title: Assessing non-inferiority: a combination approach.
abstract: Non-inferiority designs are growing in importance as a strategy for comparing new drugs with established therapies. Because it is not possible to show that a new drug and the established therapy have identical efficacy profiles, non-inferiority trials are designed to demonstrate that the new drug is not inferior to an established drug (the 'control') relative to a prespecified 'non-inferiority margin'. No objective principle guides the choice of the non-inferiority margin, and controversies about the margin have, in some cases, had important consequences for drug development. We argue that some of these controversies have arisen because non-inferiority trials must achieve two objectives. They must demonstrate not only that the new drug is not inferior to the control drug by the non-inferiority margin, but also that the new drug is superior to placebo. When the second objective is not considered explicitly, it can distort the choice of the non-inferiority margin. Some methods designed to address both objectives through the choice of the non-inferiority margin lead to overly stringent non-inferiority criteria. We describe an approach to non-inferiority analysis that combines two tests, a traditional test for non-inferiority and a test for superiority based on a synthetic estimate of the effect of the new treatment relative to placebo. The synthetic estimate may be 'discounted' to address concerns about assay inconstancy. We discuss power and sample size considerations for the proposed procedure.
authors.affiliation: The Medicines Company, 8 Campus Drive, Parsippany, NJ 07054, USA. ping.gao@themedco.com
authors.forename: Ping
authors.initials: P
authors.lastname: Gao
authors.forename: James H
authors.initials: JH
authors.lastname: Ware
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D015507:Drugs, Investigational / Q000627:therapeutic use; D005069:Evaluation Studies as Topic; D006801:Humans; D010919:Placebos; D012107:Research Design; D018401:Sample Size; D016896:Treatment Outcome; D014481:United States
chemical_list: D015507:Drugs, Investigational; D010919:Placebos