Key result
Multi-cancer risk models combining non-genetic and polygenic factors identify ~24% of adults as high risk.
Why the study?
Risk assessment remains largely site-specific despite shared cancer risk factors, and multi-cancer risk prediction could provide a more holistic understanding to improve risk-stratified prevention.
Does a multi-cancer risk prediction model incorporating polygenic risk scores and non-genetic factors accurately stratify cancer risk in a non-Hispanic White population?
Population
Non-Hispanic White population in the PLCO Cancer Screening Trial and a US reference population
Design
Risk model development, prospective validation, and population projection study
Follow-up
10-yr
Authors
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May support risk-stratified screening in non-Hispanic White adults; extends prior models by integrating PRS with non-genetic factors.
Does a multi-cancer risk prediction model incorporating polygenic risk scores and non-genetic factors accurately stratify cancer risk in a non-Hispanic White population?
A multi-cancer risk prediction model combining non-genetic factors and polygenic risk scores provides meaningful risk stratification, identifying nearly a quarter of US adults as having moderate to high 10-year cancer risk.
Norton et al. (2026) studied this question. Multi-cancer risk models combining non-genetic factors and polygenic risk scores achieved 10-year risk AUCs of 0.60 in females and 0.61 in males, identifying ~24% of US adults as high risk.
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