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The performance of biased-coin minimization in multicenter randomized clinical trials

机译：偏向硬币最小化在多中心随机临床试验中的表现

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摘要

Randomized clinical trials (RCTs) are widely used as the gold standard for comparative medical studies. Using randomization to determine treatment assignment assures that all patients have the same chance of being assigned to each treatment group and that the treatment groups are comparable in terms of the distributions of prognostic factors. When treatment groups are not comparable, the power of statistical test will be decreased. Moreover, the problem of imbalance becomes more notable when it occurs in the important prognostic factors because it could result in a significant bias when assessing differences by treatment group. udThe most intuitive and simple form of randomization is complete randomization. However, with complete randomization there is still a chance for an imbalance on prognostic factors. In order to overcome the problem of imbalance when using complete randomization, restricted randomization procedures were proposed. However, some have argued that an unintended consequence of the restrictions placed on randomization is that they could create patterns that allow for the prediction of future treatment allocation. Furthermore, some have questioned the accuracy of model-based statistical inference using conventional asymptotic test under restrictions placed on the treatment allocation.udThis dissertation is concerned with an assessment of the performance of biased-coin minimization. The assessment is twofold. The first aspect is to determine in terms of balancing properties and also in terms of the probability of predicting treatment assignment when using biased-coin minimization. The second aspect is to compare the results from the classical statistical test, log-rank test, based on population model and the randomization test from the randomization model while biased-coin minimization is applied. udRandomized clinical trials are the gold standard of research for demonstrating the efficacy of therapies used to treat patients in the general community. Allocation methods that promote balance in key prognostic factors between treatment groups are important to assure the accuracy and validity of results from clinical trials. It is important to assess the properties of dynamic allocation methods to demonstrate the validity of these methods as they are applied in research that is designed to develop treatments that are used to enhance the public health. ud
机译：随机临床试验（RCT）被广泛用作比较医学研究的金标准。使用随机化确定治疗分配可确保所有患者被分配到每个治疗组的机会相同，并且治疗组在预后因素的分布方面具有可比性。当治疗组无法比较时，统计检验的功效将降低。此外，当不平衡发生在重要的预后因素中时，不平衡的问题变得更加明显，因为在按治疗组评估差异时，它可能导致明显的偏差。 ud最直观，最简单的随机形式是完全随机。但是，通过完全随机化，预后因素仍然有可能失衡。为了克服使用完全随机化时的不平衡问题，提出了受限的随机化程序。但是，有些人认为，对随机化施加限制的意外结果是，他们可能会创建允许预测未来治疗分配的模式。此外，一些人质疑在治疗分配受到限制的情况下使用常规渐近检验进行基于模型的统计推断的准确性。 ud本论文涉及对偏向硬币最小化性能的评估。评估是双重的。第一个方面是根据平衡特性以及使用偏向硬币最小化时预测治疗方案分配的可能性来确定。第二方面是比较采用人口模型的经典统计检验，对数秩检验和采用有偏硬币最小化方法的随机模型的随机检验结果。 ud随机临床试验是证明在一般社区中用于治疗患者的疗法功效的研究的金标准。促进治疗组之间关键预后因素平衡的分配方法对于确保临床试验结果的准确性和有效性很重要。重要的是评估动态分配方法的属性，以证明这些方法的有效性，因为它们被用于旨在开发用于增强公共卫生的治疗方法的研究中。 ud

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    Tu Li-Chuan;

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