BMJ Medicine (Jul 2023)

Transparent reporting of adaptive clinical trials using concurrently randomised cohorts

  • ,
  • Mark Jones,
  • David Price,
  • Jason Roberts,
  • Joseph John,
  • Tim Spelman,
  • Thomas L Snelling,
  • Vivekanand Jha,
  • Steven Y C Tong,
  • David Paterson,
  • Balasubramanian Venkatesh,
  • Naomi Hammond,
  • James McFadyen,
  • Robert Medcalf,
  • Huyen Tran,
  • Asha Bowen,
  • Sanjeev Chunilal,
  • Megan Rees,
  • Joshua Davis,
  • Justin Denholm,
  • Susan Morpeth,
  • Ian C Marschner,
  • James McGree,
  • James A Totterdell,
  • Robert K Mahar,
  • Bhupendra Basnet,
  • Grace McPhee,
  • Zoe McQuilten,
  • Matthew O’Sullivan,
  • Nanette Trask,
  • Jennifer Curnow,
  • Eileen Merriman,
  • Todd Cooper,
  • Julie Marsh

DOI
https://doi.org/10.1136/bmjmed-2023-000497
Journal volume & issue
Vol. 2, no. 1

Abstract

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Adaptive clinical trials have designs that evolve over time because of changes to treatments or changes to the chance that participants will receive these treatments. These changes might introduce confounding that biases crude comparisons of the treatment arms and makes the results from standard reporting methods difficult to interpret for adaptive trials. To deal with this shortcoming, a reporting framework for adaptive trials was developed based on concurrently randomised cohort reporting. A concurrently randomised cohort is a subgroup of participants who all had the same treatments available and the same chance of receiving these treatments. The reporting of pre-randomisation characteristics and post-randomisation outcomes for each concurrently randomised cohort in the study is recommended. This approach provides a transparent and unbiased display of the degree of baseline balance and the randomised treatment comparisons for adaptive trials. The key concepts, terminology, and recommendations underlying concurrently randomised cohort reporting are presented, and its routine use in adaptive trial reporting is advocated.