Wen Hai, Li Pengzhi, Ma Hong, Lv Guohua
Department of Spine Surgery, The Second Xiangya Hospital of Central South University, Changsha, People's Republic of China.
Infect Drug Resist. 2017 Sep 28;10:299-305. doi: 10.2147/IDR.S145843. eCollection 2017.
Xpert MTB/RIF assay, a rapid and automated real-time nucleic acid amplification test, has been reported for the diagnosis of musculoskeletal tuberculosis (TB) in current years. This meta-analysis aims to determine the diagnostic accuracy of Xpert for the detection of musculoskeletal TB and rifampicin (RIF) resistance.
We searched PubMed, Embase, China National Knowledge Infrastructure, and Wanfang for original articles published up to 1st June 2017 to identify studies in which the Xpert assay was applied to diagnose musculoskeletal TB. Pooled estimates were calculated using a random-effects model or a fixed-effects model according to heterogeneity. Summary receiver operating characteristic curves and the area under the curve (AUC) were used to summarize overall diagnostic performance. Deeks' test was performed to evaluate potential publication bias.
Twelve studies were identified with a pooled sensitivity and specificity of respectively 0.81 (95% confidence interval [CI] 0.78-0.83) and 0.83 (95% CI 0.80-0.86) of Xpert for the diagnosis of musculoskeletal TB. Xpert was highly sensitive (0.89, 95% CI 0.79-0.95) and highly specific (0.96, 95% CI 0.92-0.98) in detecting RIF resistance. AUC (over 0.9) suggested a relatively high level of overall diagnostic accuracy of Xpert for detecting musculoskeletal TB and RIF resistance. Prevalence and reference standard were indicated to be sources of heterogeneity between studies. No publication bias was found.
This study provides available evidence of the rapid and effective role of Xpert in diagnosing musculoskeletal TB and detecting RIF resistance.
Xpert MTB/RIF检测是一种快速自动化的实时核酸扩增检测方法，近年来已被报道用于肌肉骨骼结核（TB）的诊断。本荟萃分析旨在确定Xpert检测肌肉骨骼结核及利福平（RIF）耐药性的诊断准确性。
我们检索了PubMed、Embase、中国知网和万方数据库，查找截至2017年6月1日发表的原始文章，以确定应用Xpert检测法诊断肌肉骨骼结核的研究。根据异质性，使用随机效应模型或固定效应模型计算合并估计值。采用汇总的受试者工作特征曲线及曲线下面积（AUC）来总结总体诊断性能。进行Deeks检验以评估潜在的发表偏倚。
共纳入12项研究，Xpert诊断肌肉骨骼结核的合并敏感性和特异性分别为0.81（95%置信区间[CI]0.78 - 0.83）和0.83（95%CI 0.80 - 0.86）。Xpert检测RIF耐药性的敏感性（0.89，95%CI 0.79 - 0.95）和特异性（0.96，95%CI 0.92 - 0.98）均较高。AUC（超过0.9）表明Xpert检测肌肉骨骼结核及RIF耐药性的总体诊断准确性较高。研究间的异质性来源为患病率和参考标准。未发现发表偏倚。
本研究提供了Xpert在诊断肌肉骨骼结核及检测RIF耐药性方面快速有效的作用的现有证据。
