4.6 Review

Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review

Journal

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/jamia/ocac002

Keywords

clinical prediction model; electronic health record; external validation; machine learning; clinical decision support

Funding

  1. European Health Data & Evidence Network (EHDEN) project
  2. Innovative Medicines Initiative 2 Joint Undertaking (JU) [806968]
  3. European Union
  4. EFPIA

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This systematic review examines the conduct and reporting of clinical prediction model development and validation. The study found that there has been limited improvement over time in terms of reporting the necessary information for external validation. The findings highlight the urgent need for improvement in reporting to increase the adoption of developed models in clinical practice.
Objectives This systematic review aims to provide further insights into the conduct and reporting of clinical prediction model development and validation over time. We focus on assessing the reporting of information necessary to enable external validation by other investigators. Materials and Methods We searched Embase, Medline, Web-of-Science, Cochrane Library, and Google Scholar to identify studies that developed 1 or more multivariable prognostic prediction models using electronic health record (EHR) data published in the period 2009-2019. Results We identified 422 studies that developed a total of 579 clinical prediction models using EHR data. We observed a steep increase over the years in the number of developed models. The percentage of models externally validated in the same paper remained at around 10%. Throughout 2009-2019, for both the target population and the outcome definitions, code lists were provided for less than 20% of the models. For about half of the models that were developed using regression analysis, the final model was not completely presented. Discussion Overall, we observed limited improvement over time in the conduct and reporting of clinical prediction model development and validation. In particular, the prediction problem definition was often not clearly reported, and the final model was often not completely presented. Conclusion Improvement in the reporting of information necessary to enable external validation by other investigators is still urgently needed to increase clinical adoption of developed models.

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