A multi-treatment response adaptive design for ordinal categorical responses. (March 2020)

• Record Type: Journal Article
• Authors: Biswas, Atanu; Bhattacharya, Rahul; Das, Soumyadeep
• Other Names: Austin Peter guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 29:Number 3(2020)
• Page Start: 827
• Page End: 836
• Publication Date: 2020-03
• Subjects: Response adaptive design -- ordinal categorical responses -- cumulative odds ratio; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280219846152
• Languages: English
• ISSNs: 0962-2802

Abstract

A multi-treatment response adaptive procedure is developed considering "comparison with the best" philosophy of multiple comparison procedures for clinical trials with ordinal categorical responses, when there is no shared control. For each response category, we arbitrarily create two outcome groups; one by combining the categories more favorable to it and the other by merging the categories at most as favorable to it and hence define the odds (i.e. cumulative odds). Pairwise ratios of such odds (i.e. cumulative odds ratios) based on pairs of treatments are combined conveniently to derive a measure of relative superiority and hence the allocation probability functions. For practical implementation, we suggest response-adaptive randomization (RAR), that is, update the allocation probabilities dynamically using the available allocation and response information to favor the treatment doing better. Empirical as well as large sample properties following the randomization are investigated in detail. Moreover, a real clinical trial with trauma patients is redesigned using the proposed RAR to envisage practical applicability.