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Blinded sample size reestimation for negative binomial regression with baseline adjustment.

Antonia Zapf1,2, Thomas Asendorf1, Christoph Anten1

  • 1Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.

Statistics in Medicine
|March 25, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a blinded sample size reestimation (BSSR) method for clinical trials with count data and baseline covariates. The new approach ensures accurate trial power and maintains the type I error rate.

Keywords:
adaptive designcount datacovariatesgeneralized linear modellikelihood ratioprognostic factorssample size reestimation

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Methods

Background:

  • International guidelines recommend including baseline covariates in primary analyses of randomized clinical trials.
  • Sample size calculations should incorporate baseline covariates for appropriate trial power.
  • Blinded sample size reestimation (BSSR) is crucial for adjusting sample size due to uncertainties in initial calculations.

Purpose of the Study:

  • To introduce a novel BSSR approach for clinical trials utilizing count data outcomes with baseline covariates.
  • To provide statistically sound methods for sample size adjustment in trials with count data.
  • To ensure trials maintain adequate power and control type I error rates.

Main Methods:

  • Development of BSSR methods based on Wald and likelihood ratio test statistics for count data.
  • Application of the proposed methods to a clinical trial in epilepsy.
  • Comparison of BSSR procedures using Monte Carlo simulation.

Main Results:

  • The proposed BSSR methods for count data with baseline covariates yield power values close to the target.
  • The BSSR procedures effectively maintain the type I error rate.
  • The methods are validated through simulation studies and a practical example.

Conclusions:

  • The introduced BSSR approach is effective for count data outcomes in clinical trials.
  • This method allows for necessary sample size adjustments while preserving statistical integrity.
  • The findings support the use of BSSR to optimize clinical trial design and analysis for count data.