1. Clinical prediction models in children that use repeated measurements with time-varying covariates: a scoping review.
- Author
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Fung A, Loutet M, Roth DE, Wong E, Gill PJ, Morris SK, and Beyene J
- Subjects
- Humans, Child, Proportional Hazards Models, Time Factors, Child, Preschool, Models, Statistical
- Abstract
Background: Emerging evidence suggests that clinical prediction models that use repeated (time-varying) measurements within each patient may have higher predictive accuracy than models that use patient information from a single measurement., Objective: To determine the breadth of the published literature reporting the development of clinical prediction models in children that use time-varying predictors., Data Sources: MEDLINE, EMBASE and Cochrane databases., Eligibility Criteria: We included studies reporting the development of a multivariable clinical prediction model in children, with or without validation, to predict a repeatedly measured binary or time-to-event outcome and utilizing at least one repeatedly measured predictor., Synthesis Methods: We categorized included studies by the method used to model time-varying predictors., Results: Of 99 clinical prediction model studies that had a repeated measurements data structure, only 27 (27%) used methods that incorporated the repeated measurements as time-varying predictors in a single model. Among these 27 time-varying prediction model studies, we grouped model types into nine categories: time-dependent Cox regression, generalized estimating equations, random effects model, landmark model, joint model, neural network, K-nearest neighbor, support vector machine and tree-based algorithms. Where there was comparison of time-varying models to single measurement models, using time-varying predictors improved predictive accuracy., Conclusions: Various methods have been used to develop time-varying prediction models in children, but there is a paucity of pediatric time-varying models in the literature. Incorporating time-varying covariates in pediatric prediction models may improve predictive accuracy. Future research in pediatric prediction model development should further investigate whether incorporation of time-varying covariates improves predictive accuracy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
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