Glenny A M, Altman D G, Song F, Sakarovitch C, Deeks J J, D'Amico R, Bradburn M, Eastwood A J
Cochrane Oral Health Group, Dental School, University of Manchester, UK.
Health Technol Assess. 2005 Jul;9(26):1-134, iii-iv. doi: 10.3310/hta9260.
To survey the frequency of use of indirect comparisons in systematic reviews and evaluate the methods used in their analysis and interpretation. Also to identify alternative statistical approaches for the analysis of indirect comparisons, to assess the properties of different statistical methods used for performing indirect comparisons and to compare direct and indirect estimates of the same effects within reviews.
Electronic databases.
The Database of Abstracts of Reviews of Effects (DARE) was searched for systematic reviews involving meta-analysis of randomised controlled trials (RCTs) that reported both direct and indirect comparisons, or indirect comparisons alone. A systematic review of MEDLINE and other databases was carried out to identify published methods for analysing indirect comparisons. Study designs were created using data from the International Stroke Trial. Random samples of patients receiving aspirin, heparin or placebo in 16 centres were used to create meta-analyses, with half of the trials comparing aspirin and placebo and half heparin and placebo. Methods for indirect comparisons were used to estimate the contrast between aspirin and heparin. The whole process was repeated 1000 times and the results were compared with direct comparisons and also theoretical results. Further detailed case studies comparing the results from both direct and indirect comparisons of the same effects were undertaken.
Of the reviews identified through DARE, 31/327 (9.5%) included indirect comparisons. A further five reviews including indirect comparisons were identified through electronic searching. Few reviews carried out a formal analysis and some based analysis on the naive addition of data from the treatment arms of interest. Few methodological papers were identified. Some valid approaches for aggregate data that could be applied using standard software were found: the adjusted indirect comparison, meta-regression and, for binary data only, multiple logistic regression (fixed effect models only). Simulation studies showed that the naive method is liable to bias and also produces over-precise answers. Several methods provide correct answers if strong but unverifiable assumptions are fulfilled. Four times as many similarly sized trials are needed for the indirect approach to have the same power as directly randomised comparisons. Detailed case studies comparing direct and indirect comparisons of the same effect show considerable statistical discrepancies, but the direction of such discrepancy is unpredictable.
Direct evidence from good-quality RCTs should be used wherever possible. Without this evidence, it may be necessary to look for indirect comparisons from RCTs. However, the results may be susceptible to bias. When making indirect comparisons within a systematic review, an adjusted indirect comparison method should ideally be used employing the random effects model. If both direct and indirect comparisons are possible within a review, it is recommended that these be done separately before considering whether to pool data. There is a need to evaluate methods for the analysis of indirect comparisons for continuous data and for empirical research into how different methods of indirect comparison perform in cases where there is a large treatment effect. Further study is needed into when it is appropriate to look at indirect comparisons and when to combine both direct and indirect comparisons. Research into how evidence from indirect comparisons compares to that from non-randomised studies may also be warranted. Investigations using individual patient data from a meta-analysis of several RCTs using different protocols and an evaluation of the impact of choosing different binary effect measures for the inverse variance method would also be useful.
调查系统评价中间接比较的使用频率，并评估其分析和解释中所采用的方法。同时识别用于间接比较分析的替代统计方法，评估用于进行间接比较的不同统计方法的特性，并在系统评价中比较同一效应的直接和间接估计值。
电子数据库。
检索效果综述文摘数据库（DARE），查找涉及随机对照试验（RCT）荟萃分析的系统评价，这些评价报告了直接和间接比较，或仅报告了间接比较。对MEDLINE和其他数据库进行系统综述，以识别已发表的分析间接比较的方法。利用国际卒中试验的数据创建研究设计。在16个中心，使用接受阿司匹林、肝素或安慰剂治疗的患者随机样本进行荟萃分析，其中一半试验比较阿司匹林和安慰剂，另一半比较肝素和安慰剂。使用间接比较方法估计阿司匹林和肝素之间的对比。整个过程重复1000次，并将结果与直接比较结果以及理论结果进行比较。开展了更详细的案例研究，比较同一效应的直接和间接比较结果。
通过DARE识别的综述中，31/327（9.5%）包含间接比较。通过电子检索又识别出另外5篇包含间接比较的综述。很少有综述进行正式分析，一些分析基于对感兴趣治疗组数据的简单相加。识别出的方法学论文很少。发现了一些可使用标准软件应用于汇总数据的有效方法：调整后的间接比较、荟萃回归，对于二元数据，仅为多重逻辑回归（仅固定效应模型）。模拟研究表明，简单方法容易产生偏差，并且给出的答案过于精确。如果满足强但不可验证假设，几种方法可提供正确答案。间接方法要具有与直接随机比较相同的检验效能，所需样本量是直接方法的四倍。比较同一效应直接和间接比较的详细案例研究显示出相当大的统计差异，但这种差异的方向不可预测。
应尽可能使用高质量RCT的直接证据。没有此证据时，可能有必要从RCT中寻找间接比较。然而，结果可能容易产生偏差。在系统评价中进行间接比较时，理想情况下应使用采用随机效应模型的调整间接比较方法。如果在一个综述中既可以进行直接比较也可以进行间接比较，建议在考虑合并数据之前分别进行。需要评估连续数据间接比较分析方法，以及在存在较大治疗效应情况下不同间接比较方法性能的实证研究。需要进一步研究何时适合查看间接比较，以及何时同时结合直接和间接比较。也可能有必要研究间接比较证据与非随机研究证据的比较情况。使用来自几个采用不同方案的RCT荟萃分析的个体患者数据进行调查，以及评估为逆方差法选择不同二元效应测量指标的影响也会很有用。
