A prediction model for metachronous colorectal cancer: development and validation.

ABSTRACT:

Background

Being able to estimate the risk of metachronous disease in a patient with colorectal cancer (CRC) could enable risk-appropriate surveillance. The aim of this study was to develop a risk-prediction model to estimate individual 10-year risk of metachronous disease following a CRC diagnosis.

Methods

A population-based cohort of patients with CRC was recruited soon after diagnosis between 1997 and 2012 from the United States, Canada, and Australia. Cox regression with the least absolute shrinkage and selection operator penalization was used to identify factors that predicted the risk of a new primary CRC diagnosed at least 1 year after the initial CRC diagnosis. Potential predictors included demography, anthropometry, lifestyle factors, comorbidities, personal and fam

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC12505132 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature