Predicting 10-Year Risk of Pancreatic Cancer Using a Combined Genetic and Clinical Model

利用遗传和临床联合模型预测胰腺癌10年风险

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Abstract

BACKGROUND AND AIMS: Pancreatic cancer has the poorest 5-year survival rate of any major solid tumor, but when diagnosed at an early stage, survival rates improve. Population screening is impractical because pancreatic cancer is rare with a lifetime risk of 1.7%, but accurate risk stratification in the general population could enable health care providers to focus early detection strategies to at-risk individuals. Here, we validate a combined risk prediction model that integrates a polygenic risk score and a clinical risk model. METHODS: Using the UK Biobank, we conducted a prospective cohort study assessing 10-year pancreatic cancer risks based on a polygenic risk score, a clinical risk score, and a combined risk score. We assessed the association, discrimination, calibration, cumulative hazards, and standardized incidence ratios compared to population incidence rates for the risk scores. We also conducted net reclassification analyses. RESULTS: While all of the risk scores discriminated well between affected and unaffected participants, the combined risk score - with a Harrell's C-index of 0.714 (95% confidence interval [CI] = 0.698, 0.730) - discriminated better than both the polygenic risk score (P = .001) and the clinical risk score (P = .02). In terms of calibration, there was no problem with dispersion for the combined risk score (β = 0.952, 95% CI = 0.865-1.039, P = .3) and overall there was a small overestimation of risk (α = -0.089, 95% CI = -0.156 to -0.021, P = .009). Participants in the top decile of 10-year risk were at 1.413 (95% CI = 1.242-1.607) times population risk. CONCLUSION: The combined risk score was able to identify individuals at substantially increased risk of pancreatic cancer and to whom targeted screening could be useful.

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