Poulopoulou Stavroula, Karlis Dimitris, Yiannoutsos Constantin T, Dafni Urania
a Department of Statistics , Athens University of Economics and Business , Athens , Greece.
J Biopharm Stat. 2014;24(4):768-84. doi: 10.1080/10543406.2014.900784.
The main goal of a Phase II clinical trial is to decide, whether a particular therapeutic regimen is effective enough to warrant further study. The hypothesis tested by Fleming's Phase II design (Fleming, 1982) is [Formula: see text] versus [Formula: see text], with level [Formula: see text] and with a power [Formula: see text] at [Formula: see text], where [Formula: see text] is chosen to represent the response probability achievable with standard treatment and [Formula: see text] is chosen such that the difference [Formula: see text] represents a targeted improvement with the new treatment. This hypothesis creates a misinterpretation mainly among clinicians that rejection of the null hypothesis is tantamount to accepting the alternative, and vice versa. As mentioned by Storer (1992), this introduces ambiguity in the evaluation of type I and II errors and the choice of the appropriate decision at the end of the study. Instead of testing this hypothesis, an alternative class of designs is proposed in which two hypotheses are tested sequentially. The hypothesis [Formula: see text] versus [Formula: see text] is tested first. If this null hypothesis is rejected, the hypothesis [Formula: see text] versus [Formula: see text] is tested next, in order to examine whether the therapy is effective enough to consider further testing in a Phase III study. For the derivation of the proposed design the exact binomial distribution is used to calculate the decision cut-points. The optimal design parameters are chosen, so as to minimize the average sample number (ASN) under specific upper bounds for error levels. The optimal values for the design were found using a simulated annealing method.
II期临床试验的主要目标是确定一种特定的治疗方案是否足够有效，值得进一步研究。弗莱明II期设计（弗莱明，1982年）所检验的假设是[公式：见原文]对[公式：见原文]，显著性水平为[公式：见原文]，在[公式：见原文]时检验功效为[公式：见原文]，其中[公式：见原文]被选定为代表标准治疗可达到的反应概率，[公式：见原文]的选择使得差异[公式：见原文]代表新治疗的目标改善。这个假设主要在临床医生中造成了一种误解，即拒绝原假设等同于接受备择假设，反之亦然。正如斯托勒（1992年）所提到的，这在I型和II型错误的评估以及研究结束时适当决策的选择中引入了模糊性。与其检验这个假设，不如提出另一类设计，其中两个假设是顺序检验的。首先检验假设[公式：见原文]对[公式：见原文]。如果这个原假设被拒绝，接下来检验假设[公式：见原文]对[公式：见原文]，以便检查该疗法是否足够有效，从而考虑在III期研究中进一步检验。对于所提出设计的推导，使用精确二项分布来计算决策切点。选择最优设计参数，以便在误差水平的特定上限下使平均样本数（ASN）最小化。使用模拟退火方法找到了该设计的最优值。
