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Optimal designs for active controlled dose-finding trials with efficacy-toxicity outcomes.
Schorning, K; Dette, H; Kettelhake, K; Wong, W K; Bretz, F.
Affiliation
  • Schorning K; Fakultät für Mathematik, Ruhr-Universität Bochum, 44780 Bochum, GermanyKirsten.Schorning@rub.deholger.dette@rub.deKatrin.Kettelhake@rub.de.
  • Dette H; Fakultät für Mathematik, Ruhr-Universität Bochum, 44780 Bochum, GermanyKirsten.Schorning@rub.deholger.dette@rub.deKatrin.Kettelhake@rub.de.
  • Kettelhake K; Fakultät für Mathematik, Ruhr-Universität Bochum, 44780 Bochum, GermanyKirsten.Schorning@rub.deholger.dette@rub.deKatrin.Kettelhake@rub.de.
  • Wong WK; Department of Biostatistics, University of California at Los Angeles, 650 Charles E. Young Dr. South, Los Angeles, California 90095, U.S.A.wkwong@ucla.edu.
  • Bretz F; Statistical Methodology, Novartis Pharma AG, 4002 Basel, Switzerlandfrank.bretz@novartis.com.
Biometrika ; 104(4): 1003-1010, 2017 Dec.
Article in En | MEDLINE | ID: mdl-29430043
ABSTRACT
We derive optimal designs to estimate efficacy and toxicity in active controlled dose-finding trials when the bivariate continuous outcomes are described using nonlinear regression models. We determine upper bounds on the required number of different doses and provide conditions under which the boundary points of the design space are included in the optimal design. We provide an analytical description of minimally supported optimal designs and show that they do not depend on the correlation between the bivariate outcomes.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Biometrika Year: 2017 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Prognostic_studies Language: En Journal: Biometrika Year: 2017 Document type: Article