治疗干预的间接比较。

Ben Schöttker, Dagmar Lühmann, Dalila Boulkhemair, Heiner Raspe
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引用次数: 13

摘要

卫生政治背景:卫生技术有效性的比较不仅在德国法律中有规定(社会法典第V卷第139节和第35b节),而且也是临床指导方针和卫生保健决策的核心要素。因此,支持决策的工具(例如卫生技术评估)需要一套有效的方法汇编来进行这些比较。科学背景:直接比较不同疗法效果的随机对照头对头试验被认为是比较干预措施疗效的黄金标准方法。由于这种类型的试验很少被发现,疗效的比较通常需要依赖于间接比较,其有效性一直存在争议。研究问题:当前评估的研究问题是:存在哪些(统计)方法用于治疗干预的间接比较,它们的应用频率有多高,它们的结果与正面试验的结果相比有多有效?方法:在系统文献研究中,检索德国医学文献与信息研究所(DIMDI)的所有医学数据库,检索方法学论文以及在系统评价中间接比较的应用。文献分析的结果定性地总结了方法的特征,定量地总结了它们的应用频率。间接比较结果的有效性是通过将它们与金标准的结果进行比较来检验的——直接比较。使用直接和间接比较的系统评价的数据集通过z统计量的一致性进行测试。结果:分析了29篇方法学论文和106篇间接方法在系统评价中的应用。可以确定四种间接比较方法:未经调整的间接比较包括,独立于任何比较者,所有随机对照试验(RCT),提供感兴趣的干预研究组。调整后的间接比较和元回归分析只包括那些为一个研究组提供感兴趣的干预措施,而另一个研究组提供共同比较物的研究。虽然上述方法使用传统的元分析技术,但混合处理比较(MTC)使用贝叶斯统计。他们能够同时分析具有多个比较器的复杂RCT网络。1999 - 2008年期间,调整后的间接比较是最常用的间接比较方法。自2006年以来,观察到在方法上更具挑战性的MTC的应用有所增加。对于有效性检查,有248个数据集,其中包括直接和间接比较的结果。在未调整的间接比较中,统计上显著差异的比例最大(25.5% [95% CI: 13.1%;38%]),然后进行元回归分析(16.7% [95% CI: - 13.2%;46,5%]),校正间接比较(12.1% [95% CI: 6,1%;18%])和MTC (1,8% [95% CI: -1,7%;5 2%)。如果间接比较的基本假设——研究间的同质性——不成立,则主要检测出差异结果。然而,在本样本中没有观察到任何间接比较方法对直接比较结果的系统性高估或低估。讨论:选择一种适当的方法进行间接比较必须考虑到其有效性、要比较的干预措施的数量以及现有研究的质量和数量。与直接比较的结果相比,未经调整的间接比较提供了低效度。在某些情况下,调整后的间接比较和MTC可能会给出与直接比较结果一致的结果。利用元回归分析进行间接比较的现有综述数量有限,目前禁止对该方法进行实证评估。结论/建议:考虑到主要的先决条件——一组同质和高质量的随机对照试验——头对头试验的结果可以通过调整后的间接比较或MTC进行预估。在HTA和指南制定的背景下,如果缺乏对感兴趣的干预措施的直接比较,它们是有价值的工具。
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Indirect comparisons of therapeutic interventions.

Health political background: The comparison of the effectiveness of health technologies is not only laid down in German law (Social Code Book V, § 139 and § 35b) but also constitutes a central element of clinical guidelines and decision making in health care. Tools supporting decision making (e. g. Health Technology Assessments (HTA)) are therefore in need of a valid methodological repertoire for these comparisons.

Scientific background: Randomised controlled head-to-head trials which directly compare the effects of different therapies are considered the gold standard methodological approach for the comparison of the efficacy of interventions. Because this type of trial is rarely found, comparisons of efficacy often need to rely on indirect comparisons whose validity is being controversially debated.

Research questions: RESEARCH QUESTIONS FOR THE CURRENT ASSESSMENT ARE: Which (statistical) methods for indirect comparisons of therapeutic interventions do exist, how often are they applied and how valid are their results in comparison to the results of head-to-head trials?

Methods: In a systematic literature research all medical databases of the German Institute of Medical Documentation and Information (DIMDI) are searched for methodological papers as well as applications of indirect comparisons in systematic reviews. Results of the literature analysis are summarized qualitatively for the characterisation of methods and quantitatively for the frequency of their application. The validity of the results from indirect comparisons is checked by comparing them to the results from the gold standard - a direct comparison. Data sets from systematic reviews which use both direct and indirect comparisons are tested for consistency by of the z-statistic.

Results: 29 methodological papers and 106 applications of indirect methods in systematic reviews are being analysed. Four methods for indirect comparisons can be identified: Unadjusted indirect comparisons include, independent of any comparator, all randomised controlled trials (RCT) that provide a study arm with the intervention of interest. Adjusted indirect comparisons and metaregression analyses include only those studies that provide one study arm with the intervention of interest and another study arm with a common comparator. While the aforementioned methods use conventional metaanalytical techniques, Mixed treatment comparisons (MTC) use Bayesian statistics. They are able to analyse a complex network of RCT with multiple comparators simultaneously. During the period from 1999 to 2008 adjusted indirect comparisons are the most commonly used method for indirect comparisons. Since 2006 an increase in the application of the more methodologically challenging MTC is being observed. For the validity check 248 data sets, which include results of a direct and an indirect comparison, are available. The share of statistically significant discrepant results is greatest in the unadjusted indirect comparisons (25,5% [95% CI: 13,1%; 38%]), followed by metaregression analyses (16,7% [95% CI: -13,2%; 46,5%]), adjusted indirect comparisons (12,1% [95% CI: 6,1%; 18%]) and MTC (1,8% [95% CI: -1,7%; 5,2%]). Discrepant results are mainly detected if the basic assumption for an indirect comparison - between-study homogeneity - does not hold. However a systematic over- or underestimation of the results of direct comparisons by any of the indirectly comparing methods was not observed in this sample.

Discussion: The selection of an appropriate method for an indirect comparison has to account for its validity, the number of interventions to be compared and the quality as well as the quantity of available studies. Unadjusted indirect comparisons provide, contrasted with the results of direct comparisons, a low validity. Adjusted indirect comparisons and MTC may, under certain circumstances, give results which are consistent with the results of direct comparisons. The limited number of available reviews utilizing metaregression analyses for indirect comparisons currently prohibits empirical evaluation of this methodology.

Conclusions/recommendations: Given the main prerequisite - a pool of homogenous and high-quality RCT - the results of head-to-head trials may be pre-estimated by an adjusted indirect comparison or a MTC. In the context of HTA and guideline development they are valuable tools if there is a lack of a direct comparison of the interventions of interest.

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