Author Affiliations: Department of Clinical Science and Medical Education, Charles E. Schmidt College of Biomedical Science and Center of Excellence, Florida Atlantic University, Boca Raton (Dr Hennekens); and Department of Biostatistics & Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison (Dr DeMets).
Randomized trials of adequate size and duration designed to test a priori hypotheses represent the most reliable design strategy to detect the most realistically small to moderate therapeutic effects of drugs. Such trials should achieve high adherence to an adequate dose of the drug and a sufficient number of clinical end points to distinguish reliably between the null hypothesis and the most plausible alternative hypothesis of small to moderate benefit or harm.1 With regard to the development of drugs to treat diabetes mellitus, the US Food and Drug Administration (FDA) has developed guidance for industry that somewhat overemphasizes results from meta-analyses of phase 2 trials that were not large enough to test realistic hypotheses about clinical cardiovascular (CV) events.2 Even in aggregate, such results should be considered more as hypothesis formulating than as hypothesis testing. The main need now is for trials that are large enough to have adequate statistical power.
Hennekens CH, DeMets D. The Need for Large-Scale Randomized Evidence Without Undue Emphasis on Small Trials, Meta-analyses, or Subgroup Analyses. JAMA. 2009;302(21):2361–2362. doi:10.1001/jama.2009.1756
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