Abstract

Clinical trials in the modern medical era began in the mid-20th century with the first randomized, double-blind assessment of an antibiotic, streptomycin, for the treatment of pulmonary tuberculosis.1 Over the course of the next 50 years, the randomized, controlled trial became the “gold standard” for testing the efficacy of new therapies and is generally required for their approval by regulatory agencies worldwide. To be sure, many effective cardiovascular therapies have been identified and approved for use following this generally accepted approach. In this editorial, I will review the many factors that can and do adversely affect the performance and interpretation of contemporary clinical trials in cardiovascular medicine, hoping to shed light on what I view as a series of growing and only partly remediable challenges to effective clinical investigation. Clinical trials in cardiovascular medicine set the standard for randomized, controlled trial design owing to the population prevalence of the major cardiovascular diseases, the event rates in these patient populations, and the practicably achievable sample sizes sufficient to minimize type II errors. In the early studies of fibrinolytic therapy for myocardial infarction (ISIS [International Study of Infarct Survival] and TIMI [Thrombolysis In Myocardial Infarction]), for example, the expected 5-week mortality rate for conventionally treated patients was 12% to 13% at the time2,3 in Europe and the United States. Thus, with several thousand patients in each treatment arm, one could expect to detect confidently true reductions in absolute mortality of 3% to 4%, as was the case in these landmark trials. Over the past three decades, mortality rates for highly prevalent cardiovascular diseases, including acute coronary syndromes, heart failure, and sudden death, have continuously improved owing to the clear benefits of therapies proved to be efficacious in double-blind, randomized, controlled trials. With these mounting, cumulative successes, however, the marginal benefit …

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