Journal of clinical epidemiology
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A survey of randomized controlled trials found that almost a quarter of trials had more than 10% of responses missing for the primary outcome. There are a number of ways in which data could be missing: the subject is unable to provide it, or they withdraw, or become lost to follow-up. Such attrition means that balance in baseline characteristics for those randomized may not be maintained in the subsample who has outcome data. For individual trials, if the attrition is systematic and linked to outcome, then this will result in biased estimates of the overall effect. It then follows that if such trials are combined in a meta-analysis, it will result in a biased estimate of the overall effect and be misleading. The aim of this study was to investigate the impact of attrition on baseline imbalance within individual trials and across multiple trials. ⋯ Although, in theory, attrition can introduce selection bias in randomized trials, we did not find sufficient evidence to support this claim in our convenience sample of trials. However, the number of trials included was relatively small, which may have led to small but important differences in outcomes being missed. In addition, only 2 of 10 trials included had attrition levels greater than 15% suggesting a low level of potential bias. Meta-analyses and systematic reviews should always consider the impact of attrition on baseline imbalances and where possible any baseline imbalances in the analyzed data set and their impact on the outcomes reported.
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A recently published instrument (PRECIS) was designed to assist investigative teams in understanding the various design decisions that need to be made regarding pragmatic vs. explanatory trials. Our team used this instrument during an investigators' meeting to organize our discussion regarding the design of a planned trial and to determine the extent of consensus among the study investigators. ⋯ The investigative team found that applying PRECIS principles were useful for (1) detailing points of discussion related to trial design, (2) making revisions to the design to be consistent with the project goals, and (3) achieving consensus. We believe our experiences with PRECIS may prove valuable for trial researchers in much the same way that case reports can provide valuable insights for clinicians.