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The Ci3+3 design for dual-agent combination dose-finding clinical trials.
Yuan, Shijie; Zhou, Tianjian; Lin, Yawen; Ji, Yuan.
Afiliação
  • Yuan S; Cytel Inc, Cambridge, USA.
  • Zhou T; Department of Public Health Sciences, The University of Chicago, Chicago, USA.
  • Lin Y; Cytel Inc, Cambridge, USA.
  • Ji Y; Department of Statistics, Colorado State University, Fort Collins, USA.
J Biopharm Stat ; 31(6): 745-764, 2021 11 02.
Article em En | MEDLINE | ID: mdl-34781853
ABSTRACT
We propose a rule-based statistical design for combination dose-finding trials with two agents. The Ci3 + 3 design is an extension of the i3 + 3 design with simple up-and-down decision rules comparing the observed toxicity rates and equivalence intervals that define the maximum tolerated dose combination. Ci3 + 3 consists of two stages to allow fast and efficient exploration of the dose-combination space. Statistical inference is restricted to a beta-binomial model for dose evaluation, and the entire design is built upon a set of fixed rules. We show via simulation studies that the Ci3 + 3 design exhibits similar and comparable operating characteristics to more complex designs utilizing model-based inferences. Implementation of Ci3 + 3 for practical trials is simple for the first stage, where the up-and-down decisions may be carried out using a decision table based on the preselected escalation path and i3 + 3. The second stage is not simpler than model-based designs, however, since it also requires computation of posterior probabilities based on a Bayesian model. We believe that the Ci3 + 3 design may provide an alternative choice to help simplify the design and conduct of combination dose-finding trials in practice.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / Modelos Estatísticos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Biopharm Stat Assunto da revista: FARMACOLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / Modelos Estatísticos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Biopharm Stat Assunto da revista: FARMACOLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
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