Comparative Validation of Breast Cancer Risk Prediction Models and Projections for Future Risk Stratification. (4th June 2019)

• Record Type: Journal Article
• Authors: Pal Choudhury, Parichoy; Wilcox, Amber N; Brook, Mark N; Zhang, Yan; Ahearn, Thomas; Orr, Nick; Coulson, Penny; Schoemaker, Minouk J; Jones, Michael E; Gail, Mitchell H; Swerdlow, Anthony J; Chatterjee, Nilanjan; Garcia-Closas, Montserrat
• Is Part Of: Journal of the National Cancer Institute. Volume 112:Number 3(2020)
• Page Start: 278
• Page End: 285
• Publication Date: 2019-06-04
• Subjects: Cancer -- Periodicals; Cancer -- Research -- Periodicals; 616.994
• DOI: 10.1093/jnci/djz113
• Languages: English
• ISSNs: 0027-8874

Abstract

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.