scholarly journals Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5194
Author(s):  
Sherly X. Li ◽  
Roger L. Milne ◽  
Tú Nguyen-Dumont ◽  
Dallas R. English ◽  
Graham G. Giles ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Age Groups ◽  
Risk Scores ◽  
P Value ◽  
Risk Models ◽  
Discriminatory Accuracy ◽  
Incident Cases

Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50–65 years and unaffected at commencement of follow-up two (conducted in 2003–2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50–54, 55–59, 60–65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56–0.62) and IBIS (0.57, 95% CI 0.54–0.61) than the other models (p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum.

scholarly journals Risk models for breast cancer

2019 ◽  
Vol 15 (4) ◽  
pp. 503-510
Author(s):  
T. V. Pyatchanina ◽  
A. N. Ohorodnyk
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Scientific Evidence ◽  
Breast Cancer Patients ◽  
Brca1 And Brca2 ◽  
Risk Models ◽  
Brca1 And Brca2 Genes

Scientific evidence indicates the stabilization of indicators of morbidity and mortality from breast cancer in women in Ukraine and the existence of a number of models for predicting the breast cancer risk with the consideration of life style factors, detectable mutations of BRCA1 and BRCA2 genes, family history, as well as predicative and prognostic factors (clinical, molecular-biological) to determine the possible ways of the tumor process and the survival of breast cancer patients.

Endogenous Steroid Hormone Concentrations and Risk of Breast Cancer: Does the Association Vary by a Woman's Predicted Breast Cancer Risk?

2006 ◽  
Vol 24 (12) ◽  
pp. 1823-1830 ◽  
Author(s):  
A. Heather Eliassen ◽  
Stacey A. Missmer ◽  
Shelley S. Tworoger ◽  
Susan E. Hankinson
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Total N ◽  
History Of ◽  
Predicted Risk

PurposeTo examine whether the associations of endogenous estrogens and testosterone with breast cancer risk differ between high- and low-risk women, as determined by the Gail model and the Rosner and Colditz model, and by family history of breast cancer.MethodsWe conducted a prospective nested case-control study within the Nurses' Health Study. From 1989 or 1990 until June 2000, blood samples were collected, 418 breast cancer patient cases were identified, and two controls (total n = 817) were matched to each case. We classified women as high or low risk based on their family history of breast cancer, their 5-year Gail risk score, and their 5-year Rosner and Colditz risk score. Multivariate relative risks (RR) and 95% CI were calculated by unconditional logistic regression, adjusting for matching and breast cancer risk factors.ResultsEstrone sulfate was statistically significantly associated with breast cancer risk among women with low (< 1.66%) and high (≥ 2.52%; 75th percentile) Gail predicted risk (fourth v first quartile RR = 3.6; 95% CI, 1.9 to 7.0; RR = 2.5; 95% CI, 1.2 to 5.1, respectively). Testosterone results were similar across strata of predicted risk, with two times the risk in the fourth (v first) quartile. Estradiol appeared more strongly associated with breast cancer in women with higher predicted risk (RR = 4.5; 95% CI, 2.1 to 9.5) compared with women with lower risk (RR = 2.1; 95% CI, 1.2 to 3.6), but differences were not statistically significant. Results were similar across predicted Rosner and Colditz risk scores.ConclusionThese data suggest that higher levels of endogenous estrogens and testosterone are associated with increased breast cancer risk, regardless of predicted risk or family history of breast cancer.

scholarly journals Polygenic Breast Cancer Risk for Women Veterans in the Million Veteran Program

2021 ◽  
pp. 1178-1191
Author(s):  
Jessica Minnier ◽  
Nallakkandi Rajeevan ◽  
Lina Gao ◽  
Byung Park ◽  
Saiju Pyarajan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Prediction Models ◽  
Assessment Tool ◽  
Cancer Risk Assessment ◽  
Risk Models ◽  
Breast Cancer Risk Assessment ◽  
Incident Cases

PURPOSE Accurate breast cancer (BC) risk assessment allows personalized screening and prevention. Prospective validation of prediction models is required before clinical application. Here, we evaluate clinical- and genetic-based BC prediction models in a prospective cohort of women from the Million Veteran Program. MATERIALS AND METHODS Clinical BC risk prediction models were validated in combination with a genetic polygenic risk score of 313 (PRS313) single-nucleotide polymorphisms in genetic females without prior BC diagnosis (n = 35,130, mean age 49 years) with 30% non-Hispanic African ancestry (AA). Clinical risk models tested were Breast and Prostate Cancer Cohort Consortium, literature review, and Breast Cancer Risk Assessment Tool, and implemented with or without PRS313. Prediction accuracy and association with incident breast cancer was evaluated with area under the receiver operating characteristic curve (AUC), hazard ratios, and proportion with high absolute lifetime risk. RESULTS Three hundred thirty-eight participants developed incident breast cancers with a median follow-up of 3.9 years (2.5 cases/1,000 person-years), with 196 incident cases in women of European ancestry and 112 incident cases in AA women. Individualized Coherent Absolute Risk Estimator-literature review in combination with PRS313 had an AUC of 0.708 (95% CI, 0.659 to 0.758) in women with European or non-African ancestries and 0.625 (0.539 to 0.711) in AA women. Breast Cancer Risk Assessment Tool with PRS313 had an AUC of 0.695 (0.62 to 0.729) in European or non-AA and 0.675 (0.626 to 0.723) in AA women. Incorporation of PRS313 with clinical models improved prediction in European but not in AA women. Models estimated up to 9% of European and 18% of AA women with absolute lifetime risk > 20%. CONCLUSION Clinical and genetic BC risk models predict incident BC in a large prospective multiracial cohort; however, more work is needed to improve genetic risk estimation in AA women.

scholarly journals Potential of polygenic risk scores for improving population estimates of women’s breast cancer genetic risks

2021 ◽  
Author(s):  
Michael Wolfson ◽  
Steve Gribble ◽  
Nora Pashayan ◽  
Douglas F. Easton ◽  
Antonis C. Antoniou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Breast Cancer Incidence ◽  
Population Level ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Risk Algorithm

Abstract Purpose Breast cancer risk has conventionally been assessed using family history (FH) and rare high/moderate penetrance pathogenic variants (PVs), notably in BRCA1/2, and more recently PALB2, CHEK2, and ATM. In addition to these PVs, it is now possible to use increasingly predictive polygenic risk scores (PRS) as well. The comparative population-level predictive capability of these three different indicators of genetic risk for risk stratification is, however, unknown. Methods The Canadian heritable breast cancer risk distribution was estimated using a novel genetic mixing model (GMM). A realistically representative sample of women was synthesized based on empirically observed demographic patterns for appropriately correlated family history, inheritance of rare PVs, PRS, and residual risk from an unknown polygenotype. Risk assessment was simulated using the BOADICEA risk algorithm for 10-year absolute breast cancer incidence, and compared to heritable risks as if the overall polygene, including its measured PRS component, and PV risks were fully known. Results Generally, the PRS was most predictive for identifying women at high risk, while family history was the weakest. Only the PRS identified any women at low risk of breast cancer. Conclusion PRS information would be the most important advance in enabling effective risk stratification for population-wide breast cancer screening.

scholarly journals Disease family history and modification of breast cancer risk in common BRCA2 variants

2008 ◽  
Author(s):  
Ian Seymour ◽  
Silvia Casadei ◽  
Valentina Zampiga ◽  
Simonetta Rosato ◽  
Rita Danesi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Disease Family

scholarly journals Evaluating the Effect of Health Education Intervention on the Health Beliefs and Behaviors of First-Degree Female Relatives of Breast Cancer Patients

2021 ◽  
Author(s):  
Sule Olgun ◽  
Berna Dizer
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Health Education ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Patients ◽  
Health Beliefs ◽  
Breast Cancer Patients ◽  
History Of ◽  
And Behaviors

Abstract Background Breast cancer risk increases by 80% in the presence of BRCA1 and BRCA2 gene mutations in the same family. In particular, a woman whose sister or mother has breast cancer has a 2- to 5-fold higher risk of developing breast cancer compared with other women. For this reason, recommendations should have been made regarding breast cancer prevention and/or early detection for women with first-degree family history of breast cancer. Aim The aim of this study was to evaluate the effect of health education, which was provided to first-degree female relatives of breast cancer patients, on their health beliefs and behaviors. Study Design and Methods The study sample included 50 women with a first-degree relative being treated for breast cancer in the chemotherapy and radiotherapy unit of a university hospital. A one-group pretest-posttest design was used. The pretest consisted of the health belief model scale and a questionnaire regarding the women’s sociodemographic information and breast cancer screening behaviors. After the pretest, the patients received health education regarding breast cancer risk factors and screening methods. The posttest was conducted 3 weeks after the education using the same assessment tools. Results After education, there were statistically significant increases in rates of practicing breast self-examination, having clinical breast examinations, and undergoing breast ultrasound/mammography compared with pretest results. Conclusions Health workers should possess knowledge and experience about breast cancer which will enable them to effectively undertake an educational role, especially for high-risk groups such as women with first-degree family history of breast cancer.

scholarly journals The influence of family history on breast cancer risk in women with biopsy-confirmed benign breast disease

Cancer ◽  
2006 ◽  
Vol 107 (6) ◽  
pp. 1240-1247 ◽  
Author(s):  
Laura C. Collins ◽  
Heather J. Baer ◽  
Rulla M. Tamimi ◽  
James L. Connolly ◽  
Graham A. Colditz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Benign Breast Disease ◽  
Breast Disease
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