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External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb.

External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb. Thumbnail


Abstract

INTRODUCTION: Sample size 'rules-of-thumb' for external validation of clinical prediction models suggest at least 100 events and 100 non-events. Such blanket guidance is imprecise, and not specific to the model or validation setting. We investigate factors affecting precision of model performance estimates upon external validation, and propose a more tailored sample size approach. METHODS: Simulation of logistic regression prediction models to investigate factors associated with precision of performance estimates. Then, explanation and illustration of a simulation-based approach to calculate the minimum sample size required to precisely estimate a model's calibration, discrimination and clinical utility. RESULTS: Precision is affected by the model's linear predictor (LP) distribution, in addition to number of events and total sample size. Sample sizes of 100 (or even 200) events and non-events can give imprecise estimates, especially for calibration. The simulation-based calculation accounts for the LP distribution and (mis)calibration in the validation sample. Application identifies 2430 required participants (531 events) for external validation of a deep vein thrombosis diagnostic model. CONCLUSION: Where researchers can anticipate the distribution of the model's LP (e.g. based on development sample, or a pilot study), a simulation-based approach for calculating sample size for external validation offers more flexibility and reliability than rules-of-thumb.

Citation

(2021). External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb. Journal of Clinical Epidemiology, https://doi.org/10.1016/j.jclinepi.2021.02.011

Acceptance Date Feb 9, 2021
Publication Date Feb 14, 2021
Journal Journal of Clinical Epidemiology
Print ISSN 0895-4356
Publisher Elsevier
DOI https://doi.org/10.1016/j.jclinepi.2021.02.011
Publisher URL https://www.sciencedirect.com/science/article/pii/S0895435621000482?via%3Dihub

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