TY - JOUR
T1 - Comparative validation of breast cancer risk prediction models and projections for future risk stratification
AU - Choudhury, Parichoy Pal
AU - Wilcox, Amber N.
AU - Brook, Mark N.
AU - Zhang, Yan
AU - Ahearn, Thomas
AU - Orr, Nick
AU - Coulson, Penny
AU - Schoemaker, Minouk J.
AU - Jones, Michael E.
AU - Gail, Mitchell H.
AU - Swerdlow, Anthony J.
AU - Chatterjee, Nilanjan
AU - Garcia-Closas, Montserrat
N1 - Publisher Copyright:
© 2020 Oxford University Press. All rights reserved.
PY - 2021
Y1 - 2021
N2 - 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] ¼ 0.98, 95% confidence interval [CI] ¼ 0.87 to 1.11) for women younger than 50 years, and iCARE-BPC3 (E/O ¼ 1.00, 95% CI ¼ 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.
AB - 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] ¼ 0.98, 95% confidence interval [CI] ¼ 0.87 to 1.11) for women younger than 50 years, and iCARE-BPC3 (E/O ¼ 1.00, 95% CI ¼ 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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U2 - 10.1093/JNCI/DJZ113
DO - 10.1093/JNCI/DJZ113
M3 - Article
C2 - 31165158
AN - SCOPUS:85075023860
SN - 0027-8874
VL - 112
SP - 278
EP - 285
JO - Journal of the National Cancer Institute
JF - Journal of the National Cancer Institute
IS - 3
M1 - DJZ113
ER -