Pain
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Missing data in clinical trials can bias estimates of treatment effects. Statisticians and government agencies recommend making every effort to minimize missing data. Although statistical methods are available to accommodate missing data, their validity depends on often untestable assumptions about why the data are missing. ⋯ Last observation carried forward imputation was used most commonly (42%). Thirteen articles reported more than 1 method to accommodate missing data; however, the majority of methods, including last observation carried forward, were not methods currently recommended by statisticians. Authors, reviewers, and editors should prioritize proper reporting of missing data and appropriate use of methods to accommodate them so as to improve the deficiencies identified in this systematic review.
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Proof-of-concept (POC) clinical trials play an important role in developing novel treatments and determining whether existing treatments may be efficacious in broader populations of patients. The goal of most POC trials is to determine whether a treatment is likely to be efficacious for a given indication and thus whether it is worth investing the financial resources and participant exposure necessary for a confirmatory trial of that intervention. A challenge in designing POC trials is obtaining sufficient information to make this important go/no-go decision in a cost-effective manner. ⋯ The trade-off between parallel-group and crossover designs with respect to overall sample sizes, trial duration, and applicability is summarized. The advantages and disadvantages of more recent trial designs, including N-of-1 designs, enriched designs, adaptive designs, and sequential parallel comparison designs, are summarized, and recommendations for consideration are provided. More attention to identifying efficient yet powerful designs for POC clinical trials of chronic pain treatments may increase the percentage of truly efficacious pain treatments that are advanced to confirmatory trials while decreasing the percentage of ineffective treatments that continue to be evaluated rather than abandoned.