Correcting for case-mix shift when developing clinical prediction models.

ABSTRACT:

Background

When developing a clinical prediction model (CPM), a case-mix shift could occur in the development dataset where the distribution of individual predictors changes, potentially affecting model performance. This study exploits the case-mix shift that is already observed in the development dataset to address the case-mix shift between the development and deployment phase of a CPM.

Methods

We propose a Membership-based method to correct for case-mix shift in the development phase of CPMs. This method uses a probabilistic similarity metric to re-weight data samples in the source set (before the case-mix shift) to more closely match the target set (after the case-mix shift), assuming the target set reflects the target population. We apply the proposed method in a real-w

SUBMITTER: Elayan H 

PROVIDER: S-EPMC12317593 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature