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建立在沙滩上的随机试验:慢性阻塞性肺疾病、激素治疗和癌症的实例

Randomized Trials Built on Sand: Examples from COPD, Hormone Therapy, and Cancer.

作者信息

Suissa Samy

机构信息

Center for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, and Departments of Epidemiology and Biostatistics, and of Medicine, McGill University, Montreal, Canada.

出版信息

Rambam Maimonides Med J. 2012 Jul 31;3(3):e0014. doi: 10.5041/RMMJ.10082. Print 2012 Jul.

Abstract

The randomized controlled trial is the fundamental study design to evaluate the effectiveness of medications and receive regulatory approval. Observational studies, on the other hand, are essential to address post-marketing drug safety issues but have also been used to uncover new indications or new benefits for already marketed drugs. Hormone replacement therapy (HRT) for instance, effective for menopausal symptoms, was reported in several observational studies during the 1980s and 1990s to also significantly reduce the incidence of coronary heart disease. This claim was refuted in 2002 by the large-scale Women's Health Initiative randomized trial. An example of a new indication for an old drug is that of metformin, an anti-diabetic medication, which is being hailed as a potential anti-cancer agent, primarily on the basis of several recent observational studies that reported impressive reductions in cancer incidence and mortality with its use. These observational studies have now sparked the conduct of large-scale randomized controlled trials currently ongoing in cancer. We show in this paper that the spectacular effects on new indications or new outcomes reported in many observational studies in chronic obstructive pulmonary disease (COPD), HRT, and cancer are the result of time-related biases, such as immortal time bias, that tend to seriously exaggerate the benefits of a drug and that eventually disappear with the proper statistical analysis. In all, while observational studies are central to assess the effects of drugs, their proper design and analysis are essential to avoid bias. The scientific evidence on the potential beneficial effects in new indications of existing drugs will need to be more carefully assessed before embarking on long and expensive unsubstantiated trials.

摘要

随机对照试验是评估药物疗效并获得监管批准的基础研究设计。另一方面,观察性研究对于解决上市后药物安全问题至关重要,但也被用于发现已上市药物的新适应症或新益处。例如,激素替代疗法(HRT)对更年期症状有效,在20世纪80年代和90年代的几项观察性研究中报告称,它还能显著降低冠心病的发病率。2002年,大规模的妇女健康倡议随机试验反驳了这一说法。一种旧药的新适应症的例子是二甲双胍,一种抗糖尿病药物,主要基于最近的几项观察性研究,这些研究报告称使用它可显著降低癌症发病率和死亡率,它被誉为一种潜在的抗癌药物。这些观察性研究现已引发了目前正在进行的癌症大规模随机对照试验。我们在本文中表明,在慢性阻塞性肺疾病(COPD)、激素替代疗法和癌症的许多观察性研究中报告的对新适应症或新结果的惊人效果是与时间相关的偏差的结果,如不朽时间偏差,这种偏差往往会严重夸大药物的益处,而最终通过适当的统计分析会消失。总之,虽然观察性研究对于评估药物的效果至关重要,但其合理的设计和分析对于避免偏差至关重要。在开展漫长且昂贵的未经证实的试验之前,需要更仔细地评估关于现有药物在新适应症方面潜在有益效果的科学证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd11/3678819/11ca7a9eacf0/rmmj-3-3-e0014_Figure1.jpg

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