利用SAS软件PROC MCMC过程步实现诊断性试验的贝叶斯Meta分析

Bayesian meta-analysis of diagnostic tests using PROC MCMC program in SAS software

目的:介绍利用SAS软件PROC MCMC过程步实现诊断性试验的贝叶斯Meta分析。方法:利用Menke编制的基于SAS PROC MCMC过程步的Meta分析代码,以高分辨率超声诊断颞下颌关节盘前移位准确度的研究作为示例,介绍诊断性试验的贝叶斯Meta分析实施方法。结果:基于实例数据,本文给出了贝叶斯固定效应模型和随机效应模型Meta分析结果。随机效应分析结果显示:高分辨率超声诊断可复性盘前移位的合并敏感度0.852(95%CI:0.766~0.924),合并特异度0.865(95%CI=0.760:0.944),诊断比值比DOR 53.413(95%CI:11.855~170.4)。结论:SAS PROC MCMC是实现敏感性和特异性的双变量随机效应贝叶斯Meta分析的优秀方法。

Objective :To introduce the Bayesian meta-analysis of the diagnostic test using the SAC software PROC MCMC program. Methods :Meta-analysis code based on SAS PROC MCMC program prepared by Menke J was used and the study on the accuracy of high-resolution ultrasound diagnosis of anterior disc displacement of temporomandibular joint published by Dong Xiaoyu et al. was selected as an example data. Bayesian meta-analysis implementation method for diagnostic test was introduced. Results :Based on the example data, the results of Bayesian fixed effect model and random effect model meta-analysis were given. The results of random effects analysis showed that the combined sensitivity, specificity, diagnostic Odds Ratio (DOR)of high-resolution ultrasound diagnosis for anterior disc displacement with reduction (ADDWR) were 0.852 (95%CI: 0.766-0.924), 0.865 (95%CI: 0.760-0.944), 53.413 (95%CI: 11.855-170.4) respectively. Conclusion :SAS PROC MCMC was an excellent method for achieving bivariate random effects Bayesian meta-analysis of sensitivity and specificity.