Decision Rules and Associated Sample Size Planning for Regional Approval Utilizing Multiregional Clinical Trials

2012 ◽  
Vol 22 (5) ◽  
pp. 1001-1018 ◽  
Author(s):  
Xiaoyuan Chen ◽  
Nelson Lu ◽  
Rajesh Nair ◽  
Yunling Xu ◽  
Cailian Kang ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Decision Rules ◽  
Sample Size Planning

Planning the Size of Clinical Trials with Allowance for Patient Noncompliance

1990 ◽  
Vol 29 (03) ◽  
pp. 243-246 ◽  
Author(s):  
M. A. A. Moussa
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Sample Size ◽  
Event Rate ◽  
Survival Functions ◽  
Time Intervals ◽  
Patient Noncompliance ◽  
Event Rates ◽  
Larger Sample

AbstractVarious approaches are considered for adjustment of clinical trial size for patient noncompliance. Such approaches either model the effect of noncompliance through comparison of two survival distributions or two simple proportions. Models that allow for variation of noncompliance and event rates between time intervals are also considered. The approach that models the noncompliance adjustment on the basis of survival functions is conservative and hence requires larger sample size. The model to be selected for noncompliance adjustment depends upon available estimates of noncompliance and event rate patterns.

scholarly journals Do patient characteristics matter when calculating sample size for eczema clinical trials?

2021 ◽  
Author(s):  
L. Howells ◽  
S. Gran ◽  
J. R. Chalmers ◽  
B. Stuart ◽  
M. Santer ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Patient Characteristics

scholarly journals Erratum to: Power Analysis and Sample Size Planning in Ancova Designs

Psychometrika ◽  
2021 ◽  
Author(s):  
Gwowen Shieh
Keyword(s):  
Sample Size ◽  
Power Analysis ◽  
Sample Size Planning

A Correction to this paper has been published: https://doi.org/10.1007/s11336-019-09692-3

Unified exact design with early stopping rules for single arm clinical trials with multiple endpoints

2021 ◽  
pp. 096228022110130
Author(s):  
Wei Wei ◽  
Denise Esserman ◽  
Michael Kane ◽  
Daniel Zelterman
Keyword(s):  
Clinical Trials ◽  
Early Phase ◽  
Decision Rules ◽  
Stopping Rules ◽  
Multiple Endpoints ◽  
Shiny App ◽  
R Shiny ◽  
Early Phase Clinical Trials ◽  
User Friendly ◽  
Exact Design

Adaptive designs are gaining popularity in early phase clinical trials because they enable investigators to change the course of a study in response to accumulating data. We propose a novel design to simultaneously monitor several endpoints. These include efficacy, futility, toxicity and other outcomes in early phase, single-arm studies. We construct a recursive relationship to compute the exact probabilities of stopping for any combination of endpoints without the need for simulation, given pre-specified decision rules. The proposed design is flexible in the number and timing of interim analyses. A R Shiny app with user-friendly web interface has been created to facilitate the implementation of the proposed design.

Sample size calculation for clinical trials in which entry criteria and outcomes are counts of events

1994 ◽  
Vol 13 (8) ◽  
pp. 859-870 ◽  
Author(s):  
Robert P. McMahon ◽  
Michael Proschan ◽  
Nancy L. Geller ◽  
Peter H. Stone ◽  
George Sopko
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Sample Size Calculation

scholarly journals Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications

2014 ◽  
Vol 56 (4) ◽  
pp. 614-630 ◽  
Author(s):  
Alexandra C. Graf ◽  
Peter Bauer ◽  
Ekkehard Glimm ◽  
Franz Koenig
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Error Rate ◽  
Type 1 Error ◽  
Multiarmed Clinical Trials
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