Abrams Keith R, Gillies Clare L, Lambert Paul C
Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, UK.
Stat Med. 2005 Dec 30;24(24):3823-44. doi: 10.1002/sim.2423.
This paper considers the quantitative synthesis of published comparative study results when the outcome measures used in the individual studies and the way in which they are reported varies between studies. Whilst the former difficulty may be overcome, at least to a limited extent, by the use of standardized effects, the latter is often more problematic. Two potential solutions to this problem are; sensitivity analyses and a fully Bayesian approach, in which pertinent external information is included. Both approaches are illustrated using the results of two systematic reviews and meta-analyses which consider the difference in mean change in systolic blood pressure and the difference in physical functioning between an intervention and control group. The two examples illustrate that by adopting a fully Bayesian approach, as opposed to undertaking sensitivity analyses assuming fixed values for unknown parameters, the overall intervention effect can be estimated with greater uncertainty, but that assessing the sensitivity of results to choice of prior distributions in such analyses is crucial.
本文探讨了在个体研究中使用的结果测量指标以及报告方式在不同研究之间存在差异时,已发表的比较研究结果的定量综合问题。虽然前一个困难至少在一定程度上可以通过使用标准化效应来克服,但后一个问题往往更具挑战性。针对这个问题的两种潜在解决方案是:敏感性分析和完全贝叶斯方法,其中包含相关的外部信息。通过两项系统评价和荟萃分析的结果对这两种方法进行了说明,这两项分析考虑了收缩压平均变化的差异以及干预组与对照组之间身体功能的差异。这两个例子表明,与采用假设未知参数为固定值的敏感性分析相反,采用完全贝叶斯方法可以在更大的不确定性下估计总体干预效果,但在此类分析中评估结果对先验分布选择的敏感性至关重要。