Design, analysis and reporting of multi-arm trials and strategies to address multiple testing

Author:

Odutayo Ayodele12,Gryaznov Dmitry3,Copsey Bethan1,Monk Paul4,Speich Benjamin13,Roberts Corran1,Vadher Karan1,Dutton Peter1,Briel Matthias35ORCID,Hopewell Sally1,Altman Douglas G1,

Affiliation:

1. Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK

2. Applied Health Research Centre, Li Ka Shing Knowledge Institute of St Michael’s Hospital, Toronto, Ontario, Canada

3. Basel Institute for Clinical Epidemiology and Biostatistics, Department of Clinical Research, University of Basel and University Hospital Basel, Basel, Switzerland

4. Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK

5. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada

Abstract

Abstract Background It is unclear how multiple treatment comparisons are managed in the analysis of multi-arm trials, particularly related to reducing type I (false positive) and type II errors (false negative). Methods We conducted a cohort study of clinical-trial protocols that were approved by research ethics committees in the UK, Switzerland, Germany and Canada in 2012. We examined the use of multiple-testing procedures to control the overall type I error rate. We created a decision tool to determine the need for multiple-testing procedures. We compared the result of the decision tool to the analysis plan in the protocol. We also compared the pre-specified analysis plans in trial protocols to their publications. Results Sixty-four protocols for multi-arm trials were identified, of which 50 involved multiple testing. Nine of 50 trials (18%) used a single-step multiple-testing procedures such as a Bonferroni correction and 17 (38%) used an ordered sequence of primary comparisons to control the overall type I error. Based on our decision tool, 45 of 50 protocols (90%) required use of a multiple-testing procedure but only 28 of the 45 (62%) accounted for multiplicity in their analysis or provided a rationale if no multiple-testing procedure was used. We identified 32 protocol–publication pairs, of which 8 planned a global-comparison test and 20 planned a multiple-testing procedure in their trial protocol. However, four of these eight trials (50%) did not use the global-comparison test. Likewise, 3 of the 20 trials (15%) did not perform the multiple-testing procedure in the publication. The sample size of our study was small and we did not have access to statistical-analysis plans for the included trials in our study. Conclusions Strategies to reduce type I and type II errors are inconsistently employed in multi-arm trials. Important analytical differences exist between planned analyses in clinical-trial protocols and subsequent publications, which may suggest selective reporting of analyses.

Funder

Advanced Postdoc.Mobility

Swiss National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

General Medicine,Epidemiology

Reference21 articles.

1. An introduction to multiplicity issues in clinical trials: the what, why, when and how;Li;Int J Epidemiol,2017

2. Reporting of analyses from randomized controlled trials with multiple arms: a systematic review;Baron;BMC Med,2013

3. Adjusting for multiple testing--when and how?;Bender;J Clin Epidemiol,2001

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3