title: Detecting qualitative interactions in clinical trials with binary responses.
abstract: This study considers the detection of treatment-by-subset interactions in a stratified, randomised clinical trial with a binary-response variable. The focus lies on the detection of qualitative interactions. In addition, the presented method is useful more generally, as it can assess the inconsistency of the treatment effects among strata by using an a priori-defined inconsistency margin. The methodology presented is based on the construction of ratios of treatment effects. In addition to multiplicity-adjusted p-values, simultaneous confidence intervals are recommended to use in detecting the source and the amount of a potential qualitative interaction. The proposed method is demonstrated on a multi-regional trial using the open-source statistical software R.
authors: Institut für Biostatistik, Leibniz Universität Hannover, Herrenhäuser Straße 2, Hannover, Germany.
authors: Andreas
authors: A
authors: Kitsche
mesh_terms: D003627:Data Interpretation, Statistical; D006333:Heart Failure / Q000188:drug therapy / Q000453:epidemiology; D006801:Humans; D057230:Limit of Detection; D008790:Metoprolol / Q000627:therapeutic use; D015337:Multicenter Studies as Topic / Q000592:standards / Q000706:statistics & numerical data; D016032:Randomized Controlled Trials as Topic / Q000592:standards / Q000706:statistics & numerical data*
chemical_list: D008790:Metoprolol
keywords: heterogeneity; inconsistency; qualitative interaction; simultaneous confidence intervals