Determining optimal sample sizes for multistage adaptive randomized clinical trials from an industry perspective using value of information methods
Determining optimal sample sizes for multistage adaptive randomized clinical trials from an industry perspective using value of information methods
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DOI：
10.1177/1740774512467404
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发表时间：
2013-02-01
期刊：
影响因子：
2.7
通讯作者：
Willan, Andrew R.
中科院分区：
文献类型：
--
作者：
Chen, Maggie H.;Willan, Andrew R.
随机临床试验的样本量通常基于频率论方法，该方法依赖于任意选择的因素，例如I型和II型错误概率以及最小的临床重要差异。作为替代方案，许多作者提出了决策理论（全贝叶斯）方法，通常被称为信息价值方法，试图确定最大化试验预期效用和预期成本之间差异的样本量，称为预期净收益。从行业的角度来看，威兰提出了一个解决方案，其中试验的效用是预期利润的增加。此外，Willan和Kowgier，从社会的角度来看，表明多级设计可以增加预期的净gains.Purpose-本文的目的是确定最佳样本量使用的信息方法的价值，以行业为基础的，多级自适应随机临床试验，并证明预期的净收益实现的增加。在每个阶段结束时，试验的申办者必须在三种行动之间做出决定：继续进行下一阶段，停止试验并寻求监管部门的批准，或停止试验并放弃药物。方法提出了一个预期总利润模型，其中包括考虑每例患者的利润，疾病发生率，时间范围，试验持续时间，市场份额，以及试验结果与监管批准概率之间的关系。所提出的方法扩展到包括多级设计与解决方案提供了一个两阶段的设计。一个例子gived.Results的预期净增益显着增加，实现通过使用多级designs.Limitations的解决方案的复杂性随着级数的增加，虽然更简单的接近最优的解决方案存在。该方法依赖于中心极限定理，假设样本量足够大，从而使相关统计数据呈正态分布。结论从信息价值的角度看，在工业试验中使用多阶段设计会导致预期净收益的显着收益。临床试验2012; 10：54-62。http://ctj.sagepub.com
Background Most often, sample size determinations for randomized clinical trials are based on frequentist approaches that depend on somewhat arbitrarily chosen factors, such as type I and II error probabilities and the smallest clinically important difference. As an alternative, many authors have proposed decision-theoretic (full Bayesian) approaches, often referred to as value of information methods that attempt to determine the sample size that maximizes the difference between the trial's expected utility and its expected cost, referred to as the expected net gain. Taking an industry perspective, Willan proposes a solution in which the trial's utility is the increase in expected profit. Furthermore, Willan and Kowgier, taking a societal perspective, show that multistage designs can increase expected net gain.Purpose The purpose of this article is to determine the optimal sample size using value of information methods for industry-based, multistage adaptive randomized clinical trials, and to demonstrate the increase in expected net gain realized. At the end of each stage, the trial's sponsor must decide between three actions: continue to the next stage, stop the trial and seek regulatory approval, or stop the trial and abandon the drug.Methods A model for expected total profit is proposed that includes consideration of per-patient profit, disease incidence, time horizon, trial duration, market share, and the relationship between trial results and probability of regulatory approval. The proposed method is extended to include multistage designs with a solution provided for a two-stage design. An example is given.Results Significant increases in the expected net gain are realized by using multistage designs.Limitations The complexity of the solutions increases with the number of stages, although far simpler near-optimal solutions exist. The method relies on the central limit theorem, assuming that the sample size is sufficiently large so that the relevant statistics are normally distributed.Conclusion From a value of information perspective, the use of multistage designs in industry trials leads to significant gains in the expected net gain. Clinical Trials 2012; 10: 54-62. http://ctj.sagepub.com