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The Difference Between Learning and Claiming: Why Hypothesis Testing and Multiplicity Control Should Depend on Context
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DOI：10.1093/ejcts/ezag171.png)
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Abstract
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Clinical trials are not all trying to do the same thing. Some are meant to establish that a new treatment works well enough to be approved, paid for, and adopted in practice. Others compare treatments that are already in use, such as coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI), where the question is less whether either treatment “works” and more how they differ: which outcomes improve and by how much, which risks increase, which patients benefit most, and over what time horizon.1 In the first setting, the trial is often asked to support a clear yes-or-no claim. In the second, the trial may be most useful when it preserves the complexity of the evidence rather than forcing all results into a single declaration of success or failure (Figure 1).
Keywords:
clinical trials
hypothesis testing
multiplicity control
treatment comparison
evidence complexity
Journal
E
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