Clinical trials : journal of the Society for Clinical Trials
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Comparative effectiveness research (CER) is still an evolving framework for which much needs to be done to improve the ability of randomized controlled trials (RCTs) to supply the necessary evidence. Perhaps, most important is to start with a clearly specified decision and decision maker in mind when the RCTs are designed. Second is to initiate RCTs with clinically relevant outcomes and comparators earlier in the evaluation process. ⋯ It will be necessary to borrow observational methodologies and approaches to extract meaningful causal and subgroup inferences from such trials. Process variables should be seen as potentially part of that framework of effect-modifying factors, perhaps amenable to embedded experimental assessment with a trial. Perhaps most importantly, we need to improve the nationwide CER infrastructure to allow for rapid initiation and accrual for CER trials to reduce the trade-off that often exists between the speed of evidence development and its quality.
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The intention-to-treat comparison is the primary, if not the only, analytic approach of many randomized clinical trials. ⋯ We recommend that all randomized clinical trials with substantial lack of adherence or loss to follow-up are analyzed using different methods. These include an intention-to-treat analysis to estimate the effect of assigned treatment and 'as treated' and 'per protocol' analyses to estimate the effect of treatment after appropriate adjustment via inverse probability weighting or g-estimation.
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Randomized clinical trials (RCTs) are often positioned at the top of evidence hierarchies. Meta-analyses of RCTs aim to integrate the state of knowledge on a given scientific question, particularly for rare drug-related outcomes. However, although RCTs are valuable tools in our armamentarium, they are rarely designed to evaluate drug safety and are thus susceptible to limitations that may hamper the ability of both RCTs and meta-analyses to fully characterize the safety profiles of drugs. Their potential limitations might be exacerbated in the study of rare outcomes, often encountered in drug safety assessment, when even minor deviations from the intended randomization could impact the stability of the risk estimates. ⋯ Although some of the limitations described are inherent in RCTs, some of the sources of bias highlighted in this article could be minimized by careful RCT design, planned follow-up, and improved collection of information on adverse events. As future research sheds more light on pertinent knowledge gaps and issues, the ability to maximize the use of RCTs and meta-analyses of RCTs to address drug safety questions of interest will be greatly enhanced.
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Randomized Controlled Trial
Design of a randomized trial of diabetes genetic risk testing to motivate behavior change: the Genetic Counseling/lifestyle Change (GC/LC) Study for Diabetes Prevention.
The efficacy of diabetes genetic risk testing to motivate behavior change for diabetes prevention is currently unknown. ⋯ We designed a randomized clinical trial designed to explore the motivational impact of disclosing both higher than average and lower than average genetic risk for type 2 diabetes. This design allowed exploration of both increased risk and false reassurance, and has implications for future studies in translational genomics.
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Benjamin Freedman has argued in 1987 that before a controlled trial is started, there should be 'genuine uncertainty in the expert medical community about the preferred treatment'. Freedman's definition of the concept is widespread in clinical research, but has been controversial since its start. Over the past decade, the equipoise controversy has become increasingly complex. ⋯ There is no decisive reason to give up on the equipoise requirement.