Journal article : Letter
Targeted validation: validating clinical prediction models in their intended population and setting
- Abstract:
- Clinical prediction models must be appropriately validated before they can be used. While validation studies are sometimes carefully designed to match an intended population/setting of the model, it is common for validation studies to take place with arbitrary datasets, chosen for convenience rather than relevance. We call estimating how well a model performs within the intended population/setting "targeted validation". Use of this term sharpens the focus on the intended use of a model, which may increase the applicability of developed models, avoid misleading conclusions, and reduce research waste. It also exposes that external validation may not be required when the intended population for the model matches the population used to develop the model; here, a robust internal validation may be sufficient, especially if the development dataset was large.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 800.3KB, Terms of use)
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- Publisher copy:
- 10.1186/s41512-022-00136-8
Authors
- Publisher:
- BioMed Central
- Journal:
- Diagnostic and Prognostic Research More from this journal
- Volume:
- 6
- Issue:
- 1
- Article number:
- 24
- Publication date:
- 2022-12-22
- Acceptance date:
- 2022-11-14
- DOI:
- EISSN:
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2397-7523
- Pmid:
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36550534
- Language:
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English
- Keywords:
- Subtype:
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Letter
- Pubs id:
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1317279
- Local pid:
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pubs:1317279
- Deposit date:
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2024-01-26
Terms of use
- Copyright holder:
- Sperrin et al.
- Copyright date:
- 2022
- Rights statement:
- © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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