Dose Finding Designs for Continuous Responses and Binary Utility

Often in clinical trials the observed responses are continuous but a regulatory agency will approve the drug only if the probability is sufficiently large that the efficacy measure exceeds a predefined threshold and the toxicity does not exceed another given threshold. Thus the measure of interest (...

Full description

Saved in:
Bibliographic Details
Published in:Journal of biopharmaceutical statistics 2007-01, Vol.17 (6), p.1085-1096
Main Authors: Fedorov, Valerii V., Wu, Yuehui
Format: Article
Language:English
Subjects:
Binary utility function
Clinical Trials as Topic - methods
Clinical Trials as Topic - statistics & numerical data
Computer Simulation
Continuous responses
Dichotomization
Dose-Response Relationship, Drug
Humans
Normal Distribution
Optimal study design
Research Design
Two-stage design
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Often in clinical trials the observed responses are continuous but a regulatory agency will approve the drug only if the probability is sufficiently large that the efficacy measure exceeds a predefined threshold and the toxicity does not exceed another given threshold. Thus the measure of interest (utility) is based on dichotomized responses. We consider normally distributed correlated responses and build a utility function using the probit transform. Locally optimal designs are used as benchmarks for more practical designs such as composite and adaptive designs. We focus on D -criterion (i.e., all parameters of the dose-response model are of interest) and consider only two-stage designs. It is shown that the practice of reporting dichotomized responses leads to a substantial loss in the precision of estimated parameters (or in the power loss).
ISSN:1054-3406
1520-5711
DOI:10.1080/10543400701645132