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External validation, impact assessment and clinical utilization of clinical prediction models: a prospective cohort study
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Laura Cowley,
Eline Rijnhart ,
Kelly Reeve,
Luc J. Smits,
Laure Wynants
Journal of Clinical Epidemiology, Volume: 186, Start page: 111902
Swansea University Author: Laura Cowley
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Copyright: 2025 The Authors. This is an open access article under the CC BY license.
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DOI (Published version): 10.1016/j.jclinepi.2025.111902
Abstract
We aimed to assess paths taken by clinical prediction models (CPM) after development by quantifying external validation, impact assessment, and utilization in clinical practice. We followed a random sample of 109 regression-based CPM development articles published between 1995-2020 by performing a f...
| Published in: | Journal of Clinical Epidemiology |
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| ISSN: | 0895-4356 1878-5921 |
| Published: |
Elsevier BV
2025
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa70067 |
| Abstract: |
We aimed to assess paths taken by clinical prediction models (CPM) after development by quantifying external validation, impact assessment, and utilization in clinical practice. We followed a random sample of 109 regression-based CPM development articles published between 1995-2020 by performing a forward citation search. We estimated five- and ten-year probabilities of validation and impact assessment after development of CPMs using Kaplan-Meier analysis. In addition, we conducted a survey among the authors of the development articles to determine whether the CPMs had been used in clinical settings. Eighteen (17%) CPM development articles reported a CPM that was externally validated after development. Five- and ten-year probabilities of validation were 0.13 (0.06 to 0.19) and 0.16 (0.08 to 0.23), respectively. Only one article had a CPM with impact assessment during follow-up (ten-year probability: 0.01 [0 to 0.04]). Among the 34 (31%) articles with a survey response, 17 (50%) had CPMs that had been used in clinical practice, in a median of 5 sites (IQR: 1-347). Of these models, only 4 (24%) were externally validated, and none had undergone impact assessment. Despite evidence of utilization in clinical settings, few models are externally validated after development, and published impact assessment is scarce. To prevent compromising patient safety, it is crucial to intensify efforts to promote external validation and impact assessment of prediction models. |
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| Keywords: |
Prediction research; clinical prediction models; external validation; impact assessment; clinical utilization |
| College: |
Faculty of Medicine, Health and Life Sciences |
| Start Page: |
111902 |