title: Key steps and common pitfalls in developing and validating risk models.
abstract: Models for estimating an individual's risk of having or developing a disease are abundant in the medical literature, yet many do not meet the methodological standards that have been set to maximise generalisability and utility. This paper presents an overview of ten steps from the conception of the study to the implementation of the risk model and discusses common pitfalls. We discuss crucial aspects of study design, data collection, model development and performance evaluation, and discuss how to bring the model to clinical practice.
  
  
  
  We present an overview of ten key steps for the development of risk models and discuss common pitfalls.
authors.affiliation: KU Leuven Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven iMinds Medical IT Department, Leuven, Belgium.
authors.forename: L
authors.initials: L
authors.lastname: Wynants
authors.affiliation: Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
authors.forename: G S
authors.initials: GS
authors.lastname: Collins
authors.affiliation: KU Leuven Department of Development and Regeneration, Leuven, Belgium.
authors.forename: B
authors.initials: B
authors.lastname: Van Calster
mesh_terms: D006801:Humans; D015233:Models, Statistical; D015203:Reproducibility of Results; D012107:Research Design; D018570:Risk Assessment / Q000379:methods*
keywords: Clinical prediction model; logistic regression; model development; model reporting; model validation; risk model