A simple method to estimate sample sizes for safety equivalence studies using inverse sampling.

Nicholas Moore, Pascale Tubert-Bitter, Anne Fourrier, Bernard Bégaud
Author Information
  1. Nicholas Moore: Départment de Pharmacologie, Université Victor-Segalen, Case 36, 33076, Bordeaux, Cedex, France. nicholas.moore@pharmaco.u-bordeaux2.fr

Abstract

Safety equivalence studies may be required to demonstrate that a new procedure or process is at least as safe as a previous one. They usually involve low or very low outcome rates that are often not precisely determined, making patient-based sample sizing uncertain. Using a reverse sampling approach, a method is derived from standard equations to estimate the number of events that need to be observed to demonstrate equivalence using the confidence interval approach. For instance, for a one-sided (nonsuperiority) hypothesis, 5% alpha risk, and 80% power, almost 100 events need to be observed in each study arm to demonstrate equivalence within 30%, or 250 events for 20% equivalence. The number of patients to be included can be derived directly from expected event rates.

MeSH Term

Confidence Intervals
Epidemiologic Research Design
Humans
Safety
Sample Size
Therapeutic Equivalency

Word Cloud

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