BACKGROUND

Opinions and practices vary around the issue of performing multiple statistical tests in randomised controlled trials (RCTs). We carried out a study to collate information about opinions and practices using a methodological rapid review and a survey, specifically of publicly funded pragmatic RCTs that are not seeking marketing authorisation. The aim was to identify the circumstances under which researchers would make a statistical adjustment for multiplicity.

METHODS

A review was performed extracting information from articles reporting primary analyses of pragmatic RCTs in one of seven high quality medical journals, in January to June (inclusive) 2018. A survey (Survey Monkey) eliciting opinions and practices around multiplicity was distributed to the 47 registered clinical trials units (CTUs) in the UK.

RESULTS

One hundred and thirty-eight RCTs were included in the review, and survey responses were received from 27/47 (57%) CTUs. Both the review and survey indicated that adjusting for multiplicity was considered most important for multiple treatment comparisons; adjustment was performed for 11/23 (48%) published trials, and 24/27 (89%) CTU statisticians reported they would consider adjustment. Opinions and practices varied around adjustment for multiplicity arising from multiple primary outcomes and interim analyses. Adjustment was considered less important for multiplicity due to multiple secondary outcomes (adjustment performed for 17/136 [13%] published trials and 3/27 [11%] CTU statisticians would consider adjustment) and subgroup analyses (8/85 [9%] published trials adjusted and 6/27 CTU [22%] statisticians would consider adjustment).

CONCLUSIONS

There is variation in opinions about adjustment for multiplicity among both statisticians reporting RCTs and applied statisticians working in CTUs. Further guidance is needed on the circumstances in which adjustment should be considered in relation to primary trial hypotheses, and if there are any situations in which adjustment would be recommended in the context of secondary analyses.