Wang Sue-Jane, Hung H M James, O'Neill Robert T
Office of Biostatistics, Office of Pharmacoepidemiology and Statistical Science, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 20993, USA.
Pharm Stat. 2006 Apr-Jun;5(2):85-97. doi: 10.1002/pst.217.
Traditionally, in clinical development plan, phase II trials are relatively small and can be expected to result in a large degree of uncertainty in the estimates based on which Phase III trials are planned. Phase II trials are also to explore appropriate primary efficacy endpoint(s) or patient populations. When the biology of the disease and pathogenesis of disease progression are well understood, the phase II and phase III studies may be performed in the same patient population with the same primary endpoint, e.g. efficacy measured by HbA1c in non-insulin dependent diabetes mellitus trials with treatment duration of at least three months. In the disease areas that molecular pathways are not well established or the clinical outcome endpoint may not be observed in a short-term study, e.g. mortality in cancer or AIDS trials, the treatment effect may be postulated through use of intermediate surrogate endpoint in phase II trials. However, in many cases, we generally explore the appropriate clinical endpoint in the phase II trials. An important question is how much of the effect observed in the surrogate endpoint in the phase II study can be translated into the clinical effect in the phase III trial. Another question is how much of the uncertainty remains in phase III trials. In this work, we study the utility of adaptation by design (not by statistical test) in the sense of adapting the phase II information for planning the phase III trials. That is, we investigate the impact of using various phase II effect size estimates on the sample size planning for phase III trials. In general, if the point estimate of the phase II trial is used for planning, it is advisable to size the phase III trial by choosing a smaller alpha level or a higher power level. The adaptation via using the lower limit of the one standard deviation confidence interval from the phase II trial appears to be a reasonable choice since it balances well between the empirical power of the launched trials and the proportion of trials not launched if a threshold lower than the true effect size of phase III trial can be chosen for determining whether the phase III trial is to be launched.
传统上，在临床开发计划中，II期试验规模相对较小，预计会导致基于其规划III期试验的估计存在很大程度的不确定性。II期试验还要探索合适的主要疗效终点或患者群体。当疾病生物学和疾病进展的发病机制被充分理解时，II期和III期研究可以在相同患者群体中以相同的主要终点进行，例如在治疗持续时间至少为三个月的非胰岛素依赖型糖尿病试验中通过糖化血红蛋白（HbA1c）测量疗效。在分子途径尚未明确建立或临床结局终点在短期研究中可能无法观察到的疾病领域，例如癌症或艾滋病试验中的死亡率，治疗效果可能通过在II期试验中使用中间替代终点来推断。然而，在许多情况下，我们通常在II期试验中探索合适的临床终点。一个重要问题是，在II期研究中替代终点观察到的效应有多少能够转化为III期试验中的临床效应。另一个问题是III期试验中还存在多少不确定性。在这项工作中，我们从为规划III期试验而采用II期信息的角度研究设计适应性（而非通过统计检验）的效用。也就是说，我们研究使用各种II期效应大小估计值对III期试验样本量规划的影响。一般来说，如果使用II期试验的点估计值进行规划，建议通过选择较小的α水平或较高的检验效能水平来确定III期试验的样本量。通过使用II期试验一个标准差置信区间的下限进行适应性调整似乎是一个合理的选择，因为如果可以选择一个低于III期试验真实效应大小的阈值来确定是否启动III期试验，那么它在已开展试验的经验检验效能和未开展试验的比例之间取得了很好的平衡。
