Reporting Standards and Critical Appraisal of Prediction Models

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic


Prediction models have the potential to positively influence clinical decision-making and thus the overall quality of healthcare. The translational gap needs to be bridged between development of complex statistical models requiring multiple predictors and widespread usage in clinical consultation. A recent review found that inadequate quality of reporting of prediction modelling studies could be a contributing factor in slow transition to the clinic. This chapter emphasises the importance of high-quality reporting of modelling studies and the need for critical appraisal to understand the potential issues limiting generalizability of published models. Evidence synthesis (such as systematic reviews and pooled analysis of disparate models) are relatively under-represented in literature, though methodological studies and guidelines are now starting to appear.
Original languageEnglish
Title of host publicationFundamentals of Clinical Data Science
EditorsPieters Kubben, Michel Dumontier, Andre Dekker
Number of pages16
ISBN (Electronic)978-3-319-99713-1
ISBN (Print)978-3-319-99712-4
Publication statusPublished - 2019

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