Development and validation of a risk prediction model for incident liver cancer.

ABSTRACT:

Objective

We aimed to develop and validate a risk prediction model for liver cancer based on routinely available risk factors using the data from UK Biobank prospective cohort study.

Methods

This analysis included 359,489 participants (2,894,807 person-years) without a previous diagnosis of cancer. We used the Fine-Gray regression model to predict the incident risk of liver cancer, accounting for the competing risk of all-cause death. Model discrimination and calibration were validated internally. Decision curve analysis was conducted to quantify the clinical utility of the model. Nomogram was built based on regression coefficients.

Results

Good discrimination performance of the model was observed in both development and validation datasets, with an area under the cur

SUBMITTER: Liu Y 

PROVIDER: S-EPMC9768800 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature