Comparison of simple pooling and bivariate model used in meta-analyses of diagnos-tic test accuracy published in Chinese journals
10.3969/j.issn.1671-167X.2015.03.021
- VernacularTitle:简单合并模型与双变量模型在诊断试验Meta分析中的使用现状调查
- Author:
Yuansheng HUANG
;
Zhirong YANG
;
Siyan ZHAN
- Publication Type:Journal Article
- Keywords:
Diagnostic tests,routine;
Meta-analysis;
Models,statistical
- From:
Journal of Peking University(Health Sciences)
2015;(3):483-488
- CountryChina
- Language:Chinese
-
Abstract:
Objective: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. Methods:DTA meta-analyses were searched through Chi-nese Biomedical Literature Database (January to November, 2014). Details in models and data for four-fold 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 re-sults differences were affected by between-study variability of sensitivity and specificity, expressed by I2 , was explored. Results: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%. Conclusion: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.
