Dual-objective bayesian optimal designs for a dose-ranging study

qi Zeng; Wei Zhu; Weng Kee Wong

doi:10.1177/009286150003400210

Dual-objective bayesian optimal designs for a dose-ranging study

qi Zeng
, Wei Zhu
, Weng Kee Wong

Applied Mathematics and Statistics

Merck
University of California at Los Angeles

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

The American College of Rheumatology Responder Index (ACR index) is commonly used to measure treatment efficacy in rheumatoid arthritis trials. This composite index measures the patients’ responses as improved or not improved. We use a logit model to describe the dose-response relationship and construct dual-objective optimal designs using prior information. The specific objectives of our designs are to simultaneously estimate the parameters in the dose-response curve and the minimum dose that reaches clinically meaningful significance.

Original language	English
Pages (from-to)	421-428
Number of pages	8
Journal	Therapeutic Innovation & Regulatory Science
Volume	34
Issue number	2
DOIs	https://doi.org/10.1177/009286150003400210
State	Published - 2000

Keywords

ACR Responder Index
Bayesian multiple-objective optimal design
Clinically significant dose
Efficiency plot
Logit model

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10.1177/009286150003400210

Cite this

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abstract = "The American College of Rheumatology Responder Index (ACR index) is commonly used to measure treatment efficacy in rheumatoid arthritis trials. This composite index measures the patients{\textquoteright} responses as improved or not improved. We use a logit model to describe the dose-response relationship and construct dual-objective optimal designs using prior information. The specific objectives of our designs are to simultaneously estimate the parameters in the dose-response curve and the minimum dose that reaches clinically meaningful significance.",

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AB - The American College of Rheumatology Responder Index (ACR index) is commonly used to measure treatment efficacy in rheumatoid arthritis trials. This composite index measures the patients’ responses as improved or not improved. We use a logit model to describe the dose-response relationship and construct dual-objective optimal designs using prior information. The specific objectives of our designs are to simultaneously estimate the parameters in the dose-response curve and the minimum dose that reaches clinically meaningful significance.

KW - ACR Responder Index

KW - Bayesian multiple-objective optimal design

KW - Clinically significant dose

KW - Efficiency plot

KW - Logit model

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DO - 10.1177/009286150003400210

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JO - Therapeutic Innovation & Regulatory Science

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ER -

Dual-objective bayesian optimal designs for a dose-ranging study

Abstract

Keywords

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