Validation of a breast cancer risk prediction model developed for Black women.

BACKGROUND: A breast cancer risk prediction model for black women, developed from data in the Women's Contraceptive and Reproductive Experiences (CARE) study, has been validated in women aged 50 years or older but not among younger women or for specific breast cancer subtypes. METHODS: We assessed calibration and discrimination of the CARE model in the Black Women's Health Study (BWHS) with data from 45 942 women aged 30 to 69 years at baseline. RESULTS: During a mean follow-up of 9.5 years, we identified 852 invasive breast cancers. The CARE model predicted 749.6 breast cancers, yielding an expected-to-observed (E/O) ratio of 0.88 (95% confidence interval [CI] = 0.82 to 0.94). The E/O ratio did not appreciably differ between women aged less than 50 years and those aged 50 years or older. The model underpredicted risk to the greatest degree among women aged 25 years or older at birth of first child (E/O = 0.71, 95% CI = 0.63 to 0.81); the model was well calibrated among women aged less than 25 years at birth of first child. The prevalence of later age at birth of first child was higher in the BWHS than in the CARE study, and breast cancer incidence was higher in the BWHS compared with national rates used in the CARE model. With respect to discriminatory accuracy, the concordance statistic was 0.57 (95% CI = 0.55 to 0.59) for breast cancer overall, 0.59 (95% CI = 0.57 to 0.61) for estrogen receptor (ER)-positive breast cancer, and 0.54 (95% CI = 0.50 to 0.57) for ER-negative breast cancer. CONCLUSIONS: The CARE model underpredicted breast cancer risk in the BWHS, at least in part because of older age at first birth in this cohort, which led to higher breast cancer incidence rates. Our results suggest that inclusion of age at first birth may improve model performance. Discriminatory accuracy was modest and worse for ER-negative breast cancer.

Duke Scholars

Author Michael J Pencina Biostatistics & Bioinformatics, Division of Biostatistics