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Sample size considerations for the external validation of a multivariable prognostic model: a resampling study.

Gary S Collins1, Emmanuel O Ogundimu1, Douglas G Altman1

  • 1Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Windmill Road, Oxford, OX3 7LD, U.K.

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External validation of prognostic models needs sufficient sample size for accurate performance assessment. A minimum of 100 events, ideally 200 or more, is recommended for reliable external validation studies.

Keywords:
external validationprognostic modelsample size

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Area of Science:

  • Biostatistics
  • Clinical Epidemiology
  • Health Informatics

Background:

  • External validation is crucial for assessing prognostic model generalizability.
  • Sample size requirements for external validation remain poorly understood.
  • Prognostic model performance evaluation relies on independent datasets.

Purpose of the Study:

  • To investigate the impact of sample size on prognostic model external validation.
  • To provide evidence-based guidance on sample size for external validation studies.
  • To determine optimal sample sizes for precise estimation of performance metrics.

Main Methods:

  • Utilized a large real-world dataset.
  • Employed resampling techniques to simulate varying sample sizes.
  • Evaluated six established prognostic models.
  • Focused on performance measures like the c-index, D statistic, and calibration.

Main Results:

  • Sample size significantly impacts the precision and reliability of external validation.
  • A minimum of 100 events is necessary for external validation.
  • An ideal sample size of 200 or more events ensures robust performance estimation.
  • Unbiased estimation of performance metrics is contingent upon adequate sample size.

Conclusions:

  • External validation of prognostic models requires careful consideration of sample size.
  • Investigate sample size requirements before initiating external validation studies.
  • Adhering to recommended event counts (≥100, ideally ≥200) enhances the validity of prognostic model assessments.