Literature DB >> 12812816

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

Nicholas Moore1, Pascale Tubert-Bitter, Anne Fourrier, Bernard Bégaud.   

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.

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Year:  2003        PMID: 12812816     DOI: 10.1016/s0895-4356(02)00608-x

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  3 in total

1.  Assessing drug safety.

Authors:  Nicholas Moore
Journal:  BMJ       Date:  2005-03-05

2.  Coronary Events After Dispensing of Ibuprofen: A Propensity Score-Matched Cohort Study Versus Paracetamol in the French Nationwide Claims Database Sample.

Authors:  Mai Duong; Abdelilah Abouelfath; Regis Lassalle; Cécile Droz; Patrick Blin; Nicholas Moore
Journal:  Drug Saf       Date:  2018-11       Impact factor: 5.606

Review 3.  Coronary Risks Associated with Diclofenac and Other NSAIDs: An Update.

Authors:  Nicholas Moore
Journal:  Drug Saf       Date:  2020-04       Impact factor: 5.606

  3 in total

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