title: Analyzing multiple endpoints in a confirmatory randomized clinical trial-an approach that addresses stratification, missing values, baseline imbalance and multiplicity for strictly ordinal outcomes.
abstract: Confirmatory randomized clinical trials with a stratified design may have ordinal response outcomes, ie, either ordered categories or continuous determinations that are not compatible with an interval scale. Also, multiple endpoints are often collected when 1 single endpoint does not represent the overall efficacy of the treatment. In addition, random baseline imbalances and missing values can add another layer of difficulty in the analysis plan. Therefore, the development of an approach that provides a consolidated strategy to all issues collectively is essential. For a real case example that is from a clinical trial comparing a test treatment and a control for the pain management for patients with osteoarthritis, which has all aforementioned issues, multivariate Mann-Whitney estimators with stratification adjustment are applicable to the strictly ordinal responses with stratified design. Randomization based nonparametric analysis of covariance is applied to account for the possible baseline imbalances. Several approaches that handle missing values are provided. A global test followed by a closed testing procedure controls the family wise error rate in the strong sense for the analysis of multiple endpoints. Four outcomes indicating joint pain, stiffness, and functional status were analyzed collectively and also individually through the procedures. Treatment efficacy was observed in the combined endpoint as well as in the individual endpoints. The proposed approach is effective in addressing the aforementioned problems simultaneously and straightforward to implement.
authors.affiliation: Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Hengrui
authors.initials: H
authors.lastname: Sun
authors.affiliation: Department of Biomedical Statistics and Bioinformatics, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan.
authors.forename: Atsushi
authors.initials: A
authors.lastname: Kawaguchi
authors.affiliation: Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Gary
authors.initials: G
authors.lastname: Koch
mesh_terms: D003627:Data Interpretation, Statistical; D023381:Endpoint Determination / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis; D010003:Osteoarthritis / Q000188:drug therapy; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design; D018709:Statistics, Nonparametric
keywords: baseline imbalance; closed testing; missing values; multiple endpoints; stratification; strictly ordinal outcomes