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Observational studies of treatment effectiveness: worthwhile or worthless?

机译:治疗效果的观察性研究:值得还是不值得?

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摘要

Observational studies which evaluate effectiveness are often viewed with skepticism owing to the fact that patients are not randomized to treatment, meaning that results are more prone to bias. Therefore, randomized controlled trials remain the gold standard for evaluating treatment effectiveness. However, it is not always possible to conduct randomized trials. This may be due to financial constraints, for example, in identifying funding for a randomized trial for medicines that have already gained market authorization. There can also be challenges with recruitment, for example, of people with rare conditions or in hard-to-reach population subgroups. This is why observational studies are still needed. In this manuscript, we discuss how researchers can mitigate the risk of bias in the most common type of observational study design for evaluation of treatment effectiveness, the cohort study. We outline some key issues that warrant careful consideration at the outset when the question is being developed and the cohort study is being designed. We focus our discussion on the importance of deciding when to start follow-up in a study, choosing a comparator, managing confounding and measuring outcomes. We also illustrate the application of these considerations in a more detailed case study based on an examination of comparative effectiveness of two antidiabetic treatments using data collected during routine clinical practice.
机译:由于患者并非随机接受治疗,因此评估疗效的观察性研究经常被怀疑,这意味着结果更容易产生偏差。因此,随机对照试验仍然是评估治疗效果的金标准。但是,并非总是可能进行随机试验。这可能是由于财务方面的限制,例如,在为已经获得市场授权的药品的随机试验确定资金时。招募工作也可能会遇到挑战,例如,条件极差的人或难以接触的人群中的人。这就是为什么仍需要观察研究的原因。在本手稿中,我们讨论研究人员如何在最常见的观察性研究设计中减轻偏倚风险,以评估治疗效果,即队列研究。我们概述了一些关键问题,这些问题需要在开发问题和设计队列研究时一开始就进行仔细考虑。我们将讨论的重点放在确定何时开始研究的随访,选择比较者,管理混淆和评估结果的重要性上。我们还将根据常规临床实践中收集的数据,对两种抗糖尿病药物的相对有效性进行检查,从而在更详细的案例研究中说明这些考虑因素的应用。

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