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

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

220 Citations (Scopus)
100 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)214-226
Number of pages13
JournalStatistics in Medicine
Volume35
Issue number2
DOIs
Publication statusPublished - 30 Jan 2016
Externally publishedYes

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