Abstract
Currently, an anti-glycopeptidolipid (GPL)-core IgA antibody assay kit for diagnosing Mycobacterium avium complex (MAC) is commercially available. We conducted this systematic review and meta-analysis to reveal the precise diagnostic accuracy of anti-GPL-core IgA antibodies for MAC pulmonary disease (MAC-PD). We systematically searched reports that could provide data for both sensitivity and specificity by anti-GPL-core IgA antibody for clinically diagnosed MAC-PD. Diagnostic test accuracy was estimated using the bivariate model. Of the 257 articles that we had found through primary search, we finally included 16 reports consisted of 1098 reference positive subjects and 2270 reference negative subjects. The diagnostic odds ratio was 24.8 (95% CI 11.6–52.8, I2 = 5.5%) and the area under the hierarchical summary receiver operating characteristic curves was 0.873 (95% CI 0.837–0.913). With a cutoff value of 0.7 U/mL, the summary estimates of sensitivity and specificity were 0.696 (95% CI 0.621–0.761) and 0.906 (95% CI 0.836–0.951), respectively. The positive and negative likelihood ratios were 7.4 (95% CI 4.1–13.8) and 0.34 (95% CI 0.26–0.43), respectively. The demanding clinical diagnostic criteria may be a cause of false positive of the index test. The index test had good overall diagnostic accuracy and was useful to ruling in MAC-PD with the cutoff value.
Highlights
We evaluated the heterogeneity using I2 statistics
Kitada et al reported a number of reports from a hospital, some of which were excluded due to a possible overlap of included subjects
We included 16 reports, comprising 10 full-length articles and six conference abstracts, all of which were written in English (Table 1)[7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22]
Summary
The summary estimates of sensitivity and specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were assessed. The two investigators (YS, NH) independently extracted the data from the original studies. The two investigators (YS, NH) independently scored the seven domains of the Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2)[26]. Following Grimes’s criteria[30], we interpreted PLR in the range of 2–5, 5–10, and >1 0 as representing small, moderate, and large increases of probability when the index test was positive. We used commands of the statistics software R as follows: “madauni” command for DOR, “phm” command for AUC, and “reitsma” command for the HSROC curve and the summary estimates of sensitivity and specificity[32,33]
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