Literature DB >> 33283904

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.

Richard D Riley1, Ben Van Calster2,3, Gary S Collins4,5.   

Abstract

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 R2 (proportion of variance explained) must be specified. This proposal raises the question of how to identify a plausible value for R2 in advance of model development. Our articles suggest researchers should identify R2 from closely related models already published in their field. In this letter, we present details on how to derive R2 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 R2 for subsequent sample size calculations for new models. Stata and R code is provided, and a small simulation study.
© 2020 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Keywords:  C statistic (AUROC); R squared; clinical prediction model; sample size

Year:  2020        PMID: 33283904     DOI: 10.1002/sim.8806

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  4 in total

1.  Predicting the risk of active pulmonary tuberculosis in people living with HIV: development and validation of a nomogram.

Authors:  Jinou Chen; Ling Li; Tao Chen; Xing Yang; Haohao Ru; Xia Li; Xinping Yang; Qi Xie; Lin Xu
Journal:  BMC Infect Dis       Date:  2022-04-19       Impact factor: 3.667

2.  Development of a Clinical Risk Score for Prediction of Life-Threatening Arrhythmia Events in Patients with ST Elevated Acute Coronary Syndrome after Primary Percutaneous Coronary Intervention.

Authors:  Thanutorn Wongthida; Lalita Lumkul; Jayanton Patumanond; Wattana Wongtheptian; Dilok Piyayotai; Phichayut Phinyo
Journal:  Int J Environ Res Public Health       Date:  2022-02-10       Impact factor: 3.390

3.  Developing clinical prediction models when adhering to minimum sample size recommendations: The importance of quantifying bootstrap variability in tuning parameters and predictive performance.

Authors:  Glen P Martin; Richard D Riley; Gary S Collins; Matthew Sperrin
Journal:  Stat Methods Med Res       Date:  2021-10-08       Impact factor: 3.021

4.  Long-term cardiovascular risk prediction in the emergency department: a mixed-methods study protocol.

Authors:  Charles Reynard; Brian McMillan; Anisa Jafar; Anthony Heagerty; Glen Philip Martin; Evangelos Kontopantelis; Richard Body
Journal:  BMJ Open       Date:  2022-04-08       Impact factor: 2.692

  4 in total

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