title: How to derive and validate clinical prediction models for use in intensive care medicine.
abstract: BACKGROUND
  Clinical prediction models are formal combinations of historical, physical examination and laboratory or radiographic test data elements designed to accurately estimate the probability that a specific illness is present (diagnostic model), will respond to a form of treatment (therapeutic model) or will have a well-defined outcome (prognostic model) in an individual patient. They are derived and validated using empirical data and used to assist physicians in their clinical decision-making that requires a quantitative assessment of diagnostic, therapeutic or prognostic probabilities at the bedside.
  
  
  OBJECTIVE
  To provide intensivists with a comprehensive overview of the empirical development and testing phases that a clinical prediction model must satisfy before its implementation into clinical practice.
  
  
  RESULTS
  The development of a clinical prediction model encompasses three consecutive phases, namely derivation, (external) validation and impact analysis. The derivation phase consists of building a multivariable model, estimating its apparent predictive performance in terms of both calibration and discrimination, and assessing the potential for statistical over-fitting using internal validation techniques (i.e. split-sampling, cross-validation or bootstrapping). External validation consists of testing the predictive performance of a model by assessing its calibration and discrimination in different but plausibly related patients. Impact analysis involves comparative research [i.e. (cluster) randomized trials] to determine whether clinical use of a prediction model affects physician practices, patient outcomes or the cost of healthcare delivery.
  
  
  CONCLUSIONS
  This narrative review introduces a checklist of 19 items designed to help intensivists develop and transparently report valid clinical prediction models.
authors.affiliation: Quality of Care Unit, University Hospital, Grenoble, 38043, France, JLabarere@chu-grenoble.fr.
authors.forename: José
authors.initials: J
authors.lastname: Labarère
authors.forename: Bertrand
authors.initials: B
authors.lastname: Renaud
authors.forename: Renaud
authors.initials: R
authors.lastname: Bertrand
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Fine
mesh_terms: D057189:Checklist; D003422:Critical Care / Q000379:methods*; D005544:Forecasting; D006801:Humans; D008962:Models, Theoretical; D012720:Severity of Illness Index