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STATE-OF-THE-ART PAPER AND COMMENTARY

Trial and Error

How to Avoid Commonly Encountered Limitations of Published Clinical Trials

Division of Cardiology, Cedars-Sinai Medical Center, and the David Geffen School of Medicine, University of California, Los Angeles, California

Manuscript received January 25, 2009; revised manuscript received June 1, 2009, accepted June 1, 2009.

^_* Reprint requests and correspondence: Dr. Sanjay Kaul, Division of Cardiology, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, South Professional Tower, Room 5536, Los Angeles, California 90048-1804 (Email: kaul{at}cshs.org).

The randomized controlled clinical trial is the gold standard scientific method for the evaluation of diagnostic and treatment interventions. Such trials are cited frequently as the authoritative foundation for evidence-based management policies. Nevertheless, they have a number of limitations that challenge the interpretation of the results. The strength of evidence is often judged by conventional tests that rely heavily on statistical significance. Less attention has been paid to the clinical significance or the practical importance of the treatment effects. One should be cautious that extremely large studies might be more likely to find a formally statistically significant difference for a trivial effect that is not really meaningfully different from the null. Trials often employ composite end points that, although they enable assessment of nonfatal events and improve trial efficiency and statistical precision, entail a number of shortcomings that can potentially undermine the scientific validity of the conclusions drawn from these trials. Finally, clinical trials often employ extensive subgroup analysis. However, lack of attention to proper methods can lead to chance findings that might misinform research and result in suboptimal practice. Accordingly, this review highlights these limitations using numerous examples of published clinical trials and describes ways to overcome these limitations, thereby improving the interpretability of research findings.

Key Words: results • megatrials • interpret

Abbreviations and Acronyms   ACS = acute coronary syndrome   CABG = coronary artery bypass graft surgery   CI = confidence interval   LMCA = left main coronary artery   MACE = major adverse cardiac event   MCID = minimum clinically important difference   MI = myocardial infarction   NNT = number needed to treat   PCI = percutaneous coronary intervention   RCT = randomized controlled trial   TVR = target vessel revascularization

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