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How to develop, validate, and update clinical prediction models using multinomial logistic regression.

Celina K Gehringer1, Glen P Martin2, Ben Van Calster3

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Journal of Clinical Epidemiology
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Summary
This summary is machine-generated.

Multicategory prediction models (MPMs) offer valuable clinical insights for outcomes with multiple categories. This guide details developing, validating, and updating these models using multinomial logistic regression for better healthcare predictions.

Keywords:
CalibrationClinical prediction modelMulticategoryMultinomial logistic regressionPredictionPrognosisSample sizeValidation

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Area of Science:

  • Clinical prediction modeling
  • Multinomial logistic regression
  • Health outcomes research

Background:

  • Multicategory prediction models (MPMs) are underutilized in healthcare despite their utility for outcomes with more than two categories.
  • Methodological complexities may contribute to the limited application of MPMs compared to binary outcome models.
  • Existing guidance on prediction model research can be supplemented for multicategory outcomes.

Purpose of the Study:

  • To provide a comprehensive guide on developing, validating, and updating multicategory prediction models (MPMs).
  • To illustrate the application of multinomial logistic regression for both nominal and ordinal multicategory outcomes.
  • To encourage the use of MPMs in clinical settings for predicting complex health outcomes.

Main Methods:

  • Guidance based on recent methodological literature.
  • Illustration using a validated MPM for rheumatoid arthritis treatment outcomes.
  • Focus on outcome definition, variable selection, model development, and evaluation.

Main Results:

  • The guide covers outcome definition, variable selection, model development, and evaluation (performance, validation, recalibration).
  • Methods for evaluating and interpreting the predictive performance of MPMs are outlined.
  • R code is provided to facilitate model implementation.

Conclusions:

  • MPMs are recommended for clinical settings predicting multicategory outcomes.
  • Future research should address MPM-specific variable selection and external validation sample size criteria.
  • Increased application of MPMs can enhance clinical decision-making for complex health states.