How to Develop and Validate Prediction Models for Orthopedic Outcomes

Isabella Zaniletti, Dirk R. Larson, David G. Lewallen, Daniel J. Berry, Hilal Maradit Kremers

Research output: Contribution to journalReview articlepeer-review


Prediction models are common in medicine for predicting outcomes such as mortality, complications, or response to treatment. Despite the growing interest in these models in arthroplasty (and orthopaedics in general), few have been adopted in clinical practice. If robustly built and validated, prediction models can be excellent tools to support surgical decision making. In this paper, we provide an overview of the statistical concepts surrounding prediction models and outline practical steps for prediction model development and validation in arthroplasty research. Please visit the following for a video that explains the highlights of the paper in practical terms.

Original languageEnglish (US)
Pages (from-to)627-633
Number of pages7
JournalJournal of Arthroplasty
Issue number4
StatePublished - Apr 2023


  • arthroplasty
  • machine learning
  • model validation
  • orthopedics
  • predictors
  • risk prediction

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine


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