A note on estimating the Cox-Snell R2 from a reported C statistic (AUROC) to inform sample size calculations for developing a prediction model with a binary outcome

被引:32
|
作者
Riley, Richard D. [1 ]
Van Calster, Ben [2 ,3 ]
Collins, Gary S. [4 ,5 ]
机构
[1] Keele Univ, Ctr Prognosis Res, Sch Med, Keele ST5 5BG, Staffs, England
[2] Katholieke Univ Leuven, Dept Dev & Regenerat, Leuven, Belgium
[3] Leiden Univ, Med Ctr, Dept Biomed Data Sci, Leiden, Netherlands
[4] Univ Oxford, Ctr Stat Med, Nuffield Dept Orthopaed Rheumatol & Musculoskelet, Oxford, England
[5] John Radcliffe Hosp, NIHR Oxford Biomed Res Ctr, Oxford, England
关键词
clinical prediction model; C statistic (AUROC); R squared; sample size;
D O I
10.1002/sim.8806
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In 2019 we published a pair of articles in Statistics in Medicine that describe how to calculate the minimum sample size for developing a multivariable prediction model with a continuous outcome, or with a binary or time-to-event outcome. As for any sample size calculation, the approach requires the user to specify anticipated values for key parameters. In particular, for a prediction model with a binary outcome, the outcome proportion and a conservative estimate for the overall fit of the developed model as measured by the Cox-Snell R-2 (proportion of variance explained) must be specified. This proposal raises the question of how to identify a plausible value for R-2 in advance of model development. Our articles suggest researchers should identify R-2 from closely related models already published in their field. In this letter, we present details on how to derive R-2 using the reported C statistic (AUROC) for such existing prediction models with a binary outcome. The C statistic is commonly reported, and so our approach allows researchers to obtain R-2 for subsequent sample size calculations for new models. Stata and R code is provided, and a small simulation study.
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页码:859 / 864
页数:6
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