Format

Send to

Choose Destination
Intensive Care Med. 2014 Apr;40(4):513-27. doi: 10.1007/s00134-014-3227-6. Epub 2014 Feb 26.

How to derive and validate clinical prediction models for use in intensive care medicine.

Author information

1
Quality of Care Unit, University Hospital, Grenoble, 38043, France, JLabarere@chu-grenoble.fr.

Erratum in

  • Intensive Care Med. 2014 Jun;40(6):925. Bertrand, Renaud [corrected to Renaud, Bertrand].

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.

PURPOSE:

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.

PMID:
24570265
DOI:
10.1007/s00134-014-3227-6
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center