title: Type I error and power in noninferiority/equivalence trials with correlated multiple endpoints: an example from vaccine development trials.
abstract: Clinical trials necessary for the development of new treatment often require testing of multiple endpoints for equivalence or noninferiority relative to an existing effective standard therapy. An example is a vaccine study with multiple antibody measurements in sera of subjects receiving a combination vaccine such as a pneumococcal vaccine, which contains many different serotypes of the pneumococcal organism. This article describes testing methods for the demonstration of simultaneous marginal equivalence or noninferiority of two treatments on each component of the response vector that follows a multivariate normal distribution. Systematic simulation studies are conducted to evaluate the performance of the testing method and to examine under what conditions the power is substantially different if the multiple endpoints are assumed to be independent when they are actually strongly correlated. Data from an illustrative example are used to describe how the study power can be evaluated in the design of the trials.
authors.affiliation: Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA. lkong@pitt.edu
authors.forename: Lan
authors.initials: L
authors.lastname: Kong
authors.forename: Robert C
authors.initials: RC
authors.lastname: Kohberger
authors.forename: Gary G
authors.initials: GG
authors.lastname: Koch
mesh_terms: D000465:Algorithms; D000906:Antibodies / Q000032:analysis; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D023381:Endpoint Determination / Q000706:statistics & numerical data*; D006801:Humans; D012107:Research Design; D014612:Vaccines / Q000627:therapeutic use*
chemical_list: D000906:Antibodies; D014612:Vaccines