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拨开统计迷雾:理解和评估非劣效性试验。

Cutting through the statistical fog: understanding and evaluating non-inferiority trials.

机构信息

John H. Ammon Chair, Thomas Jefferson University, Philadelphia, PA, USA.

出版信息

Int J Clin Pract. 2010 Sep;64(10):1359-66. doi: 10.1111/j.1742-1241.2010.02481.x.

Abstract

Every year, results from many important randomised, controlled trials are published. Knowing the elements of trial design and having the skills to critically read and incorporate results are important to medical practitioners. The goal of this article is to help physicians determine the validity of trial conclusions to improve patient care through more informed medical decision making. This article includes a review of 162 randomised, controlled non-inferiority (n = 116) and equivalence (n = 46) hypothesis studies as well as the larger Stroke Prevention using Oral Thrombin Inhibitor in atrial Fibrillation V study and the Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial. Evaluation of data from small and large trials uncovers significant flaws in design and models employed and uncertainty about calculations of statistical measures. As one example of questionable study design, discussion includes a large (n = 3922), double-blind, randomised, multicentre trial comparing the efficacy of ximelagatran with warfarin for prevention of stroke and systemic embolism in patients with non-valvular atrial fibrillation and additional stroke risk factors. Investigators concluded that ximelagatran was effective compared with well-controlled warfarin for prevention of thromboembolism. However, deficiencies in design, as well as concerns about liver toxicity, resulted in the rejection of the drug by the US Food and Drug Administration. Many trials fail to follow good design principles, resulting in conclusions of questionable validity. Well-designed non-inferiority trials can provide valuable data and demonstrate efficacy for beneficial new therapies. Objectives and primary end-points must be clearly stated and rigorous standards met for sample size, establishing the margin, patient characteristics and adherence to protocol.

摘要

每年都有许多重要的随机对照试验结果发表。了解试验设计的要素,并具备批判性阅读和整合结果的技能,对医疗从业者来说非常重要。本文的目的是帮助医生确定试验结论的有效性,通过更明智的医疗决策来改善患者的护理。本文回顾了 162 项随机对照非劣效性(n=116)和等效性(n=46)假设研究,以及较大的 Stroke Prevention using Oral Thrombin Inhibitor in atrial Fibrillation V 研究和 Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial。对小型和大型试验数据的评估揭示了设计和使用模型中的重大缺陷,以及对统计措施计算的不确定性。作为一个有问题的研究设计的例子,讨论包括一项大型(n=3922)、双盲、随机、多中心试验,比较了 ximelagatran 与华法林预防非瓣膜性心房颤动患者的中风和全身性栓塞以及其他中风危险因素的疗效。研究人员得出结论,ximelagatran 与控制良好的华法林相比,在预防血栓栓塞方面是有效的。然而,设计缺陷以及对肝毒性的担忧导致美国食品和药物管理局拒绝了该药物。许多试验未能遵循良好的设计原则,导致结论的有效性值得怀疑。设计良好的非劣效性试验可以提供有价值的数据,并证明有益的新疗法的疗效。目标和主要终点必须明确规定,并严格遵守样本量、建立边界、患者特征和遵守方案的标准。

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