Lessons learnt when accounting for competing events in the external validation of time-to-event prognostic models.

ABSTRACT:

Background

External validation of prognostic models is necessary to assess the accuracy and generalizability of the model to new patients. If models are validated in a setting in which competing events occur, these competing risks should be accounted for when comparing predicted risks to observed outcomes.

Methods

We discuss existing measures of calibration and discrimination that incorporate competing events for time-to-event models. These methods are illustrated using a clinical-data example concerning the prediction of kidney failure in a population with advanced chronic kidney disease (CKD), using the guideline-recommended Kidney Failure Risk Equation (KFRE). The KFRE was developed using Cox regression in a diverse population of CKD patients and has been proposed for use

SUBMITTER: Ramspek CL 

PROVIDER: S-EPMC9082803 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature