Promising zone two-stage design for a single-arm study with binary outcome

Adaptive designs are increasingly used in clinical trials to assess the effectiveness of new drugs. For a single-arm study with a binary outcome, several adaptive designs were developed by using numerical search algorithms and the conditional power approach. The design based on numerical search algo...

Full description

Saved in:
Bibliographic Details
Published in:Statistical methods in medical research Vol. 32; no. 6; p. 1159
Main Author: Shan, Guogen
Format: Journal Article
Language:English
Published: England 01.06.2023
Subjects:
Algorithms
Research Design
Sample Size
optimal two-stage design
single-arm study
Adaptive design
promising zone design
conditional power
binary response
ISSN:1477-0334, 1477-0334
Online Access:Get more information
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Adaptive designs are increasingly used in clinical trials to assess the effectiveness of new drugs. For a single-arm study with a binary outcome, several adaptive designs were developed by using numerical search algorithms and the conditional power approach. The design based on numerical search algorithms is able to identify the global optimal design, but the computational intensity limits the usage of these designs. The conditional power approach searches for the optimal design without expensive computing time. In addition, promising zone strategy was proposed to move on drug development to the follow-up stages when the interim results are promising. We propose to develop two adaptive designs: One based on the conditional power approach, and the other based on the promising zone strategy. These two designs preserve types I and II error rates. It is preferable to satisfy the monotonic property for adaptive designs: The second stage sample size decreases as the first stage responses go up. We theoretically prove this important property for the two proposed designs. The proposed designs can be easily applied to real trials with limited computing resources.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1477-0334
1477-0334
DOI:10.1177/09622802231164737