Abstract
INTRODUCTION: Polygenic risk scores combined to clinical parameters provide promising avenues for breast cancer risk prediction. We evaluated the performance of the Breast Cancer Screening Consortium (BCSC) and the MammoRisk (MR) with and without 313-variant polygenic risk score (PRS313) in the UK Biobank cohort.</p>
METHODS: We used data from female participants enrolled in the UK Biobank cohort to assess model calibration and discrimination of BCSC and MR with and without PRS313. Mammographic density data were not available, therefore, the four predicted risks were averaged with a weight corresponding to their frequencies in the population. The primary endpoint was the diagnosis of invasive breast cancer within 5 years among individuals of European ancestry. We also explored the performance parameters of the risk models among individuals of non-European ancestry.</p>
RESULTS: Adding PRS313 improved the discriminative performance for both BCSC and MR scores across ancestry groups. Among participants of European ancestry, time-dependent area under the receiver operating characteristic curve (tdAUROC) increased by + 0.083 and + 0.084, respectively, reaching 0.639 and 0.641. Among participants of non-European ancestry, smaller improvement were observed (tdAUROC = +0.033 and +0.032, respectively) to tdAUROC of 0.610 and 0.609. Calibration improvement was limited to participants from European ancestry, with integrated calibration index (ICI) decreasing by 0.00005 and 0.00027, to reach 0.00088 and 0.00078, respectively.</p>
CONCLUSIONS: Our findings support the potential of integrating PRS with clinical risk models to enhance breast cancer risk prediction. The differential contribution of adding PRS313 to the performance of clinical models across ancestries underscores the limitations in the generalizability of current PRS-based screening models for breast cancer.</p>