Genetics, primary care records and lifestyle factors for short-term dynamic risk prediction of colorectal cancer: Prospective study of asymptomatic and symptomatic UK Biobank participants

Abstract

Objectives To quantify the contributions of polygenic scores, primary care records (presenting symptoms, medical history and common blood tests) and lifestyle factors, for short-term risk prediction of colorectal cancer (CRC) in general and symptomatic individuals. Methods and analysis This prospective cohort study used data from the UK Biobank with follow-up until 2018. It included 160 507 participants with linked primary care records and a subcohort of 42 782 participants with recent CRC-related symptoms. The outcome was the first-recorded CRC diagnosis within 2 years. Dynamic risk models with time-varying predictors were derived using a super-landmark framework. Model discrimination was assessed through Harrel's C-index, and predictor contributions to model discrimination were evaluated using inclusion-order-agnostic Shapley values. Results C-indices (95% CIs) were 0.73 (0.72 to 0.73) and 0.69 (0.68 to 0.70) for the general and symptomatic participants, respectively. Shapley contributions to model discrimination (95% CIs) were core predictors (eg, age, sex) 33% (25% to 42%) (symptomatic: 34% (9% to 75%)), polygenic scores 16% (8% to 26%) (8% (-21% to 35%)), primary care blood tests 32% (19% to 43%) (41% (16% to 73%)), medical history 11% (4% to 17%) (9% (-25% to 37%)), lifestyle factors 6% (0% to 11%) (-5% (-32% to 13.4%)) and symptoms 3% (-2% to 7%) (13% (-19% to 41%)). Conclusions Polygenic scores contribute substantially to short-term risk prediction for CRC in both general and symptomatic populations; however, the contribution of information in primary care records (including presenting symptoms, medical history and common blood tests) is greater. Lifestyle factors not routinely collected in primary care contribute minimally.