Huang Yuan-sheng, Yang Zhi-rong, Zhan Si-yan
Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.
Center of Postmarketing Safety Evaluation, Peking University Health Science Center,Beijing 100191, China.
Beijing Da Xue Xue Bao Yi Xue Ban. 2015 Jun 18;47(3):483-8.
To investigate the use of simple pooling and bivariate model in meta-analyses of diagnostic test accuracy (DTA) published in Chinese journals (January to November, 2014), compare the differences of results from these two models, and explore the impact of between-study variability of sensitivity and specificity on the differences.
DTA meta-analyses were searched through Chinese Biomedical Literature Database (January to November, 2014). Details in models and data for fourfold table were extracted. Descriptive analysis was conducted to investigate the prevalence of the use of simple pooling method and bivariate model in the included literature. Data were re-analyzed with the two models respectively. Differences in the results were examined by Wilcoxon signed rank test. How the results differences were affected by between-study variability of sensitivity and specificity, expressed by I2, was explored.
The 55 systematic reviews, containing 58 DTA meta-analyses, were included and 25 DTA meta-analyses were eligible for re-analysis. Simple pooling was used in 50 (90.9%) systematic reviews and bivariate model in 1 (1.8%). The remaining 4 (7.3%) articles used other models pooling sensitivity and specificity or pooled neither of them. Of the reviews simply pooling sensitivity and specificity, 41(82.0%) were at the risk of wrongly using Meta-disc software. The differences in medians of sensitivity and specificity between two models were both 0.011 (P<0.001, P=0.031 respectively). Greater differences could be found as I2 of sensitivity or specificity became larger, especially when I2>75%.
Most DTA meta-analyses published in Chinese journals(January to November, 2014) combine the sensitivity and specificity by simple pooling. Meta-disc software can pool the sensitivity and specificity only through fixed-effect model, but a high proportion of authors think it can implement random-effect model. Simple pooling tends to underestimate the results compared with bivariate model. The greater the between-study variance is, the more likely the simple pooling has larger deviation. It is necessary to increase the knowledge level of statistical methods and software for meta-analyses of DTA data.
探讨简单合并法和双变量模型在2014年1月至11月发表于中文期刊的诊断试验准确性（DTA）Meta分析中的应用，比较这两种模型结果的差异，并探讨敏感度和特异度的研究间变异对差异的影响。
通过中国生物医学文献数据库检索2014年1月至11月的DTA Meta分析。提取模型及四格表数据的详细信息。进行描述性分析以调查纳入文献中简单合并法和双变量模型的使用情况。分别用这两种模型重新分析数据。通过Wilcoxon符号秩检验检查结果差异。探讨敏感度和特异度的研究间变异（用I²表示）如何影响结果差异。
纳入55篇系统评价，包含58项DTA Meta分析，25项DTA Meta分析符合重新分析条件。50项（90.9%）系统评价采用简单合并法，1项（1.8%）采用双变量模型。其余4项（7.3%）文章采用其他合并敏感度和特异度的模型或两者均未合并。在仅简单合并敏感度和特异度的评价中，41项（82.0%）有错误使用Meta-disc软件的风险。两种模型间敏感度和特异度中位数的差异均为0.011（P分别<0.001、P = 0.031）。随着敏感度或特异度的I²增大，差异更明显，尤其是当I²>75%时。
2014年1月至11月发表于中文期刊的多数DTA Meta分析通过简单合并法合并敏感度和特异度。Meta-disc软件仅能通过固定效应模型合并敏感度和特异度，但很大比例的作者认为它能实现随机效应模型。与双变量模型相比，简单合并法倾向于低估结果。研究间方差越大，简单合并法出现较大偏差的可能性越大。有必要提高DTA数据Meta分析统计方法和软件的知识水平。
