Don't be misled: 3 misconceptions about external validation of clinical prediction models.

Autor: la Roi-Teeuw HM; Department of General Practice and Nursing Science, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands. Electronic address: h.m.teeuw@umcutrecht.nl., van Royen FS; Department of General Practice and Nursing Science, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., de Hond A; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Zahra A; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., de Vries S; Department of Digital Health, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands; Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC, Utrecht, The Netherlands., Bartels R; Department of Digital Health, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands; Department of Data Science and Biostatistics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Carriero AJ; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., van Doorn S; Department of General Practice and Nursing Science, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Dunias ZS; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Kant I; Department of Digital Health, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Leeuwenberg T; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Peters R; Department of Digital Health, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Veerhoek L; Department of Digital Health, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., van Smeden M; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands; Department of Data Science and Biostatistics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands., Luijken K; Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.
Jazyk: angličtina
Zdroj: Journal of clinical epidemiology [J Clin Epidemiol] 2024 Aug; Vol. 172, pp. 111387. Date of Electronic Publication: 2024 May 08.
DOI: 10.1016/j.jclinepi.2024.111387
Abstrakt: Clinical prediction models provide risks of health outcomes that can inform patients and support medical decisions. However, most models never make it to actual implementation in practice. A commonly heard reason for this lack of implementation is that prediction models are often not externally validated. While we generally encourage external validation, we argue that an external validation is often neither sufficient nor required as an essential step before implementation. As such, any available external validation should not be perceived as a license for model implementation. We clarify this argument by discussing 3 common misconceptions about external validation. We argue that there is not one type of recommended validation design, not always a necessity for external validation, and sometimes a need for multiple external validations. The insights from this paper can help readers to consider, design, interpret, and appreciate external validation studies.
Competing Interests: Declaration of competing interest There are no competing interests for any author.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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