Introduction:Vaccines are a cornerstone of global health,with their efficacy and safety dependent on appropriate dosage determination.Early-phase vaccination trials face significant challenges due to minimal toxicity ...Introduction:Vaccines are a cornerstone of global health,with their efficacy and safety dependent on appropriate dosage determination.Early-phase vaccination trials face significant challenges due to minimal toxicity and nonmonotonic dose response curves,creating a major obstacle in vaccine development.To address this gap,we propose a novel Bayesian phase I/II trial design for dose response curves exhibiting plateau or unimodal patterns to identify the optimal biological dose(OBD),effectively balancing efficacy and toxicity.Methods:We employ a logistic dose-efficacy design that makes dose-escalation and de-escalation decisions while simultaneously considering both efficacy and safety parameters.Extensive simulation studies evaluate the performance of this design.Results:Comparative analyses with commonly used vaccine dose-finding designs demonstrate that our method excels in identifying the optimal toxicityefficacy trade-off,offering both simplicity and accuracy.Sensitivity analyses across various prior settings confirm the robustness and efficiency of our approach.Additionally,our design provides a userfriendly framework for clinicians,with superior operating performance compared to existing designs,particularly in terms of accuracy and robustness.Discussion:Our innovative Bayesian design represents a significant advancement in addressing the inherent challenges of early-phase vaccination clinical trials,offering improved accuracy and efficacy in vaccine dosage determination.展开更多
基金Supported by the National Natural Science Foundation of China(Project Nos.82404383 to Mengyi Lu,82173620 and 82373690 to Yang Zhao,82204156 to Dongfang You,and 82473732 to Fang Shao).
文摘Introduction:Vaccines are a cornerstone of global health,with their efficacy and safety dependent on appropriate dosage determination.Early-phase vaccination trials face significant challenges due to minimal toxicity and nonmonotonic dose response curves,creating a major obstacle in vaccine development.To address this gap,we propose a novel Bayesian phase I/II trial design for dose response curves exhibiting plateau or unimodal patterns to identify the optimal biological dose(OBD),effectively balancing efficacy and toxicity.Methods:We employ a logistic dose-efficacy design that makes dose-escalation and de-escalation decisions while simultaneously considering both efficacy and safety parameters.Extensive simulation studies evaluate the performance of this design.Results:Comparative analyses with commonly used vaccine dose-finding designs demonstrate that our method excels in identifying the optimal toxicityefficacy trade-off,offering both simplicity and accuracy.Sensitivity analyses across various prior settings confirm the robustness and efficiency of our approach.Additionally,our design provides a userfriendly framework for clinicians,with superior operating performance compared to existing designs,particularly in terms of accuracy and robustness.Discussion:Our innovative Bayesian design represents a significant advancement in addressing the inherent challenges of early-phase vaccination clinical trials,offering improved accuracy and efficacy in vaccine dosage determination.
