu
- Department of Ultrasound, Shanghai General Hospital, Xin Song Jiang Road, Shanghai, China
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Shen C, Klein RW, Moss JL, Dodge DG, Chetlen AL, Stahl KA, Zhou S, Leslie DL, Ruffin MT, Lengerich EJ. Association Between Dense Breast Legislation and Cancer Stage at Diagnosis. Am J Prev Med 2021; 61:890-899. [PMID: 34376293 DOI: 10.1016/j.amepre.2021.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 05/17/2021] [Accepted: 05/20/2021] [Indexed: 11/26/2022]
Abstract
INTRODUCTION Many states have mandated breast density notification and insurance coverage for additional screening; yet, the association between such legislation and stage of diagnosis for breast cancer is unclear. This study investigates this association and examines the differential impacts among different age and race/ethnicity subgroups. METHODS The Surveillance, Epidemiology, and End Results database was queried to identify patients with breast cancer aged 40-74 years diagnosed between 2005 and 2016. Using a difference-in-differences multinomial logistic model, the odds of being diagnosed at different stages of cancer relative to the localized stage depending on legislation and individual characteristics were examined. Analyses were conducted in 2020-2021. RESULTS The study included 689,641 cases. Overall, the impact of notification legislation was not significant, whereas insurance coverage legislation was associated with 6% lower odds (OR=0.94, 95% CI=0.91, 0.96) of being diagnosed at the regional stage. The association between insurance coverage legislation and stage of diagnosis was even stronger among women aged 40-49 years, with 11% lower odds (OR=0.89, 95% CI=0.82, 0.96) of being diagnosed at the regional stage and 12% lower odds (OR=0.88, 95% CI=0.81, 0.96) of being diagnosed at the distant stage. Hispanic women benefited from notification laws, with 11% lower odds (OR=0.89, 95% CI=0.82, 0.97) of being diagnosed at distant stage. Neither notification nor supplemental screening insurance coverage legislation showed a substantial impact on Black women. CONCLUSIONS The findings imply that improving insurance coverage is more important than being notified overall. Raising awareness is important among Hispanic women; improving communication about dense breasts and access to screening might be more important than legislation among Black women.
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Affiliation(s)
- Chan Shen
- Department of Surgery, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania; Division of Health Services and Behavioral Research, Department of Public Health Sciences, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania; Penn State Cancer Institute, Hershey, Pennsylvania.
| | - Roger W Klein
- Department of Economics, Rutgers University, New Brunswick, New Jersey
| | - Jennifer L Moss
- Division of Health Services and Behavioral Research, Department of Public Health Sciences, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania; Penn State Cancer Institute, Hershey, Pennsylvania; Department of Family and Community Medicine, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania
| | - Daleela G Dodge
- Department of Surgery, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania; Penn State Cancer Institute, Hershey, Pennsylvania
| | - Alison L Chetlen
- Penn State Cancer Institute, Hershey, Pennsylvania; Department of Radiology, Milton S. Hershey Medical Center, Penn State Health, Hershey, Pennsylvania
| | - Kelly A Stahl
- Department of Surgery, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania
| | - Shouhao Zhou
- Division of Health Services and Behavioral Research, Department of Public Health Sciences, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania; Penn State Cancer Institute, Hershey, Pennsylvania; Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania
| | - Douglas L Leslie
- Division of Health Services and Behavioral Research, Department of Public Health Sciences, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania
| | - Mack T Ruffin
- Penn State Cancer Institute, Hershey, Pennsylvania; Department of Family and Community Medicine, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania
| | - Eugene J Lengerich
- Division of Health Services and Behavioral Research, Department of Public Health Sciences, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania; Penn State Cancer Institute, Hershey, Pennsylvania
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Vegunta S, Kling JM, Patel BK. Supplemental Cancer Screening for Women With Dense Breasts: Guidance for Health Care Professionals. Mayo Clin Proc 2021; 96:2891-2904. [PMID: 34686363 DOI: 10.1016/j.mayocp.2021.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 05/20/2021] [Accepted: 06/08/2021] [Indexed: 11/16/2022]
Abstract
Mammography is the standard for breast cancer screening. The sensitivity of mammography in identifying breast cancer, however, is reduced for women with dense breasts. Thirty-eight states have passed laws requiring that all women be notified of breast tissue density results in their mammogram report. The notification includes a statement that differs by state, encouraging women to discuss supplemental screening options with their health care professionals (HCPs). Several supplemental screening tests are available for women with dense breast tissue, but no established guidelines exist to direct HCPs in their recommendation of preferred supplemental screening test. Tailored screening, which takes into consideration the patient's mammographic breast density and lifetime breast cancer risk, can guide breast cancer screening strategies that are more comprehensive. This review describes the benefits and limitations of the various available supplemental screening tests to guide HCPs and patients in choosing the appropriate breast cancer screening.
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Affiliation(s)
- Suneela Vegunta
- Division of Women's Health Internal Medicine, Mayo Clinic, Scottsdale, AZ.
| | - Juliana M Kling
- Division of Women's Health Internal Medicine, Mayo Clinic, Scottsdale, AZ
| | - Bhavika K Patel
- Division of Breast Imaging, Mayo Clinic Hospital, Phoenix, AZ
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Distribution of Estimated Lifetime Breast Cancer Risk Among Women Undergoing Screening Mammography. AJR Am J Roentgenol 2021; 217:48-55. [PMID: 33978450 DOI: 10.2214/ajr.20.23333] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE. Supplemental screening breast MRI is recommended for women with an estimated lifetime risk of breast cancer of greater than 20-25%. The performance of risk prediction models varies for each individual and across groups of women. The present study investigates the concordance of three breast cancer risk prediction models among women presenting for screening mammography. SUBJECTS AND METHODS. In this prospective study, we calculated the estimated lifetime risk of breast cancer using the modified Gail, Tyrer-Cuzick version 7, and BRCAPRO models for each woman who presented for screening mammography. Per American Cancer Society guidelines, for each woman the risk was categorized as less than 20% or 20% or greater as well as less than 25% or 25% or greater with use of each model. Venn diagrams were constructed to evaluate concordance across models. The McNemar test was used to test differences in risk group allocations between models, with p ≤ .05 considered to denote statistical significance. RESULTS. Of 3503 screening mammography patients who underwent risk stratification, 3219 (91.9%) were eligible for risk estimation using all three models. Using at least one model, 440 (13.7%) women had a lifetime risk of 20% or greater, including 390 women (12.1%) according to the Tyrer-Cuzick version 7 model, 18 (0.6%) according to the BRCAPRO model, and 141 (4.4%) according to the modified Gail model. Six women (0.2%) had a risk of 20% or greater according to all three models. Women were significantly more likely to be classified as having a high lifetime breast cancer risk by the Tyrer-Cuzick version 7 model compared with the modified Gail model, with thresholds of 20% or greater (odds ratio, 6.4; 95% CI, 4.7-8.7) or 25% or greater (odds ratio, 7.4; 95% CI, 4.7-11.9) used for both models. CONCLUSION. To identify women with a high lifetime breast cancer risk, practices should use estimates of lifetime breast cancer risk derived from multiple risk prediction models.
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Lee JS, Oh M. Breast Cancer Screening in Asian Women with Dense Breast by Mammography: A Cross-Sectional Observational Study. Asian Pac J Cancer Prev 2021; 22:1165-1170. [PMID: 33906309 PMCID: PMC8325126 DOI: 10.31557/apjcp.2021.22.4.1165] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Indexed: 12/29/2022] Open
Abstract
Objective: Mammography density of Asian women is known to be higher than Western women. After 2009, the Korean National Cancer Screening Program (NCSP) has started to notify mammography density (MD). To investigate the effect of MD notification, we integrated screening results with national health insurance claim data from 2009 to 2013. Patients and Methods: We performed a cross-sectional observational study which investigated the crude detection rate (CDR), positive predictive value (PPV), and incidence rate of Interval Cancer (IC). IC was defined as breast cancer, where the interval between the screening date and date of diagnosis was more than 12 months and less than 24 months among participants with previous normal results. Results: CDR and PPV per 100,000 results increased from 510.9 to 756.2 and from 1842.5 to 3364.9, respectively. The incidence rate of IC per 100,000 negative results increased from 623.3 to 676.2. Women younger than 50 years had a high incidence of ICs. Conclusion: After notifying MD, the incidence rate of IC less increased comparing with CDR or PPV. Screening mammography could be more useful to Asian women when reporting MD.
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Affiliation(s)
- Jung Sun Lee
- Department of Surgery, Haeundae Paik Hospital, College of Medicine, Inje University, Busan, Korea
| | - Minkyung Oh
- Department of Pharmacology, Inje University College of medicine, Clinical Trial Center, Inje University Busan Paik Hospital, Busan, Korea
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Santos Aragon LN, Soto-Trujillo D. Effectiveness of Tomosynthesis Versus Digital Mammography in the Diagnosis of Suspicious Lesions for Breast Cancer in an Asymptomatic Population. Cureus 2021; 13:e13838. [PMID: 33717771 PMCID: PMC7952495 DOI: 10.7759/cureus.13838] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Introduction The most frequent malignant tumor in women is breast cancer. A dense breast may mask lesions within the tissue. The constant improvement in diagnosis techniques has made the diagnosis more accurate. Digital mammography loses sensitivity in dense breasts as lesions may be masked by the over-position of tissue. Tomosynthesis increases sensitivity and specificity over diagnostic mammography. In this study, we examine the effectiveness of tomosynthesis versus digital mammography in asymptomatic patients. Materials and methods A cohort study of 1,499 Mexican patients that came for screening at a private health service from January to December 2015. A Breast Imaging Reporting and Database System (BI-RADS) classification was given by a breast radiologist with the digital mammography reading. Later, a second breast radiologist reviewed the same patients with tomosynthesis and assigned a second BI-RADS category. Results Patients were divided into three age groups. The one with the most had patients between 40-49 years (51.3%), where re-staging to a higher BI-RADS occurred in 40 patients. Re-staging to a lower category was most common in the group of age above 50, where 30 patients were assigned BI-RADS 2 after tomosynthesis. Dense breast (C and D) represented 38%. After tomosynthesis, 28 patients were classified as BI-RADS 4 or 5. The prevalence of diseases in groups BI-RADS 4 and BI-RADS 5 after re-staging and a breast cancer result was 0.024, with a sensitivity of 54% and a specificity of 88%. When re-staging 2D mammography with 3D tomosynthesis for suspicious lesions classified BI-RADS 3, 4, or 5, the prevalence was 0.23, with a sensitivity of 45% and a specificity of 98%. In this study, patients were asymptomatic, yet 20 breast cancers were detected, with a sensitivity of 54% and a specificity of 88%, exceeding the specificity of diagnostic mammography. Moreover, when re-staging to a BI-RADS of suspicious findings, the sensitivity was 45%, with a specificity of as high as 98%.
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Lee JS, Oh M. Breast Density of Mammography is Correlated with Reproductive Risk Factors Regardless of Menopausal Status: A Cross-Sectional Study of the Korean National Screening Program. Asian Pac J Cancer Prev 2020; 21:1011-1018. [PMID: 32334463 PMCID: PMC7445990 DOI: 10.31557/apjcp.2020.21.4.1011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE To clarify the limitations of mammography screening for women with dense breasts, we examined breast density and its effects on screening results. PATIENTS AND METHODS We performed a cross-sectional, observational study on women who underwent mammography. Data from the National Cancer Screening Program(NCSP) from 2009 to 2013 were used. The study population consisted of participants with high breast density. We used a logistic regression analysis to evaluate the relationships between breast density and reproductive factors and screening results according to menopause status. RESULTS High breast density was reported for 57.5% of all participants (3,417,319 participants). Screening results indicated breast density of <25%, 25-50%, 51-75%, and ≥76% for 16.4%, 26.3%, 37.8%, and 19.5%, respectively, of participants. According to the screening results, high breast density was correlated with high deferment and recall rates. Reproductive factors, especially parity, breastfeeding, and use of oral contraceptives, had consistent effects on screening results of premenopausal and postmenopausal women. Regardless of menopausal status, age, early onset of menarche (15 years or younger), fewer live births (≤1 birth), and previous benign breast disease were correlated with increased breast density. In postmenopausal women, early-onset menopause and longer-term hormone replacement therapy (≥2 years) also independently increased breast density. CONCLUSION Breast density influenced screening results, which could increase the rate of recall. Breast density was also influenced by reproductive factors, with patterns similar to those of breast cancer risk, regardless of menopausal status. We need to identify high-risk women with high density who would probably benefit from supplemental breast cancer screening.
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Affiliation(s)
- Jung Sun Lee
- Department of Surgery, Haeundae Paik Hospital, College of Medicine, Inje University, Busan, Korea
| | - Minkyung Oh
- Department of Pharmacology, Inje University College of Medicine, Clinical Trial Center, Inje University Busan Paik Hospital, Busan, Korea
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