Bérard A, Bravo G
McGill University, Department of Epidemiology and Biostatistics, and Centre for Clinical Epidemiology and Community Studies, Jewish General Hospital, Montreal, Quebec, Canada.
J Clin Epidemiol. 1998 Oct;51(10):801-7. doi: 10.1016/s0895-4356(98)00073-0.
This article presents a random effects model that uses effect sizes (ES) and quality scores to integrate results from investigations. An empirical example is given with data obtained from a meta-analysis on the effectiveness of physical activity in the prevention of bone loss in healthy postmenopausal women. A Medline search was performed to locate relevant studies published in French or English between January 1966 and May 1996. Three independent reviewers extracted data from studies. Effect sizes were calculated according to the method of Hedges and Olkin. A modified version of Chalmers' scale was utilized to calculate quality scores. DerSimonian and Laird's method with incorporation of the quality scores was used to estimate the overall effect size. Quality scores and the inverse of the variances were included as weights when combining studies. The overall estimate and standard error (SE) of the effect of physical activity on spinal bone mineral density loss in healthy postmenopausal women was ESoverall = 0.4263 (1.1361). When compared to other meta-analysis methods such as the fixed effects model and the model of DerSimonian and Laird without the quality score (DL), the new model generated comparable estimators (fixed effects model's ESoverall (SE) = 1.2724 (0.0139), DLs ESoverall (SE) = 0.3958 (1.2370)). Due to the heterogeneity that existed between studies, a random effects model was more appropriate then a fixed effects model. However, it resulted in wider confidence intervals, as expected. It was shown empirically that the model using quality scores generated narrower confidence intervals than the model of DL alone. The inclusion of covariates such as quality scores in meta-analyses permits the quantification of the variation between studies.
本文提出了一种随机效应模型，该模型使用效应量（ES）和质量评分来整合各项研究的结果。文中给出了一个实证示例，数据来源于一项关于体育活动对健康绝经后妇女预防骨质流失有效性的荟萃分析。通过检索Medline数据库，查找1966年1月至1996年5月期间发表的法语或英语相关研究。三位独立评审员从研究中提取数据。效应量根据赫奇斯和奥尔金的方法计算。采用查尔默斯量表的修改版来计算质量评分。运用纳入质量评分的德西蒙尼亚和莱尔德方法来估计总体效应量。合并研究时，将质量评分和方差的倒数作为权重。体育活动对健康绝经后妇女脊柱骨矿物质密度损失影响的总体估计值和标准误（SE）为ESoverall = 0.4263（1.1361）。与其他荟萃分析方法（如固定效应模型以及没有质量评分的德西蒙尼亚和莱尔德模型（DL））相比，新模型生成的估计值相当（固定效应模型的ESoverall（SE） = 1.2724（0.0139），DL的ESoverall（SE） = 0.3958（1.2370））。由于研究之间存在异质性,随机效应模型比固定效应模型更合适。然而，正如预期的那样，它导致的置信区间更宽。实证表明，使用质量评分的模型生成的置信区间比单独使用DL模型的置信区间更窄。在荟萃分析中纳入质量评分等协变量能够对研究之间的差异进行量化。
