scholarly journals Designing therapeutic cancer vaccine trials with delayed treatment effect

2016 ◽  
Vol 36 (4) ◽  
pp. 592-605 ◽  
Author(s):  
Zhenzhen Xu ◽  
Boguang Zhen ◽  
Yongsoek Park ◽  
Bin Zhu
Keyword(s):  
Cancer Vaccine ◽  
Treatment Effect ◽  
Therapeutic Cancer Vaccine ◽  
Delayed Treatment ◽  
Vaccine Trials

scholarly journals MAGE-A3 With Cell-Penetrating Domain as an Efficient Therapeutic Cancer Vaccine

JAMA Surgery ◽  
2014 ◽  
Vol 149 (5) ◽  
pp. 451 ◽  
Author(s):  
Ramesh B. Batchu ◽  
Oksana Gruzdyn ◽  
Ravindra B. Potti ◽  
Donald W. Weaver ◽  
Scott A. Gruber
Keyword(s):  
Cancer Vaccine ◽  
Therapeutic Cancer Vaccine ◽  
Cell Penetrating

scholarly journals An alphavirus-based therapeutic cancer vaccine: from design to clinical trial

2018 ◽  
Vol 68 (5) ◽  
pp. 849-859 ◽  
Author(s):  
Amrita Singh ◽  
Georgia Koutsoumpli ◽  
Stephanie van de Wall ◽  
Toos Daemen
Keyword(s):  
Clinical Trial ◽  
Cancer Vaccine ◽  
Therapeutic Cancer Vaccine

A group sequential design and sample size estimation for an immunotherapy trial with a delayed treatment effect

2020 ◽  
pp. 096228022098078
Author(s):  
Bosheng Li ◽  
Liwen Su ◽  
Jun Gao ◽  
Liyun Jiang ◽  
Fangrong Yan
Keyword(s):  
Sample Size ◽  
Treatment Effect ◽  
Search Algorithm ◽  
Rank Test ◽  
Group Sequential Design ◽  
Group Sequential ◽  
Delayed Treatment ◽  
Maximum Sample Size ◽  
Analytical Estimation ◽  
Immunotherapy Trial

A delayed treatment effect is often observed in the confirmatory trials for immunotherapies and is reflected by a delayed separation of the survival curves of the immunotherapy groups versus the control groups. This phenomenon makes the design based on the log-rank test not applicable because this design would violate the proportional hazard assumption and cause loss of power. Thus, we propose a group sequential design allowing early termination on the basis of efficacy based on a more powerful piecewise weighted log-rank test for an immunotherapy trial with a delayed treatment effect. We present an approach on the group sequential monitoring, in which the information time is defined based on the number of events occurring after the delay time. Furthermore, we developed a one-dimensional search algorithm to determine the required maximum sample size for the proposed design, which uses an analytical estimation obtained by the inflation factor as an initial value and an empirical power function calculated by a simulation-based procedure as an objective function. In the simulation, we tested the unstable accuracy of the analytical estimation, the consistent accuracy of the maximum sample size determined by the search algorithm and the advantages of the proposed design on saving sample size.

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