Validation of a clinical breast cancer risk assessment tool combining a polygenic score for all ancestries with traditional risk factors

Genet Med. 2024 Jul;26(7):101128. doi: 10.1016/j.gim.2024.101128. Epub 2024 Jun 3.

Abstract

Purpose: We previously described a combined risk score (CRS) that integrates a multiple-ancestry polygenic risk score (MA-PRS) with the Tyrer-Cuzick (TC) model to assess breast cancer (BC) risk. Here, we present a longitudinal validation of CRS in a real-world cohort.

Methods: This study included 130,058 patients referred for hereditary cancer genetic testing and negative for germline pathogenic variants in BC-associated genes. Data were obtained by linking genetic test results to medical claims (median follow-up 12.1 months). CRS calibration was evaluated by the ratio of observed to expected BCs.

Results: Three hundred forty BCs were observed over 148,349 patient-years. CRS was well-calibrated and demonstrated superior calibration compared with TC in high-risk deciles. MA-PRS alone had greater discriminatory accuracy than TC, and CRS had approximately 2-fold greater discriminatory accuracy than MA-PRS or TC. Among those classified as high risk by TC, 32.6% were low risk by CRS, and of those classified as low risk by TC, 4.3% were high risk by CRS. In cases where CRS and TC classifications disagreed, CRS was more accurate in predicting incident BC.

Conclusion: CRS was well-calibrated and significantly improved BC risk stratification. Short-term follow-up suggests that clinical implementation of CRS should improve outcomes for patients of all ancestries through personalized risk-based screening and prevention.

Keywords: Breast cancer; Breast prediction; Longitudinal; Polygenic risk score; Validation.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Breast Neoplasms* / diagnosis
  • Breast Neoplasms* / genetics
  • Female
  • Genetic Predisposition to Disease*
  • Genetic Testing* / methods
  • Genetic Testing* / standards
  • Humans
  • Middle Aged
  • Multifactorial Inheritance* / genetics
  • Risk Assessment / methods
  • Risk Factors