Meta-analyses of adverse effects data derived from randomised controlled trials as compared to observational studies: methodological overview.
Meta-analyses of adverse effects data derived from randomised controlled trials as compared to observational studies: methodological overview.
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DOI：
10.1371/journal.pmed.1001026
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发表时间：
2011-05
期刊：
影响因子：
15.8
通讯作者：
Bland M
中科院分区：
文献类型：
--
作者：
Golder S;Loke YK;Bland M
Su Golder 及其同事对荟萃分析进行了概述，以评估随机试验和观察性研究之间对伤害结果风险的估计是否存在差异。他们发现，平均而言，观察性研究概述和随机试验概述之间的风险估计没有差异。关于在不良反应的系统评价中使用随机对照试验（RCT）数据相对于观察数据的相对优点存在相当多的争论。这种荟萃分析的荟萃分析旨在评估与观察性研究的荟萃分析相比，随机对照试验荟萃分析得出的危害估计的一致或分歧程度。除了参考文献检查、联系专家、引文检索以及手动检索重要期刊、会议记录和网站之外，还对十个数据库进行了检索。纳入的研究中，可以使用比值比的比率，将随机对照试验中不良反应（比值比或风险比）的汇总相对测量值与观察性研究中产生的相同不良反应的汇总估计进行直接比较。确定纳入 19 项研究，产生 58 项荟萃分析。与观察性研究相比，RCT 的合并比值比估计为 1.03（95% 置信区间为 0.93-1.15）。与大型研究的差异较小。对称漏斗图表明，随机对照试验数据荟萃分析的风险估计与观察性研究荟萃分析的风险估计之间没有一致的差异。几乎在所有情况下，不同研究设计的荟萃分析对危害的估计有 95% 的置信区间重叠（54/58，93%）。就统计显着性而言，近三分之二（37/58，64%）的结果一致（两项研究均显示显着增加或显着减少，或均显示无显着差异）。只有一项关于一种不良反应的荟萃分析存在相反的统计显着性。本概述的经验证据表明，根据随机对照试验的荟萃分析和观察性研究的荟萃分析得出的干预措施不良反应的风险估计平均没有差异。这表明不良反应的系统评价不应仅限于特定的研究类型。 请参阅本文后面的编辑摘要 每当患者咨询医生时，他们都希望接受的治疗有效且副作用最小。为了确保这一点，所有治疗方法现在都经过详尽的临床研究——精心设计的研究，在人体中测试新的治疗方法和疗法。临床研究主要分为两类：随机对照试验 (RCT) 和观察性或非随机研究。在随机对照试验中，患有特定疾病或病症的患者组被随机分配接受新治疗或对照治疗，并比较两组患者的结果（例如健康状况的改善和特定不良反应的发生）。由于患者是随机选择的，因此两组之间的结果差异可能与治疗相关。在观察性研究中，招募正在接受特定治疗的患者，并将该组的结果与类似的未经治疗的患者组的结果进行比较。由于患者组不是随机选择的，病例和对照之间结果的差异可能是病例之间隐藏的共同特征的结果，而不是与治疗相关（所谓的混杂变量）。尽管来自个别试验和研究的数据很有价值，但通过系统地审查所有证据，然后进行荟萃分析（所谓的循证医学），可以获得有关潜在新疗法的更多信息。系统评价使用预先定义的标准来识别有关治疗的所有研究；荟萃分析是一种统计方法，用于结合多项研究的结果，得出治疗效果（治疗功效）和伤害风险的“汇总估计”。随机对照试验和观察性研究之间的治疗效果估计可能有所不同，但不良反应估计又如何呢？不同的研究设计能否提供一致的伤害风险图景，或者不同研究设计的结果是否差异如此之大，以至于将它们合并在一次审查中毫无意义？在这个包括系统回顾和荟萃分析的方法学概述中，研究人员评估了随机对照试验荟萃分析得出的危害估计与观察性研究荟萃分析得出的估计的一致性程度。研究人员检索了文献数据库和参考文献列表，咨询了专家，并手工检索了各种其他来源的研究，在这些研究中，随机对照试验的不良反应的汇总估计可以直接与观察性研究的相同不良反应的汇总估计进行比较。他们确定了 19 项研究，总共涵盖了 58 种不同的不良反应。几乎在所有情况下，从随机对照试验和观察性研究的荟萃分析中获得的危害估计都有重叠的 95% 置信区间。也就是说，从统计角度来看，对危害的估计是相似的。此外，在近三分之二的病例中，随机对照试验和观察性研究对于治疗是否导致不良反应显着增加、显着减少或没有显着变化（显着变化不太可能偶然发生）达成了一致。最后，研究人员使用荟萃分析计算出，随机对照试验与观察性研究相比的比值比（风险的统计测量）的汇总比为 1.03。该图表明，从随机对照试验数据的荟萃分析中获得的风险估计与从观察性研究数据的荟萃分析中获得的风险估计之间没有一致的差异。该方法学概述的结果表明，从随机对照试验荟萃分析和观察性研究荟萃分析中获得的干预措施不良反应的风险估计平均没有差异。尽管受到其设计的某些方面的限制，这一概述对于对不良反应进行系统评价具有几个重要的意义。特别是，它表明，与其将系统评价局限于某些研究设计，不如评估广泛的研究可能更好。通过这种方式，与评估单一类型的研究相比，有可能在不丧失任何有效性的情况下，对与干预相关的潜在危害建立更完整、更普遍的认识。这样的图片，再加上从系统评价和荟萃分析中获得的治疗效果估计，将有助于临床医生为患者决定最佳治疗方案。请通过此摘要的在线版本访问这些网站：http://dx.doi.org/10.1371/journal.pmed.1001026。美国国立卫生研究院提供临床研究信息；英国国家卫生服务选择网站还有一个关于临床试验和医学研究的页面 Cochrane 协作组织制作并传播卫生保健干预措施的系统评价 Medline Plus 提供有关临床试验的更多信息的链接（英语和西班牙语）
Su Golder and colleagues carry out an overview of meta-analyses to assess whether estimates of the risk of harm outcomes differ between randomized trials and observational studies. They find that, on average, there is no difference in the estimates of risk between overviews of observational studies and overviews of randomized trials. There is considerable debate as to the relative merits of using randomised controlled trial (RCT) data as opposed to observational data in systematic reviews of adverse effects. This meta-analysis of meta-analyses aimed to assess the level of agreement or disagreement in the estimates of harm derived from meta-analysis of RCTs as compared to meta-analysis of observational studies. Searches were carried out in ten databases in addition to reference checking, contacting experts, citation searches, and hand-searching key journals, conference proceedings, and Web sites. Studies were included where a pooled relative measure of an adverse effect (odds ratio or risk ratio) from RCTs could be directly compared, using the ratio of odds ratios, with the pooled estimate for the same adverse effect arising from observational studies. Nineteen studies, yielding 58 meta-analyses, were identified for inclusion. The pooled ratio of odds ratios of RCTs compared to observational studies was estimated to be 1.03 (95% confidence interval 0.93–1.15). There was less discrepancy with larger studies. The symmetric funnel plot suggests that there is no consistent difference between risk estimates from meta-analysis of RCT data and those from meta-analysis of observational studies. In almost all instances, the estimates of harm from meta-analyses of the different study designs had 95% confidence intervals that overlapped (54/58, 93%). In terms of statistical significance, in nearly two-thirds (37/58, 64%), the results agreed (both studies showing a significant increase or significant decrease or both showing no significant difference). In only one meta-analysis about one adverse effect was there opposing statistical significance. Empirical evidence from this overview indicates that there is no difference on average in the risk estimate of adverse effects of an intervention derived from meta-analyses of RCTs and meta-analyses of observational studies. This suggests that systematic reviews of adverse effects should not be restricted to specific study types. Please see later in the article for the Editors' Summary Whenever patients consult a doctor, they expect the treatments they receive to be effective and to have minimal adverse effects (side effects). To ensure that this is the case, all treatments now undergo exhaustive clinical research—carefully designed investigations that test new treatments and therapies in people. Clinical investigations fall into two main groups—randomized controlled trials (RCTs) and observational, or non-randomized, studies. In RCTs, groups of patients with a specific disease or condition are randomly assigned to receive the new treatment or a control treatment, and the outcomes (for example, improvements in health and the occurrence of specific adverse effects) of the two groups of patients are compared. Because the patients are randomly chosen, differences in outcomes between the two groups are likely to be treatment-related. In observational studies, patients who are receiving a specific treatment are enrolled and outcomes in this group are compared to those in a similar group of untreated patients. Because the patient groups are not randomly chosen, differences in outcomes between cases and controls may be the result of a hidden shared characteristic among the cases rather than treatment-related (so-called confounding variables). Although data from individual trials and studies are valuable, much more information about a potential new treatment can be obtained by systematically reviewing all the evidence and then doing a meta-analysis (so-called evidence-based medicine). A systematic review uses predefined criteria to identify all the research on a treatment; meta-analysis is a statistical method for combining the results of several studies to yield “pooled estimates” of the treatment effect (the efficacy of a treatment) and the risk of harm. Treatment effect estimates can differ between RCTs and observational studies, but what about adverse effect estimates? Can different study designs provide a consistent picture of the risk of harm, or are the results from different study designs so disparate that it would be meaningless to combine them in a single review? In this methodological overview, which comprises a systematic review and meta-analyses, the researchers assess the level of agreement in the estimates of harm derived from meta-analysis of RCTs with estimates derived from meta-analysis of observational studies. The researchers searched literature databases and reference lists, consulted experts, and hand-searched various other sources for studies in which the pooled estimate of an adverse effect from RCTs could be directly compared to the pooled estimate for the same adverse effect from observational studies. They identified 19 studies that together covered 58 separate adverse effects. In almost all instances, the estimates of harm obtained from meta-analyses of RCTs and observational studies had overlapping 95% confidence intervals. That is, in statistical terms, the estimates of harm were similar. Moreover, in nearly two-thirds of cases, there was agreement between RCTs and observational studies about whether a treatment caused a significant increase in adverse effects, a significant decrease, or no significant change (a significant change is one unlikely to have occurred by chance). Finally, the researchers used meta-analysis to calculate that the pooled ratio of the odds ratios (a statistical measurement of risk) of RCTs compared to observational studies was 1.03. This figure suggests that there was no consistent difference between risk estimates obtained from meta-analysis of RCT data and those obtained from meta-analysis of observational study data. The findings of this methodological overview suggest that there is no difference on average in the risk estimate of an intervention's adverse effects obtained from meta-analyses of RCTs and from meta-analyses of observational studies. Although limited by some aspects of its design, this overview has several important implications for the conduct of systematic reviews of adverse effects. In particular, it suggests that, rather than limiting systematic reviews to certain study designs, it might be better to evaluate a broad range of studies. In this way, it might be possible to build a more complete, more generalizable picture of potential harms associated with an intervention, without any loss of validity, than by evaluating a single type of study. Such a picture, in combination with estimates of treatment effects also obtained from systematic reviews and meta-analyses, would help clinicians decide the best treatment for their patients. Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001026. The US National Institutes of Health provide information on clinical research; the UK National Health Service Choices Web site also has a page on clinical trials and medical research The Cochrane Collaboration produces and disseminates systematic reviews of health-care interventions Medline Plus provides links to further information about clinical trials (in English and Spanish)
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影响因子：
120.7
作者：
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