Polygenic risk scores to stratify cancer screening should predict mortality not incidence

Population-based cancer screening programs such as mammography or colonscopy generally directed at all healthy individuals in a given age stratum. It has recently been proposed that cancer screening could be restricted to a high-risk subgroup based on polygenic risk scores (PRSs) using panels of single-nucleotide polymorphisms (SNPs). These PRSs were, however, generated to predict cancer incidence rather than cancer mortality and will not necessarily address overdiagnosis, a major problem associated with cancer screening programs. We develop a simple net-benefit framework for evaluating screening approaches that incorporates overdiagnosis. We use this methodology to demonstrate that if a PRS does not differentially discriminate between incident and lethal cancer, restricting screening to a subgroup with high scores will only improve screening outcomes in a small number of scenarios. In contrast, restricting screening to a subgroup defined as high-risk based on a marker that is more strongly predictive of mortality than incidence will often afford greater net benefit than screening all eligible individuals. If PRS-based cancer screening is to be effective, research needs to focus on identifying PRSs associated with cancer mortality, an unchartered and clinically-relevant area of research, with a much higher potential to improve screening outcomes.

Automated summary

The study proposes using polygenic risk scores (PRSs) based on single-nucleotide polymorphisms (SNPs) to determine high-risk subgroups for cancer screening. However, these PRSs only predict cancer incidence and do not address the issue of overdiagnosis. The authors develop a net-benefit framework to evaluate screening strategies, and find that screening based on a marker that predicts cancer mortality rather than incidence can lead to greater net benefits.