Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews.
Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews.
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DOI：
10.1093/ije/dys041
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发表时间：
2012-06
影响因子：
7.7
通讯作者：
Higgins JP
中科院分区：
文献类型：
--
作者：
Turner RM;Davey J;Clarke MJ;Thompson SG;Higgins JP
许多荟萃分析只包含少量的研究，这使得很难估计研究间异质性的程度。贝叶斯荟萃分析允许纳入异质性的外部证据，并提供了传统的随机效应荟萃分析的优势。为了帮助这一点，我们提供了经验证据的异质性在特定领域的医疗保健的可能程度。方法我们的分析包括来自科克伦系统评价数据库的14 886篇荟萃分析。我们根据结果类型、干预比较类型和医学专业对每个荟萃分析进行分类。通过同时对所有荟萃分析的研究数据进行建模，使用对数比值比量表，我们研究了荟萃分析特征对基础研究间异质性方差的影响。获得了未来荟萃分析中预期异质性的预测分布。结果：荟萃分析结果为全因死亡率的研究间异质性方差平均为其他结果方差的17%（95%CI 10-26）。在比较两种活性药物干预的荟萃分析中，非药物干预的异质性平均为方差的75%（95% CI 58-95）。发现荟萃分析的规模对异质性只有很小的影响。预测分布呈现为九种不同的设置，定义的结果类型和类型的干预比较。例如，对于一项比较药物干预与安慰剂或对照的计划荟萃分析，其结果是主观测量的，异质性的预测分布是对数正态（-2.13，1.582）分布，其中位数为0.12。在6项研究的荟萃分析中，合并外部证据导致联合干预效应的异质性估计值较小，置信区间较窄。结论：荟萃分析特征与研究间异质性程度密切相关，异质性的预测分布在不同环境中差异很大。提供的信息先验将是非常有益的，在未来的荟萃分析，包括一些研究。
Background Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care. Methods Our analyses included 14 886 meta-analyses from the Cochrane Database of Systematic Reviews. We classified each meta-analysis according to the type of outcome, type of intervention comparison and medical specialty. By modelling the study data from all meta-analyses simultaneously, using the log odds ratio scale, we investigated the impact of meta-analysis characteristics on the underlying between-study heterogeneity variance. Predictive distributions were obtained for the heterogeneity expected in future meta-analyses. Results Between-study heterogeneity variances for meta-analyses in which the outcome was all-cause mortality were found to be on average 17% (95% CI 10–26) of variances for other outcomes. In meta-analyses comparing two active pharmacological interventions, heterogeneity was on average 75% (95% CI 58–95) of variances for non-pharmacological interventions. Meta-analysis size was found to have only a small effect on heterogeneity. Predictive distributions are presented for nine different settings, defined by type of outcome and type of intervention comparison. For example, for a planned meta-analysis comparing a pharmacological intervention against placebo or control with a subjectively measured outcome, the predictive distribution for heterogeneity is a log-normal (−2.13, 1.582) distribution, which has a median value of 0.12. In an example of meta-analysis of six studies, incorporating external evidence led to a smaller heterogeneity estimate and a narrower confidence interval for the combined intervention effect. Conclusions Meta-analysis characteristics were strongly associated with the degree of between-study heterogeneity, and predictive distributions for heterogeneity differed substantially across settings. The informative priors provided will be very beneficial in future meta-analyses including few studies.
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DOI：
10.1111/j.1467-985x.2008.00547.x
发表时间：
2009-01
期刊：
Journal of the Royal Statistical Society. Series A, (Statistics in Society)
影响因子：
--
作者：
Turner RM;Spiegelhalter DJ;Smith GC;Thompson SG
通讯作者：
Thompson SG
影响因子：
2
作者：
Pullenayegum, Eleanor M.
通讯作者：
Pullenayegum, Eleanor M.
影响因子：
2
作者：
Viechtbauer, Wolfgang
通讯作者：
Viechtbauer, Wolfgang
DOI：
10.1016/0197-2456(86)90046-2
发表时间：
1986-09-01
期刊：
CONTROLLED CLINICAL TRIALS
影响因子：
--
作者：
DERSIMONIAN, R;LAIRD, N
通讯作者：
LAIRD, N
影响因子：
2
作者：
Lambert, PC;Sutton, AJ;Jones, DR
通讯作者：
Jones, DR