Phase II clinical trials are commonly conducted as pilot studies to evaluate the efficacy and safety of the investigational drug in the targeted patient population with the disease or condition to be treated or preven...Phase II clinical trials are commonly conducted as pilot studies to evaluate the efficacy and safety of the investigational drug in the targeted patient population with the disease or condition to be treated or prevented.When designing such a trial considering efficacy conclusions,people natu-rally think as follows:if efficacy evidence is very strong,a go decision should be made;if efficacy evidence is very weak,a no-go decision should be made;if the efficacy evidence is neither strong nor weak,no decision can be made(inconclusive).The designs presented in this paper match this natural thinking process with go/no-go/inconclusive outcomes.Both two-/three-stage designs are developed with three outcomes.Additionally,a general approach based on conditional error function is implemented such that new decision boundaries can be calculated to handle mid-course sample size change which results in either‘over-running’or‘under-running’and ensure the control of overall type I error.A free open-source R package tsdf that calculates the proposed two-/three-stage designs is available on CRAN.展开更多
We propose a new two-/three-stage dose-finding design called Target Toxicity(TT)for phase Ⅰ clinical trials,where we link the decision rules in the dose-finding process with the conclusions from a hypothesis test.The...We propose a new two-/three-stage dose-finding design called Target Toxicity(TT)for phase Ⅰ clinical trials,where we link the decision rules in the dose-finding process with the conclusions from a hypothesis test.The power to detect excessive toxicity is also given.This solves the problem of why the minimal number of patients is needed for the selected dose level.Our method provides a statistical explanation of traditional‘3+3’design using frequentist framework.The proposed method is very flexible and it incorporates other interval-based decision rules through different parameter settings.We provide the decision tables to guide investigators when to decrease,increase or repeat a dose for next cohort of subjects.Simulation experiments were conducted to compare the performance of the proposed method with other dose-finding designs.A free open source R package tsdf is available on CRAN.It is dedicated to deriving two-/three-stage design decision tables and perform dose-finding simulations.展开更多
文摘Phase II clinical trials are commonly conducted as pilot studies to evaluate the efficacy and safety of the investigational drug in the targeted patient population with the disease or condition to be treated or prevented.When designing such a trial considering efficacy conclusions,people natu-rally think as follows:if efficacy evidence is very strong,a go decision should be made;if efficacy evidence is very weak,a no-go decision should be made;if the efficacy evidence is neither strong nor weak,no decision can be made(inconclusive).The designs presented in this paper match this natural thinking process with go/no-go/inconclusive outcomes.Both two-/three-stage designs are developed with three outcomes.Additionally,a general approach based on conditional error function is implemented such that new decision boundaries can be calculated to handle mid-course sample size change which results in either‘over-running’or‘under-running’and ensure the control of overall type I error.A free open-source R package tsdf that calculates the proposed two-/three-stage designs is available on CRAN.
文摘We propose a new two-/three-stage dose-finding design called Target Toxicity(TT)for phase Ⅰ clinical trials,where we link the decision rules in the dose-finding process with the conclusions from a hypothesis test.The power to detect excessive toxicity is also given.This solves the problem of why the minimal number of patients is needed for the selected dose level.Our method provides a statistical explanation of traditional‘3+3’design using frequentist framework.The proposed method is very flexible and it incorporates other interval-based decision rules through different parameter settings.We provide the decision tables to guide investigators when to decrease,increase or repeat a dose for next cohort of subjects.Simulation experiments were conducted to compare the performance of the proposed method with other dose-finding designs.A free open source R package tsdf is available on CRAN.It is dedicated to deriving two-/three-stage design decision tables and perform dose-finding simulations.
