Schöttker Ben, Lühmann Dagmar, Boulkhemair Dalila, Raspe Heiner
Institut für Sozialmedizin, Universität zu Lübeck, Lübeck, Deutschland.
GMS Health Technol Assess. 2009 Jul 21;5:Doc09. doi: 10.3205/hta000071.
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.
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 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?
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.
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.
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.
健康技术有效性的比较不仅在德国法律（《社会法典》第五卷，第139条和第35b条）中有规定，也是临床指南及医疗保健决策的核心要素。因此，支持决策的工具（如卫生技术评估（HTA））需要有用于这些比较的有效方法。
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金标准方法。由于这类试验很少见，疗效比较往往需要依赖间接比较，但其有效性存在争议。
本次评估的研究问题是：存在哪些用于治疗性干预间接比较的（统计）方法，它们的应用频率如何，与头对头试验的结果相比其结果的有效性如何？
在一项系统的文献研究中，搜索了德国医学文献与信息研究所（DIMDI）的所有医学数据库，以查找方法学论文以及间接比较在系统评价中的应用。对文献分析结果进行定性总结以描述方法特点，进行定量总结以统计其应用频率。通过将间接比较的结果与金标准（直接比较）的结果进行比较，来检验间接比较结果的有效性。对同时使用直接和间接比较的系统评价数据集，用z统计量检验其一致性。
正在分析29篇方法学论文以及106项间接方法在系统评价中的应用。可识别出四种间接比较方法：未调整的间接比较，不考虑任何对照物，包括所有为感兴趣的干预措施提供研究组的随机对照试验（RCT）。调整后的间接比较和Meta回归分析仅包括那些为感兴趣的干预措施提供一个研究组，为另一个研究组提供共同对照物的研究。虽然上述方法使用传统的Meta分析技术，但混合治疗比较（MTC）使用贝叶斯统计。它们能够同时分析具有多个对照物的复杂RCT网络。在1999年至2008年期间，调整后的间接比较是间接比较中最常用的方法。自2006年以来，观察到方法学上更具挑战性的MTC的应用有所增加。为进行有效性检验，有248个包含直接和间接比较结果的数据集。在未调整的间接比较中，统计学上显著不一致结果的比例最高（25.5% [95% CI：13.1%；38%]），其次是Meta回归分析（16.7% [95% CI：-13.2%；46.5%]）、调整后的间接比较（12.1% [95% CI：6.1%；18%]）和MTC（1.8% [95% CI：-1.7%；5.2%]）。不一致结果主要在间接比较的基本假设——研究间同质性——不成立时被检测到。然而，在该样本中未观察到任何间接比较方法对直接比较结果进行系统性高估或低估的情况。
选择合适的间接比较方法必须考虑其有效性、要比较的干预措施数量以及现有研究的质量和数量。与直接比较的结果相比，未调整的间接比较有效性较低。在某些情况下，调整后的间接比较和MTC可能得出与直接比较结果一致的结果。目前利用Meta回归分析进行间接比较的可用综述数量有限，禁止对该方法进行实证评估。
结论/建议：鉴于主要前提条件——一组同质且高质量的RCT——可以通过调整后的间接比较或MTC预先估计头对头试验的结果。在HTA和指南制定的背景下，如果缺乏对感兴趣干预措施的直接比较，它们是有价值的工具。
