A combined clinical and genetic model for predicting risk of ovarian cancer

ABSTRACT: Objective Women with a family history of ovarian cancer or a pathogenic or likely pathogenic gene variant are at high risk of the disease, but very few women have these risk factors. We assessed whether a combined polygenic and clinical risk score could predict risk of ovarian cancer in population-based women who would otherwise be considered as being at average risk.

Methods

We used the UK Biobank to conduct a prospective cohort study assessing the performance of 10-year ovarian cancer risks based on a polygenic risk score, a clinical risk score and a combined risk score. We used Cox regression to assess association, Harrell’s C-index to assess discrimination and Poisson regression to assess calibration.

Results

The combined risk model performed best and problems with ca

SUBMITTER: Dite G 

PROVIDER: S-EPMC9746333 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature