Validation of the PREDICT Breast Version 3.0 Prognostic Tool in US Breast Cancer Patients
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Background
PREDICT Breast v3 is the latest updated prognostication tool, developed from the breast cancer registry of approximately 35,000 women diagnosed between 2000 and 2018 in the United Kingdom. However, its performance in the United States (US) population is unknown. This study aims to validate PREDICT Breast v3 using newly released Surveillance, Epidemiology, and End Results (SEER) outcome data for US breast cancer patients and to address potential health disparities.
Methods
Over 860,000 female patients diagnosed between 2000 and 2018 with primary breast cancer and followed for at least 10 years were selected from the SEER database. Predicted and observed 10- and 15-year breast cancer-specific survival outcomes were compared for the overall cohort, stratified by estrogen receptor (ER) status, and predefined subgroups. Discriminatory accuracy was determined through the area under the receiver-operator curves (AUC).
Results
PREDICT Breast v3 demonstrated good calibration and discrimination for long-term breast cancer-specific mortality. It provided accurate mortality estimates (within a ±10% error range) across the entire US population for 10-year (−8% in ER-positive and 4% in ER-negative patients) and 15-year (−3 % in ER-positive and 5% in ER-negative patients) all-cause mortality, for both ER statuses. The model also showed good performance for 10- and 15-year all-cause mortality across the U.S. population, with AUC of 0.769 and 0.793 for ER-positive breast cancer as well as AUC of 0.738 and 0.746 for ER-negative breast cancer. However, recalibration is needed for specific groups, such as non-Hispanic Asian and non-Hispanic Black patients with ER-negative status.
Conclusions
PREDICT v3 accurately predicts 10- and 15-year overall survival in contemporary US breast cancer patients. Future work should focus on promoting equitable care by addressing disparities that are observed in predictive tools.
