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Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review. Cancers (Basel) 2023; 15:cancers15041124. [PMID: 36831466 PMCID: PMC9953796 DOI: 10.3390/cancers15041124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 02/12/2023] Open
Abstract
BACKGROUND The benefits and harms of breast screening may be better balanced through a risk-stratified approach. We conducted a systematic review assessing the accuracy of questionnaire-based risk assessment tools for this purpose. METHODS Population: asymptomatic women aged ≥40 years; Intervention: questionnaire-based risk assessment tool (incorporating breast density and polygenic risk where available); Comparison: different tool applied to the same population; Primary outcome: breast cancer incidence; Scope: external validation studies identified from databases including Medline and Embase (period 1 January 2008-20 July 2021). We assessed calibration (goodness-of-fit) between expected and observed cancers and compared observed cancer rates by risk group. Risk of bias was assessed with PROBAST. RESULTS Of 5124 records, 13 were included examining 11 tools across 15 cohorts. The Gail tool was most represented (n = 11), followed by Tyrer-Cuzick (n = 5), BRCAPRO and iCARE-Lit (n = 3). No tool was consistently well-calibrated across multiple studies and breast density or polygenic risk scores did not improve calibration. Most tools identified a risk group with higher rates of observed cancers, but few tools identified lower-risk groups across different settings. All tools demonstrated a high risk of bias. CONCLUSION Some risk tools can identify groups of women at higher or lower breast cancer risk, but this is highly dependent on the setting and population.
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Kurian AW, Hughes E, Simmons T, Bernhisel R, Probst B, Meek S, Caswell-Jin JL, John EM, Lanchbury JS, Slavin TP, Wagner S, Gutin A, Rohan TE, Shadyab AH, Manson JE, Lane D, Chlebowski RT, Stefanick ML. Performance of the IBIS/Tyrer-Cuzick model of breast cancer risk by race and ethnicity in the Women's Health Initiative. Cancer 2021; 127:3742-3750. [PMID: 34228814 DOI: 10.1002/cncr.33767] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 05/28/2021] [Accepted: 06/05/2021] [Indexed: 12/20/2022]
Abstract
BACKGROUND The IBIS/Tyrer-Cuzick model is used clinically to guide breast cancer screening and prevention, but was developed primarily in non-Hispanic White women. Little is known about its long-term performance in a racially/ethnically diverse population. METHODS The Women's Health Initiative study enrolled postmenopausal women from 1993-1998. Women were included who were aged <80 years at enrollment with no prior breast cancer or mastectomy and with data required for IBIS/Tyrer-Cuzick calculation (weight; height; ages at menarche, first birth, and menopause; menopausal hormone therapy use; and family history of breast or ovarian cancer). Calibration was assessed by the ratio of observed breast cancer cases to the number expected by the IBIS/Tyrer-Cuzick model (O/E; calculated as the sum of cumulative hazards). Differential discrimination was tested for by self-reported race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian or Pacific Islander, and American Indian or Alaskan Native) using Cox regression. Exploratory analyses, including simulation of a protective single-nucleotide polymorphism (SNP), rs140068132 at 6q25, were performed. RESULTS During follow-up (median 18.9 years, maximum 23.4 years), 6783 breast cancer cases occurred among 90,967 women. IBIS/Tyrer-Cuzick was well calibrated overall (O/E ratio = 0.95; 95% CI, 0.93-0.97) and in most racial/ethnic groups, but overestimated risk for Hispanic women (O/E ratio = 0.75; 95% CI, 0.62-0.90). Discrimination did not differ by race/ethnicity. Exploratory simulation of the protective SNP suggested improved IBIS/Tyrer-Cuzick calibration for Hispanic women (O/E ratio = 0.80; 95% CI, 0.66-0.96). CONCLUSIONS The IBIS/Tyrer-Cuzick model is well calibrated for several racial/ethnic groups over 2 decades of follow-up. Studies that incorporate genetic and other risk factors, particularly among Hispanic women, are essential to improve breast cancer-risk prediction.
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Affiliation(s)
- Allison W Kurian
- Department of Medicine, Stanford University School of Medicine, Stanford, California.,Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, California
| | | | | | | | | | | | | | - Esther M John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, California
| | | | | | | | | | - Thomas E Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
| | - Aladdin H Shadyab
- Department of Family Medicine and Public Health, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Dorothy Lane
- Department of Family, Population and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York
| | - Rowan T Chlebowski
- Department of Medicine, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California
| | - Marcia L Stefanick
- Department of Medicine, Stanford University School of Medicine, Stanford, California
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Pal Choudhury P, Wilcox AN, Brook MN, Zhang Y, Ahearn T, Orr N, Coulson P, Schoemaker MJ, Jones ME, Gail MH, Swerdlow AJ, Chatterjee N, Garcia-Closas M. Comparative Validation of Breast Cancer Risk Prediction Models and Projections for Future Risk Stratification. J Natl Cancer Inst 2020; 112:278-285. [PMID: 31165158 DOI: 10.1093/jnci/djz113] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 01/31/2019] [Accepted: 05/29/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND External validation of risk models is critical for risk-stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) as a flexible tool for risk model development and comparative model validation and to make projections for population risk stratification. METHODS Performance of two recently developed models, one based on the Breast and Prostate Cancer Cohort Consortium analysis (iCARE-BPC3) and another based on a literature review (iCARE-Lit), were compared with two established models (Breast Cancer Risk Assessment Tool and International Breast Cancer Intervention Study Model) based on classical risk factors in a UK-based cohort of 64 874 white non-Hispanic women (863 patients) age 35-74 years. Risk projections in a target population of US white non-Hispanic women age 50-70 years assessed potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS). RESULTS The best calibrated models were iCARE-Lit (expected to observed number of cases [E/O] = 0.98, 95% confidence interval [CI] = 0.87 to 1.11) for women younger than 50 years, and iCARE-BPC3 (E/O = 1.00, 95% CI = 0.93 to 1.09) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify approximately 500 000 women at moderate to high risk (>3% 5-year risk) in the target population. Addition of MD and a 313-variant PRS is expected to increase this number to approximately 3.5 million women, and among them, approximately 153 000 are expected to develop invasive breast cancer within 5 years. CONCLUSIONS iCARE models based on classical risk factors perform similarly to or better than BCRAT or IBIS in white non-Hispanic women. Addition of MD and PRS can lead to substantial improvements in risk stratification. However, these integrated models require independent prospective validation before broad clinical applications.
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Affiliation(s)
| | - Amber N Wilcox
- Johns Hopkins University, Baltimore, MD.,Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda
| | | | - Yan Zhang
- Department of Biostatistics, Bloomberg School of Public Health
| | - Thomas Ahearn
- Johns Hopkins University, Baltimore, MD.,Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda
| | - Nick Orr
- Department of Biostatistics, Bloomberg School of Public Health.,Department of Oncology, School of Medicine.,Division of Breast Cancer Research, The Institute of Cancer Research, London, UK.,Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, UK
| | | | | | | | - Mitchell H Gail
- Johns Hopkins University, Baltimore, MD.,Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda
| | - Anthony J Swerdlow
- Division of Genetics and Epidemiology.,Division of Breast Cancer Research, The Institute of Cancer Research, London, UK
| | | | - Montserrat Garcia-Closas
- Johns Hopkins University, Baltimore, MD.,Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda
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Solikhah S, Nurdjannah S. Assessment of the risk of developing breast cancer using the Gail model in Asian females: A systematic review. Heliyon 2020; 6:e03794. [PMID: 32346636 PMCID: PMC7182726 DOI: 10.1016/j.heliyon.2020.e03794] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 02/25/2020] [Accepted: 04/14/2020] [Indexed: 12/13/2022] Open
Abstract
Introduction Currently, the Breast Cancer Risk Assessment Tool (BCRAT), also known as the Gail model (GM) has been widely recognized and adapted for to study disparity in racial and ethnic groups in America including Asian and Pacific Islander American females. However, its applicability outside America remains uncertain due to diversity in epidemiology and risk factors of breast cancer in populations especially in Asian females. We sought to evaluate the performance of the GM to predict breast cancer risk in Asian countries. Material and methods This study identified articles published from 2010 by searching PubMed, MEDLINE, Scopus, Web of Science, Google Scholar and gray literature. The initial search terms were breast cancer, mammary, carcinoma, tumor, neoplasm, risk assessment tool, BCRAT, breast cancer prediction, Gail model, Asia, and Asian. Results The search yielded 20 articles, with 7 articles addressing the AUC and/or the expected (E) to observed (O) ratio of predicted breast cancer risk, representing the accuracy of the GM in the Asian population. One publication reported the sensitivity and specificity but no AUC. None of the studies were accepted as the standard for reporting prognostic models. Several studies reported good prognostic testing and likely developed a new model modifying the items in the instrument. Conclusion The results are not strong enough to develop breast cancer risk in the setting of Asian countries. Involving the breast cancer risk of the Asian population in developing a prognostic model with good statistical understanding is particularly important and can reduce flawed or biased models. Identifying the best methods to achieve well-suited prognostic models in the Asian population should be a priority.
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Affiliation(s)
- Solikhah Solikhah
- Faculty of Public Health, Universitas Ahmad Dahlan, Yogyakarta, 55166, Indonesia.,Dynamic Social Study Center, Universitas Ahmad Dahlan, Yogyakarta, 55166, Indonesia
| | - Sitti Nurdjannah
- Faculty of Public Health, Universitas Ahmad Dahlan, Yogyakarta, 55166, Indonesia
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Ball S, Arevalo M, Juarez E, Payne JD, Jones C. Breast cancer chemoprevention: An update on current practice and opportunities for primary care physicians. Prev Med 2019; 129:105834. [PMID: 31494144 DOI: 10.1016/j.ypmed.2019.105834] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2019] [Revised: 09/01/2019] [Accepted: 09/05/2019] [Indexed: 12/15/2022]
Abstract
Several risk assessment models have been validated for the estimation of risk of breast cancer in women. Chemoprevention through hormonal therapy is an effective way to reduce the incidence of breast cancer in women with high risk. Selective estrogen receptor modulators, tamoxifen and raloxifene, are approved for this indication by the United States Food and Drug Administration, and aromatase inhibitors have also shown promise in recent studies. These medications are generally well tolerated, except for reported increased rates of fractures and venous thromboembolic events. Despite strong recommendations from several regulatory bodies, advocacy for chemoprevention has been inadequate in practice, more so among the primary care physicians. Studies have identified several barriers in physicians, patients, and the system, contributing to this problem. Lack of knowledge about risk assessment models and chemoprevention options preclude physicians from prescribing these medications with confidence. Fear of potential adverse events, confusion regarding the purpose of the therapy, and need for continued adherence for five years are among the principal reasons for reduced chemoprevention uptake and early discontinuation among patients. Multifaceted interventions directed at education and training of health care professionals, proper counseling of women at high risk, and promotion of the development of improved medications might help ensure better chemoprevention uptake in the target population.
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Affiliation(s)
- Somedeb Ball
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
| | - Meily Arevalo
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Edna Juarez
- Department of Internal Medicine, Memorial Medical Center, Las Cruces, NM, USA
| | - J Drew Payne
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Catherine Jones
- Division of Hematology and Medical Oncology, Texas Tech University Health Sciences Center, Lubbock, TX, USA
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Glynn RJ, Colditz GA, Tamimi RM, Chen WY, Hankinson SE, Willett WW, Rosner B. Comparison of Questionnaire-Based Breast Cancer Prediction Models in the Nurses' Health Study. Cancer Epidemiol Biomarkers Prev 2019; 28:1187-1194. [PMID: 31015199 DOI: 10.1158/1055-9965.epi-18-1039] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Revised: 12/06/2018] [Accepted: 04/11/2019] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND The Gail model and the model developed by Tyrer and Cuzick are two questionnaire-based approaches with demonstrated ability to predict development of breast cancer in a general population. METHODS We compared calibration, discrimination, and net reclassification of these models, using data from questionnaires sent every 2 years to 76,922 participants in the Nurses' Health Study between 1980 and 2006, with 4,384 incident invasive breast cancers identified by 2008 (median follow-up, 24 years; range, 1-28 years). In a random one third sample of women, we also compared the performance of these models with predictions from the Rosner-Colditz model estimated from the remaining participants. RESULTS Both the Gail and Tyrer-Cuzick models showed evidence of miscalibration (Hosmer-Lemeshow P < 0.001 for each) with notable (P < 0.01) overprediction in higher-risk women (2-year risk above about 1%) and underprediction in lower-risk women (risk below about 0.25%). The Tyrer-Cuzick model had slightly higher C-statistics both overall (P < 0.001) and in age-specific comparisons than the Gail model (overall C, 0.63 for Tyrer-Cuzick vs. 0.61 for the Gail model). Evaluation of net reclassification did not favor either model. In the one third sample, the Rosner-Colditz model had better calibration and discrimination than the other two models. All models had C-statistics <0.60 among women ages ≥70 years. CONCLUSIONS Both the Gail and Tyrer-Cuzick models had some ability to discriminate breast cancer cases and noncases, but have limitations in their model fit. IMPACT Refinements may be needed to questionnaire-based approaches to predict breast cancer in older and higher-risk women.
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Affiliation(s)
- Robert J Glynn
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. .,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.,Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Graham A Colditz
- Alvin J. Siteman Cancer Center and Department of Surgery, Division of Public Health Sciences, School of Medicine, Washington University of St. Louis, St. Louis, Missouri
| | - Rulla M Tamimi
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Wendy Y Chen
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.,Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Susan E Hankinson
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.,Division of Biostatistics and Epidemiology, School of Public Health Sciences, University of Massachusetts, Amherst, Massachusetts
| | - Walter W Willett
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Bernard Rosner
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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Wang X, Huang Y, Li L, Dai H, Song F, Chen K. Assessment of performance of the Gail model for predicting breast cancer risk: a systematic review and meta-analysis with trial sequential analysis. Breast Cancer Res 2018; 20:18. [PMID: 29534738 PMCID: PMC5850919 DOI: 10.1186/s13058-018-0947-5] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 02/26/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The Gail model has been widely used and validated with conflicting results. The current study aims to evaluate the performance of different versions of the Gail model by means of systematic review and meta-analysis with trial sequential analysis (TSA). METHODS Three systematic review and meta-analyses were conducted. Pooled expected-to-observed (E/O) ratio and pooled area under the curve (AUC) were calculated using the DerSimonian and Laird random-effects model. Pooled sensitivity, specificity and diagnostic odds ratio were evaluated by bivariate mixed-effects model. TSA was also conducted to determine whether the evidence was sufficient and conclusive. RESULTS Gail model 1 accurately predicted breast cancer risk in American women (pooled E/O = 1.03; 95% CI 0.76-1.40). The pooled E/O ratios of Caucasian-American Gail model 2 in American, European and Asian women were 0.98 (95% CI 0.91-1.06), 1.07 (95% CI 0.66-1.74) and 2.29 (95% CI 1.95-2.68), respectively. Additionally, Asian-American Gail model 2 overestimated the risk for Asian women about two times (pooled E/O = 1.82; 95% CI 1.31-2.51). TSA showed that evidence in Asian women was sufficient; nonetheless, the results in American and European women need further verification. The pooled AUCs for Gail model 1 in American and European women and Asian females were 0.55 (95% CI 0.53-0.56) and 0.75 (95% CI 0.63-0.88), respectively, and the pooled AUCs of Caucasian-American Gail model 2 for American, Asian and European females were 0.61 (95% CI 0.59-0.63), 0.55 (95% CI 0.52-0.58) and 0.58 (95% CI 0.55-0.62), respectively. The pooled sensitivity, specificity and diagnostic odds ratio of Gail model 1 were 0.63 (95% CI 0.27-0.89), 0.91 (95% CI 0.87-0.94) and 17.38 (95% CI 2.66-113.70), respectively, and the corresponding indexes of Gail model 2 were 0.35 (95% CI 0.17-0.59), 0.86 (95% CI 0.76-0.92) and 3.38 (95% CI 1.40-8.17), respectively. CONCLUSIONS The Gail model was more accurate in predicting the incidence of breast cancer in American and European females, while far less useful for individual-level risk prediction. Moreover, the Gail model may overestimate the risk in Asian women and the results were further validated by TSA, which is an addition to the three previous systematic review and meta-analyses. TRIAL REGISTRATION PROSPERO CRD42016047215 .
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Affiliation(s)
- Xin Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhu Xi Road, Tiyuan Bei, Hexi District, Tianjin, 300060 People’s Republic of China
| | - Yubei Huang
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhu Xi Road, Tiyuan Bei, Hexi District, Tianjin, 300060 People’s Republic of China
| | - Lian Li
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhu Xi Road, Tiyuan Bei, Hexi District, Tianjin, 300060 People’s Republic of China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhu Xi Road, Tiyuan Bei, Hexi District, Tianjin, 300060 People’s Republic of China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhu Xi Road, Tiyuan Bei, Hexi District, Tianjin, 300060 People’s Republic of China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Huanhu Xi Road, Tiyuan Bei, Hexi District, Tianjin, 300060 People’s Republic of China
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Mlikotic R, Parker B, Rajapakshe R. Assessing the Effects of Participant Preference and Demographics in the Usage of Web-based Survey Questionnaires by Women Attending Screening Mammography in British Columbia. J Med Internet Res 2016; 18:e70. [PMID: 27005707 PMCID: PMC4822030 DOI: 10.2196/jmir.5068] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Revised: 11/29/2015] [Accepted: 01/07/2016] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Increased usage of Internet applications has allowed for the collection of patient reported outcomes (PROs) and other health data through Web-based communication and questionnaires. While these Web platforms allow for increased speed and scope of communication delivery, there are certain limitations associated with this technology, as survey mode preferences vary across demographic groups. OBJECTIVE To investigate the impact of demographic factors and participant preferences on the use of a Web-based questionnaire in comparison with more traditional methods (mail and phone) for women participating in screening mammography in British Columbia, Canada. METHODS A sample of women attending the Screening Mammography Program of British Columbia (SMPBC) participated in a breast cancer risk assessment project. The study questionnaire was administered through one of three modes (ie, telephone, mail, or website platform). Survey mode preferences and actual methods of response were analyzed for participants recruited from Victoria General Hospital. Both univariate and multivariate analyses were used to investigate the association of demographic factors (ie, age, education level, and ethnicity) with certain survey response types. RESULTS A total of 1192 women successfully completed the study questionnaire at Victoria General Hospital. Mail was stated as the most preferred survey mode (509/1192, 42.70%), followed by website platform (422/1192, 35.40%), and telephone (147/1192, 12.33%). Over 80% (955/1192) of participants completed the questionnaire in the mode previously specified as their most preferred; mail was the most common method of response (688/1192, 57.72%). Mail was also the most preferred type of questionnaire response method when participants responded in a mode other than their original preference. The average age of participants who responded via the Web-based platform (age 52.9, 95% confidence interval [CI] 52.1-53.7) was significantly lower than those who used mail and telephone methods (age 55.9, 95% CI 55.2-56.5; P<.001); each decade of increased age was associated with a 0.97-fold decrease in the odds of using the website platform (P<.001). Web-based participation was more likely for those who completed higher levels of education; each interval increase leading to a 1.83 increase in the odds of website platform usage (P<.001). Ethnicity was not shown to play a role in participant preference for the website platform (P=.96). CONCLUSIONS It is beneficial to consider participant survey mode preference when planning to collect PROs and other patient health data. Younger participants and those of higher education level were more likely to use the website platform questionnaire; Web-based participation failed to vary across ethnic group. Because mail questionnaires were still the most preferred survey mode, it will be important to employ strategies, such as user-friendly design and Web-based support, to ensure that the patient feedback being collected is representative of the population being served.
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Affiliation(s)
- Rebecca Mlikotic
- British Columbia Cancer Agency, Sindi Ahluwalia Hawkins Centre for the Southern Interior, Kelowna, BC, Canada.
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10
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Evans DG, Howell A. Can the breast screening appointment be used to provide risk assessment and prevention advice? Breast Cancer Res 2015; 17:84. [PMID: 26155950 PMCID: PMC4496847 DOI: 10.1186/s13058-015-0595-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Breast cancer risk is continuing to increase across all societies with rates in countries with traditionally lower risks catching up with the higher rates in the Western world. Although cure rates from breast cancer have continued to improve such that absolute numbers of breast cancer deaths have dropped in many countries despite rising incidence, only some of this can be ascribed to screening with mammography, and debates over the true value of population-based screening continue. As such, enthusiasm for risk-stratified screening is gaining momentum. Guidelines in a number of countries already suggest more frequent screening in certain higher-risk (particularly, familial) groups, but this could be extended to assessing risks across the population. A number of studies have assessed breast cancer risk by using risk algorithms such as the Gail model, Tyrer-Cuzick, and BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm), but the real questions are when and where such an assessment should take place. Emerging evidence from the PROCAS (Predicting Risk Of Cancer At Screening) study is showing not only that it is feasible to undertake risk assessment at the population screening appointment but that this assessment could allow reduction of screening in lower-risk groups in many countries to 3-yearly screening by using mammographic density-adjusted breast cancer risk.
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Affiliation(s)
- D Gareth Evans
- Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester NHS Trust, Southmoor Road, Wythenshawe, Manchester, M23 9LT, UK. .,Genomic Medicine, Manchester Academic Health Science Centre, University of Manchester, Central Manchester Foundation Trust, St. Mary's Hospital, Oxford Road, Manchester, M13 9WL, UK. .,Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Christie Hospital, Wilmslow Road, Withington, Manchester, M20 4BX, UK.
| | - Anthony Howell
- Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester NHS Trust, Southmoor Road, Wythenshawe, Manchester, M23 9LT, UK.,Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Christie Hospital, Wilmslow Road, Withington, Manchester, M20 4BX, UK
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11
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Battistoni A, Mastromarino V, Volpe M. Reducing Cardiovascular and Cancer Risk: How to Address Global Primary Prevention in Clinical Practice. Clin Cardiol 2015; 38:387-94. [PMID: 25873555 DOI: 10.1002/clc.22394] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2014] [Revised: 01/15/2015] [Accepted: 01/20/2015] [Indexed: 12/11/2022] Open
Abstract
Emerging evidence suggesting the possibility that interventions able to prevent cardiovascular disease (CVD) may also be effective in the prevention of cancer have recently stimulated great interest in the medical community. In particular, data from both experimental and observational studies have demonstrated that aspirin may play a role in preventing different types of cancer. Although the use of aspirin in the secondary prevention of CVD is well established, aspirin in primary prevention is not systematically recommended because the absolute cardiovascular event reduction is similar to the absolute excess in major bleedings. By adding to its cardiovascular prevention benefits, the potential beneficial effect of aspirin in reducing the incidence of mortality and cancer could tip the balance between risks and benefits of aspirin therapy in primary prevention in favor of the latter and broaden the indication for treatment with aspirin in populations at average risk. Prospective and randomized studies are currently investigating the effect of aspirin in prevention of both cancer and CVD; however, clinical efforts at the individual level to promote the use of aspirin in global (or total) primary prevention already could be made on the basis of a balanced evaluation of the benefit/risk ratio.
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Affiliation(s)
- Allegra Battistoni
- Cardiology Department, Clinical and Molecular Medicine Department, Sapienza University of Rome, Rome, Italy
| | - Vittoria Mastromarino
- Cardiology Department, Clinical and Molecular Medicine Department, Sapienza University of Rome, Rome, Italy
| | - Massimo Volpe
- Cardiology Department, Clinical and Molecular Medicine Department, Sapienza University of Rome, Rome, Italy.,IRCCS Neuromed (Volpe), Pozzilli, Italy
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Abstract
PURPOSE OF REVIEW Breast cancer and gynecological cancers impact a significant portion of women each year. Identifying women at high risk is essential for implementation of screening and risk reduction recommendations. Risk assessment for these cancers involves an evaluation of many factors. This review discusses an overview of hereditary breast and gynecological cancers and the process of a cancer genetic risk assessment. RECENT FINDINGS Risk assessment models for breast cancer should be used with caution, especially in populations in which they are not validated. Additionally, the BRCAPRO model may underestimate the likelihood of BRCA mutations in certain populations.The utilization of next-generation sequencing panels is increasing. Benefits and limitations of panel testing are described in the literature. There are currently no guidelines for the use of panel testing; however, some reports of institutional experiences and recommendations are available. SUMMARY Cancer genetic risk assessment is complex, and models developed to estimate risk may not apply to all populations. Identifying genetic factors related to cancer risk is also becoming increasingly complex with the clinical implementation of panel testing. This testing approach should be critically evaluated by healthcare providers. Further research is needed to create evidence-based guidelines for panel testing and management recommendations for moderately penetrant genes.
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Gompel A. How to Prescribe MHT According to the Risk of Breast Cancer. CURRENT OBSTETRICS AND GYNECOLOGY REPORTS 2014. [DOI: 10.1007/s13669-014-0100-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Howell A, Anderson AS, Clarke RB, Duffy SW, Evans DG, Garcia-Closas M, Gescher AJ, Key TJ, Saxton JM, Harvie MN. Risk determination and prevention of breast cancer. Breast Cancer Res 2014; 16:446. [PMID: 25467785 PMCID: PMC4303126 DOI: 10.1186/s13058-014-0446-2] [Citation(s) in RCA: 204] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Breast cancer is an increasing public health problem. Substantial advances have been made in the treatment of breast cancer, but the introduction of methods to predict women at elevated risk and prevent the disease has been less successful. Here, we summarize recent data on newer approaches to risk prediction, available approaches to prevention, how new approaches may be made, and the difficult problem of using what we already know to prevent breast cancer in populations. During 2012, the Breast Cancer Campaign facilitated a series of workshops, each covering a specialty area of breast cancer to identify gaps in our knowledge. The risk-and-prevention panel involved in this exercise was asked to expand and update its report and review recent relevant peer-reviewed literature. The enlarged position paper presented here highlights the key gaps in risk-and-prevention research that were identified, together with recommendations for action. The panel estimated from the relevant literature that potentially 50% of breast cancer could be prevented in the subgroup of women at high and moderate risk of breast cancer by using current chemoprevention (tamoxifen, raloxifene, exemestane, and anastrozole) and that, in all women, lifestyle measures, including weight control, exercise, and moderating alcohol intake, could reduce breast cancer risk by about 30%. Risk may be estimated by standard models potentially with the addition of, for example, mammographic density and appropriate single-nucleotide polymorphisms. This review expands on four areas: (a) the prediction of breast cancer risk, (b) the evidence for the effectiveness of preventive therapy and lifestyle approaches to prevention, (c) how understanding the biology of the breast may lead to new targets for prevention, and (d) a summary of published guidelines for preventive approaches and measures required for their implementation. We hope that efforts to fill these and other gaps will lead to considerable advances in our efforts to predict risk and prevent breast cancer over the next 10 years.
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Affiliation(s)
- Anthony Howell
- Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester, Southmoor Road, Wythenshawe, M29 9LT Manchester, UK
- The Christie, NHS Foundation Trust, Wilmslow Road, Manchester, M20 2QJ UK
- Breakthrough Breast Cancer Research Unit, Institute of Cancer Sciences, University of Manchester, Wilmslow Road, Manchester, M20 2QJ UK
| | - Annie S Anderson
- Centre for Public Health Nutrition Research, Division of Cancer Research, Level 7, University of Dundee, Ninewells Hospital & Medical School, Mailbox 7, George Pirie Way, Dundee, DD1 9SY UK
| | - Robert B Clarke
- Breakthrough Breast Cancer Research Unit, Institute of Cancer Sciences, University of Manchester, Wilmslow Road, Manchester, M20 2QJ UK
| | - Stephen W Duffy
- Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ UK
| | - D Gareth Evans
- Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester, Southmoor Road, Wythenshawe, M29 9LT Manchester, UK
- The Christie, NHS Foundation Trust, Wilmslow Road, Manchester, M20 2QJ UK
- Manchester Centre for Genomic Medicine, The University of Manchester, Manchester Academic Health Science Centre, Central Manchester Foundation Trust, St. Mary’s Hospital, Oxford Road, Manchester, M13 9WL UK
| | - Montserat Garcia-Closas
- Division of Genetics and Epidemiology, Institute of Cancer Research, Cotswold Road, Sutton, SM2 5NG London, UK
| | - Andy J Gescher
- Department of Cancer Studies and Molecular Medicine, University of Leicester, University Road, Leicester, LE2 7LX UK
| | - Timothy J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Roosevelt Drive, Oxford, OX3 7LF UK
| | - John M Saxton
- School of Health Sciences, Faculty of Medicine and Health Sciences, University of East Anglia, University Drive, Norwich, NR4 7TJ UK
| | - Michelle N Harvie
- Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester, Southmoor Road, Wythenshawe, M29 9LT Manchester, UK
- The Christie, NHS Foundation Trust, Wilmslow Road, Manchester, M20 2QJ UK
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