Extending prediction models for use in a new target population with failure time outcomes

Prediction models are often built and evaluated using data from a population that differs from the target population where model-derived predictions are intended to be used in. In this article, we present methods for evaluating model performance in the target population when some observations are right censored. The methods assume that outcome and covariate data are available from a source population used for model development and covariates, but no outcome data, are available from the target population. We evaluate the finite sample performance of the proposed estimators using simulations and apply the methods to transport a prediction model built using data from a lung cancer screening trial to a nationally representative population of participants eligible for lung cancer screening.

Automated summary

This article presents methods for evaluating the performance of prediction models in the target population, taking into account right censored observations. The methods utilize outcome and covariate data from a source population for model development and apply them to a target population where only covariate data is available. The proposed estimators are evaluated using simulations and applied to a lung cancer screening trial for a nationally representative population.