Statistical tests based on new composite hypotheses in clinical trials reflecting the relative clinical importance of multiple endpoints quantitatively.
In clinical trials, several endpoints (EPs) are often evaluated to compare treatments in some therapeutic area. Suppose that there are two EPs in a clinical trial. We propose a new set of composite hypotheses for continuous variables, taking the relative clinical importance of the EPs into account. The main hypotheses were formulated to show that a treatment is so superior to the control treatment, which is not necessarily a placebo, in one EP, that the possible non-inferiority of the treatment by at most a certain value in the other EP can be compensated sufficiently, taking the clinical point of view into account. The maximum non-inferiority margin of one EP might not be a biologically unimportant difference in exchange for much superiority of the other EP. This formulation leads to a new composite EP and a very simple test statistic. The intersection-union principle was employed to derive the proposed test.
Department of Technology Assessment and Biostatistics, National Institute of Public Health, 3-6 Minami 2 chome, Wako, Saitama 351-0197, Japan. mnishikawa@niph.go.jp
Masako
M
Nishikawa
Toshiro
T
Tango
Megu
M
Ohtaki
D001249:Asthma / Q000188:drug therapy / Q000503:physiopathology; D001699:Biometry / Q000379:methods*; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D023381:Endpoint Determination / Q000706:statistics & numerical data*; D005541:Forced Expiratory Volume; D006801:Humans; D015233:Models, Statistical; D029424:Pulmonary Disease, Chronic Obstructive / Q000188:drug therapy / Q000503:physiopathology; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data