Weighted metrics are required when evaluating the performance of prediction models in nested case-control studies.

ABSTRACT:

Background

Nested case-control (NCC) designs are efficient for developing and validating prediction models that use expensive or difficult-to-obtain predictors, especially when the outcome is rare. Previous research has focused on how to develop prediction models in this sampling design, but little attention has been given to model validation in this context. We therefore aimed to systematically characterize the key elements for the correct evaluation of the performance of prediction models in NCC data.

Methods

We proposed how to correctly evaluate prediction models in NCC data, by adjusting performance metrics with sampling weights to account for the NCC sampling. We included in this study the C-index, threshold-based metrics, Observed-to-expected events ratio (O/E ratio),

SUBMITTER: Rentroia-Pacheco B 

PROVIDER: S-EPMC11533296 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature