Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Clin Trials. 2013;10(3):430-40. doi: 10.1177/1740774513483934.
Prospective trial design often occurs in the presence of 'acceptable' historical control data. Typically, these data are only utilized for treatment comparison in a posteriori retrospective analysis to estimate population-averaged effects in a random-effects meta-analysis.
We propose and investigate an adaptive trial design in the context of an actual randomized controlled colorectal cancer trial. This trial, originally reported by Goldberg et al., succeeded a similar trial reported by Saltz et al., and used a control therapy identical to that tested (and found beneficial) in the Saltz trial.
The proposed trial implements an adaptive randomization procedure for allocating patients aimed at balancing total information (concurrent and historical) among the study arms. This is accomplished by assigning more patients to receive the novel therapy in the absence of strong evidence for heterogeneity among the concurrent and historical controls. Allocation probabilities adapt as a function of the effective historical sample size (EHSS), characterizing relative informativeness defined in the context of a piecewise exponential model for evaluating time to disease progression. Commensurate priors are utilized to assess historical and concurrent heterogeneity at interim analyses and to borrow strength from the historical data in the final analysis. The adaptive trial's frequentist properties are simulated using the actual patient-level historical control data from the Saltz trial and the actual enrollment dates for patients enrolled into the Goldberg trial.
Assessing concurrent and historical heterogeneity at interim analyses and balancing total information with the adaptive randomization procedure lead to trials that on average assign more new patients to the novel treatment when the historical controls are unbiased or slightly biased compared to the concurrent controls. Large magnitudes of bias lead to approximately equal allocation of patients among the treatment arms. Using the proposed commensurate prior model to borrow strength from the historical data, after balancing total information with the adaptive randomization procedure, provides admissible estimators of the novel treatment effect with desirable bias-variance trade-offs.
Adaptive randomization methods in general are sensitive to population drift and more suitable for trials that initiate with gradual enrollment. Balancing information among study arms in time-to-event analyses is difficult in the presence of informative right-censoring.
The proposed design could prove important in trials that follow recent evaluations of a control therapy. Efficient use of the historical controls is especially important in contexts where reliance on preexisting information is unavoidable because the control therapy is exceptionally hazardous, expensive, or the disease is rare.
前瞻性试验设计通常在存在“可接受”历史对照数据的情况下进行。通常，这些数据仅在后验回顾性分析中用于治疗比较，以在随机效应荟萃分析中估计人群平均效应。
我们提出并研究了一种实际随机对照结直肠癌试验背景下的适应性试验设计。该试验最初由 Goldberg 等人报道，成功地进行了 Saltz 等人报道的类似试验，并且使用了与 Saltz 试验中测试（并发现有益）的相同对照疗法。
拟议的试验实施了一种适应性随机化程序，用于分配患者，旨在平衡研究臂之间的总信息（并发和历史）。这是通过在没有对并发和历史对照存在明显异质性的有力证据的情况下，为更多患者分配接受新疗法来实现的。分配概率作为有效历史样本量（EHSS）的函数进行调整，EHSS 是在评估疾病进展时间的分段指数模型的背景下定义的相对信息量。在中期分析中利用一致的先验来评估历史和并发异质性，并从历史数据中借鉴力量在最终分析中。使用来自 Saltz 试验的实际患者水平历史对照数据和纳入 Goldberg 试验的患者实际入组日期，对适应性试验的频率学性质进行模拟。
在中期分析中评估并发和历史异质性，并通过适应性随机化程序平衡总信息，当历史对照相对于并发对照偏倚或略微偏倚时，会导致试验平均为新疗法分配更多新患者。较大的偏倚幅度会导致治疗臂之间的患者分配大致相等。使用所提出的一致先验模型从历史数据中借鉴力量，在通过自适应随机化程序平衡总信息后，提供了新疗法效果的可接受估计值，并具有理想的偏差方差权衡。
适应性随机化方法通常对群体漂移敏感，更适合于逐渐入组的试验。在存在信息右删失的情况下，在时间事件分析中平衡研究臂之间的信息是困难的。
对于最近评估对照疗法的试验，拟议的设计可能非常重要。在由于对照疗法特别危险、昂贵或疾病罕见而不可避免地依赖现有信息的情况下，有效利用历史对照数据尤为重要。
