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
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.
