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Sample size considerations for the external validation of a multivariable prognostic model: a resampling study

Collins, Gary S.; Ogundimu, Emmanuel O.; Altman, Douglas G.

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Authors

Gary S. Collins

Douglas G. Altman



Abstract

After developing a prognostic model, it is essential to evaluate the performance of the model in samples independent from those used to develop the model, which is often referred to as external validation. However, despite its importance, very little is known about the sample size requirements for conducting an external validation. Using a large real data set and resampling methods, we investigate the impact of sample size on the performance of six published prognostic models. Focussing on unbiased and precise estimation of performance measures (e.g. the c-index, D statistic and calibration), we provide guidance on sample size for investigators designing an external validation study. Our study suggests that externally validating a prognostic model requires a minimum of 100 events and ideally 200 (or more) events

Citation

Collins, G. S., Ogundimu, E. O., & Altman, D. G. (2016). Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Statistics in Medicine, 35(2), 214-226. https://doi.org/10.1002/sim.6787

Journal Article Type Article
Acceptance Date Oct 12, 2015
Online Publication Date Nov 9, 2015
Publication Date Jan 30, 2016
Deposit Date Oct 11, 2020
Publicly Available Date Oct 15, 2021
Journal Statistics in Medicine
Print ISSN 0277-6715
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 35
Issue 2
Pages 214-226
DOI https://doi.org/10.1002/sim.6787
Public URL https://durham-repository.worktribe.com/output/1290380

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.





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