Using historical control information for the design and analysis of clinical trials with overdispersed count data

2013 ◽  
Vol 32 (21) ◽  
pp. 3609-3622 ◽  
Author(s):  
Sandro Gsteiger ◽  
Beat Neuenschwander ◽  
Francois Mercier ◽  
Heinz Schmidli
Keyword(s):  
Clinical Trials ◽  
Count Data ◽  
Historical Control ◽  
Control Information

Robust meta-analytic-predictive priors in clinical trials with historical control information

Biometrics ◽  
2014 ◽  
Vol 70 (4) ◽  
pp. 1023-1032 ◽  
Author(s):  
Heinz Schmidli ◽  
Sandro Gsteiger ◽  
Satrajit Roychoudhury ◽  
Anthony O'Hagan ◽  
David Spiegelhalter ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Historical Control ◽  
Control Information

A Comparison Between a Meta-analytic Approach and Power Prior Approach to Using Historical Control Information in Clinical Trials With Binary Endpoints

2019 ◽  
pp. 216847901986253
Author(s):  
Naoki Isogawa ◽  
Kentaro Takeda ◽  
Kazushi Maruo ◽  
Takashi Daimon
Keyword(s):  
Clinical Trials ◽  
Type I Error ◽  
Experimental Treatment ◽  
Historical Control ◽  
Analytic Approach ◽  
Control Treatment ◽  
Small Scale ◽  
Type I ◽  
Control Information ◽  
Power Prior

Background: In the process of research and development of a new treatment, clinical trials are conducted to evaluate its safety and efficacy. Key to streamlining the process is to utilize appropriate historical information on an outcome of a control treatment when designing and analyzing a clinical trial. Methods: For the use of such historical control information, there exist a meta-analytic approach and power prior approach. In this article, we evaluate their performance with regard to the type I error (TIE) rate and power through a simulation study where we analyze the data on a binary outcome of an experimental treatment and a control treatment from a new small-scale trial, along with the corresponding data of the control treatment from multiple historical trials. The reason is that the difference in the performance between the 2 approaches has not been clear. Results: When historical trials were homogeneous, the power was higher in the power prior approach and the meta-analytic approach using a beta-binomial model with a less noninformative prior than the other approaches. However, when heterogeneous historical trials were mixed, the power was lower, or the TIE rates got inflated. Conclusions: To make use of historical control data, if importance is attached to control of the TIE rate, the meta-analytic approach using a normal-normal hierarchical model may be preferable to the power prior approach, whereas if attached to improvement of the power, this preference be reversed. Anyway, the best approach should be chosen by comparing the operational characteristics of the approaches.

P35 the analysis of transformed count data in clinical trials

1997 ◽  
Vol 18 (3) ◽  
pp. S131-S132
Author(s):  
Bruce Thompson ◽  
Sandra Forman ◽  
Michael Terrin
Keyword(s):  
Clinical Trials ◽  
Count Data

scholarly journals Use of historical control data for assessing treatment effects in clinical trials

2013 ◽  
Vol 13 (1) ◽  
pp. 41-54 ◽  
Author(s):  
Kert Viele ◽  
Scott Berry ◽  
Beat Neuenschwander ◽  
Billy Amzal ◽  
Fang Chen ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Treatment Effects ◽  
Historical Control ◽  
Control Data ◽  
Historical Control Data
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