The role of randomized controlled trials, registries, observational databases in evaluating new interventions

IF 2.2 4区 医学 Q3 HEMATOLOGY
Robert Peter Gale , Mei-Jie Zhang , Hillard M. Lazarus
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引用次数: 0

Abstract

Approaches to comparing safety and efficacy of interventions include analyzing data from randomized controlled trials (RCTs), registries and observational databases (ODBs). RCTs are regarded as the gold standard but data from such trials are sometimes unavailable because a disease is uncommon, because the intervention is uncommon, because of structural limitations or because randomization cannot be done for practical or (seemingly) ethical reasons. There are many examples of an unproved intervention being so widely-believed to be effective that clinical trialists and potential subjects decline randomization. Often, when a RCT is finally done the intervention is proved ineffective or even harmful. These situations are termed medical reversals and are not uncommon [1,2]. There is also the dilemma of when seemingly similar RCTs report discordant conclisions

Data from high-quality registries, especially ODBs can be used when data from RCTs are unavailable but also have limitations. Biases and confounding co-variates may be unknown, difficult or impossible to identify and/or difficult to adjust for adequately. However, ODBs sometimes have large numbers of diverse subjects and often give answers more useful to clinicians than RCTs. Side-by-side comparisons suggest analyses from high-quality ODBs often give similar conclusions from high quality RCTs. Meta-analyses combining data from RCTs, registries and ODBs are sometimes appropriate. We suggest increased use of registries and ODBs to compare efficacy of interventions.

随机对照试验、登记、观察性数据库在评估新干预措施中的作用
比较干预措施的安全性和有效性的方法包括分析来自随机对照试验(rct)、登记和观察数据库(odb)的数据。随机对照试验被视为金标准,但由于疾病不常见、干预措施不常见、结构限制或由于实际或(看似)伦理原因无法进行随机化,有时无法获得此类试验的数据。有许多未经证实的干预措施被广泛认为是有效的,以至于临床试验人员和潜在受试者拒绝随机化。通常,当随机对照试验最终完成时,干预被证明是无效的,甚至是有害的。这些情况被称为医学逆转,并不罕见[1,2]。当看似相似的随机对照试验报告不一致的结论时,也存在两难境地。当随机对照试验的数据不可用但也有局限性时,可以使用来自高质量注册中心的数据,特别是odb。偏差和混杂协变量可能是未知的,难以或不可能识别和/或难以充分调整。然而,odb有时有大量不同的受试者,通常比随机对照试验提供的答案对临床医生更有用。并排比较表明,来自高质量odb的分析往往得出与高质量rct相似的结论。结合随机对照试验、注册表和odb的数据进行meta分析有时是合适的。我们建议增加使用登记处和odb来比较干预措施的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.20
自引率
0.00%
发文量
42
审稿时长
35 days
期刊介绍: Best Practice & Research Clinical Haematology publishes review articles integrating the results from the latest original research articles into practical, evidence-based review articles. These articles seek to address the key clinical issues of diagnosis, treatment and patient management. Each issue follows a problem-orientated approach which focuses on the key questions to be addressed, clearly defining what is known and not known, covering the spectrum of clinical and laboratory haematological practice and research. Although most reviews are invited, the Editor welcomes suggestions from potential authors.
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