Traditional reviews, meta-analyses and pooled analyses in epidemiology
Traditional reviews, meta-analyses and pooled analyses in epidemiology
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DOI：
10.1093/ije/28.1.1
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发表时间：
1999-02-01
影响因子：
7.7
通讯作者：
Friedenreich, C
中科院分区：
文献类型：
--
作者：
Blettner, M;Sauerbrei, W;Friedenreich, C
使用综述文章和荟萃分析已经成为流行病学研究的重要组成部分，主要是为了调和先前进行的结果不一致的研究，许多方法学问题，特别是关于偏倚和荟萃分析的使用仍然存在争议。方法总结流行病学研究资料的四种方法。概述了meta分析的基本原理和使用的统计方法。对这些方法的优点和局限性进行了比较，特别是在研究之间异质性和提供定量风险估计的能力方面。已发表数据的荟萃分析通常不足以计算汇总估计，因为已发表的估计是基于异质人群、不同的研究设计，主要是不同的统计模型。如果单个数据可用于汇总分析，则可以预期更可靠的结果，尽管仍存在一些异质性，但多中心研究的大型前瞻性计划荟萃分析更适合调查小的风险因素，然而这种类型的荟萃分析昂贵且耗时。为了全面评估普通人群中高患病率的危险因素，汇集数据将变得越来越重要。未来的研究需要关注综述方法的不足，特别是在使用不同设计、方法和分析模型的研究组合时可能产生的误差和偏差。
Background The use of review articles and meta-analysis has become an important part of epidemiological research, mainly for reconciling previously conducted studies that have inconsistent results, Numerous methodologic issues particularly with respect to biases and the use of meta-analysis are still controversial.Methods Four methods summarizing data from epidemiological studies are described. The rationale for meta-analysis and the statistical methods used are outlined. The strengths and limitations of these methods are compared particularly with respect to their ability to investigate heterogeneity between studies and to provide quantitative risk estimation.Results Meta-analyses from published data are in general insufficient to calculate a pooled estimate since published estimates are based on heterogeneous populations, different study designs and mainly different statistical models. More reliable results can be expected if individual data are available for a pooled analysis, although some heterogeneity still remains, Large prospective planned meta-analysis of multicentre studies would be preferable to investigate small risk factors, however this type of meta-analysis is expensive and rime-consuming.Conclusion For a full assessment of risk factors with a high prevalence in the general population, pooling of data will become increasingly important. Future research needs to focus on the deficiencies of review methods, in particular, the errors and biases that can be produced when studies are combined that have used different designs, methods and analytic models.