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BMC Med Res Methodol. 2019 Jul 3;19(1):136. doi: 10.1186/s12874-019-0787-8.

Ideal vs. real: a systematic review on handling covariates in randomized controlled trials.

Author information

1
Department of Preventive Medicine, Biostatistics Collaboration Center, Feinberg School of Medicine, Northwestern University, 680 N Lake Shore Drive, Suite 1400, Chicago, IL, 60611-4402, USA. jody.ciolino@northwestern.edu.
2
AbbVie Inc, North Chicago, IL, USA.
3
AY analytics, Chicago, IL, USA.
4
Department of Population Health, New York University Langone Health, New York, NY, USA.

Abstract

BACKGROUND:

In theory, efficient design of randomized controlled trials (RCTs) involves randomization algorithms that control baseline variable imbalance efficiently, and corresponding analysis involves pre-specified adjustment for baseline covariates. This review sought to explore techniques for handling potentially influential baseline variables in both the design and analysis phase of RCTs.

METHODS:

We searched PubMed for articles indexed "randomized controlled trial", published in the NEJM, JAMA, BMJ, or Lancet for two time periods: 2009 and 2014 (before and after updated CONSORT guidelines). Upon screening (343), 298 articles underwent full review and data abstraction.

RESULTS:

Typical articles reported on superiority (86%), multicenter (92%), two-armed (79%) trials; 81% of trials involved covariates in the allocation and 84% presented adjusted analysis results. The majority reported a stratified block method (69%) of allocation, and of the trials reporting adjusted analyses, 91% were pre-specified. Trials published in 2014 were more likely to report adjusted analyses (87% vs. 79%, p = 0.0100) and more likely to pre-specify adjustment in analyses (95% vs. 85%, p = 0.0045). Studies initiated in later years (2010 or later) were less likely to use an adaptive method of randomization (p = 0.0066; 7% of those beginning in 2010 or later vs. 31% of those starting before 2000) but more likely to report a pre-specified adjusted analysis (p = 0.0029; 97% for those initiated in 2010 or later vs. 69% of those started before 2000).

CONCLUSION:

While optimal reporting procedures and pre-specification of adjusted analyses for RCTs tend to be progressively more prevalent over time, we see the opposite effect on reported use of covariate-adaptive randomization methods.

KEYWORDS:

Allocation; CONSORT; Minimization; Randomization; Stratification

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