|
Activity Number:
|
398
- Different Approaches to the Increase of a Sample Size When the Unblinded Interim Estimate of the Treatment Effect Looks Promising
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Biopharmaceutical Section
|
|
Abstract #323026
|
|
|
Title:
|
Extensions of Adaptive Sample Size Re-Estimation Methods to the Negative Binomial Setting
|
|
Author(s):
|
Mikhail Peter Salganik* and Sandeep Menon and Abigail Sloan
|
|
Companies:
|
Pfizer Worldwide Research & Development, Pfizer, Inc and Pfizer, Inc and Harvard T.H. Chan School of Public Health
|
|
Keywords:
|
Interim analysis ;
Sample size re-estimation ;
Unblinded ;
Negative binomial ;
Promising zone
|
|
Abstract:
|
A ''promising zone'' design of a clinical trial allows the increase of study's sample size when the unblinded interim estimate of the treatment effect looks promising. In spite of the many years of research and discussion in the regulatory and statistical literature the evaluation of general usefulness of the ''promising zone'' design and ranking of the usefulness of the different sample size re-assessment rules are still opened to debate. We illustrate operating characteristics of several sample size re-assessment rules in the practically important setting where the response follows a negative binomial distribution. This setting can be relevant to the modeling of observed numbers of new enhancing lesions seen on MRI images, numbers of falls in elderly patients, numbers of exacerbation events in asthma and COPD and counts of days with pain in patients with sickle cell disease among others. Our analysis suggests that the the overall usefulness of the ''promising zone'' design and relative attractiveness of the sample size re-estimation rules may be application dependent.
|
Authors who are presenting talks have a * after their name.
