When and how to use data from randomised trials to develop or validate prognostic models
Publication date
2019-05-29
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Abstract
Prediction models have become an integral part of clinical practice, providing information for patients and clinicians and providing support for their shared decision making. The development and validation of prognostic prediction models requires substantial volumes of high quality information on relevant predictors and patient health outcomes. Primary data collection dedicated to prognostic model (development or validation) research could come with substantial time and costs and can be seen as a waste of resources if suitable data are already available. Randomised clinical trials are a source of high quality clinical data with a largely untapped potential for use in further research. This article addresses when and how data from a randomised clinical trial can be used additionally for prognostic model research, and provides guidance for researchers with access to trial data to evaluate the suitability of their data for the development and validation of prognostic prediction models.
Keywords
Clinical Decision-Making, Data Accuracy, Data Collection/methods, Data Interpretation, Statistical, Decision Support Techniques, Humans, Models, Theoretical, Prognosis, Randomized Controlled Trials as Topic/methods, Reproducibility of Results, Journal Article
Citation
Pajouheshnia, R, Groenwold, R H H, Peelen, L M, Reitsma, J B & Moons, K G M 2019, 'When and how to use data from randomised trials to develop or validate prognostic models', The BMJ, vol. 365, l2154. https://doi.org/10.1136/bmj.l2154