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Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables

机译:适应性浓缩试验设计对应计率,成果测量时间和预后变量的敏感性

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Adaptive enrichment designs involve rules for restricting enrollment to a subset of the population during the course of an ongoing trial. This can be used to target those who benefit from the experimental treatment. Trial characteristics such as the accrual rate and the prognostic value of baseline variables are typically unknown when a trial is being planned; these values are typically assumed based on information available before the trial starts. Because of the added complexity in adaptive enrichment designs compared to standard designs, it may be of special concern how sensitive the trial performance is to deviations from assumptions. Through simulation studies, we evaluate the sensitivity of Type I error, power, expected sample size, and trial duration to different design characteristics. Our simulation distributions mimic features of data from the Alzheimer's Disease Neuroimaging Initiative cohort study, and involve two subpopulations based on a genetic marker. We investigate the impact of the following design characteristics: the accrual rate, the time from enrollment to measurement of a short-term outcome and the primary outcome, and the prognostic value of baseline variables and short-term outcomes. To leverage prognostic information in baseline variables and short-term outcomes, we use a semiparametric, locally efficient estimator, and investigate its strengths and limitations compared to standard estimators. We apply information-based monitoring, and evaluate how accurately information can be estimated in an ongoing trial.
机译:自适应浓缩设计涉及一些规则,这些规则用于在正在进行的试验过程中将注册限制为一部分人口。这可以用来瞄准那些从实验治疗中受益的人。当计划进行试验时,通常不知道诸如基线变量的应计率和预后价值之类的试验特征。通常根据试用开始之前可用的信息来假定这些值。由于自适应浓缩设计与标准设计相比增加了复杂性,因此可能特别需要关注的是试验性能对偏离假设的敏感程度。通过仿真研究,我们评估了I型误差,功效,预期样本量和试验持续时间对不同设计特征的敏感性。我们的模拟分布模仿了阿尔茨海默氏病神经影像学计划队列研究的数据特征,并且涉及基于遗传标记的两个亚群。我们调查以下设计特征的影响:应计率,从入组到测量短期结果和主要结果的时间以及基线变量和短期结果的预后价值。为了在基线变量和短期结果中利用预后信息,我们使用半参数,局部有效的估计量,并与标准估计量相比,研究其优势和局限性。我们应用基于信息的监视,并评估正在进行的试验中可以如何准确估计信息。

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