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Outcome-adaptive randomization for a delayed outcome with a short-term predictor: imputation-based designs.

Mi-Ok Kim1, Chunyan Liu, Feifang Hu

  • 1Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, U.S.A.; Department of Pediatrics, University of Cincinnati, Cincinnati, Ohio, U.S.A.

Statistics in Medicine
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Summary

Outcome-adaptive randomization faces challenges with delayed outcomes. This study proposes outcome imputation to reliably handle delays in pediatric ulcerative colitis trials, improving finite sample performance.

Keywords:
delayed outcomedoubly adaptive biased coin designimputationoutcome adaptive randomization

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Pediatric Gastroenterology

Background:

  • Delayed outcomes pose challenges for outcome-adaptive randomization (OAR) in clinical trials.
  • A lag exists between patient accrual and outcome availability, impacting OAR analysis.
  • Pediatric ulcerative colitis trials often involve delayed outcome variables.

Purpose of the Study:

  • To address the challenge of delayed outcomes in OAR by utilizing short-term predictors.
  • To propose and evaluate an imputation method for delayed outcomes within OAR designs.
  • To apply and assess the doubly adaptive biased coin design (DBCD) with imputation in a pediatric ulcerative colitis trial context.

Main Methods:

  • Treating delayed outcomes as missing data and employing imputation techniques.
  • Applying the imputation approach to the doubly adaptive biased coin design (DBCD).
  • Conducting theoretical analyses and empirical simulations under various accrual rates and predictor correlations.

Main Results:

  • Theoretical results suggest that under certain conditions, delays are asymptotically ignorable even with non-homogeneous delay distributions.
  • Empirical studies demonstrate that imputation-based DBCD designs offer improved reliability and reduced root mean square errors in finite samples.
  • The performance of imputation-based DBCD is robust across different strengths of correlation between short-term predictors and delayed outcomes.

Conclusions:

  • Imputation of delayed outcomes is a reliable strategy for enhancing the performance of OAR, particularly the DBCD, in finite samples.
  • The proposed imputation method effectively mitigates the impact of outcome delays in adaptive clinical trial designs.
  • This approach holds significant promise for improving the efficiency and accuracy of pediatric ulcerative colitis trials with delayed outcomes.