Abstract | OBJECTIVE: METHOD: Searched PubMed, Web of Science, Embase and China Biology Medicine (CBM) databases comprehensively from inception to May 2020. The evaluation index were the pooled sensitivity, specificity, diagnosis odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), as well as the area under the summary receiver operating characteristic (SROC) curves. Meta-Disc 1.4 and RevMan 5.3 were used to analyze all statistics. QUADAS-2 tool was applied to evaluate the quality of eligible studies. Subgroup analysis and meta-regression were used to explore the sources of heterogeneity. RESULTS: Nine articles containing eleven records were eligible for this meta-analysis. The pooled sensitivity of 14-3-3η was 0.63 (95% CI: 0.60 to 0.66), the pooled specificity was 0.90 (95% CI: 0.88 to 0.91). The pooled PLR and NLR was 6.10 (95% CI: 4.67 to 7.96) and 0.40 (95% CI: 0.33 to 0.48), respectively. The pooled DOR was 15.90 (95% CI: 11.15 to 22.68), and the area under the curve (AUC) was 0.8696. Compared with a single indicator ( rheumatoid factor or anti-citrullinated protein antibodies), adding 14-3-3η can bring incremental benefits to the diagnosis of RA. The results of subgroup analysis and meta-regression suggested that the two factors (ethnicity, early vs established RA) we analyzed might not be the source of heterogeneity (P value were 0.0979 and 0.4298, respectively) and there was no publication bias among these articles (P = .42). CONCLUSION:
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Authors | Yue Wu, Ziwei Dai, Haili Wang, Hong Wang, Lingling Wu, Huayun Ling, Ying Zhu, Dongqing Ye, Bin Wang |
Journal | Immunological investigations
(Immunol Invest)
Vol. 51
Issue 1
Pg. 182-198
(Jan 2022)
ISSN: 1532-4311 [Electronic] England |
PMID | 32967487
(Publication Type: Journal Article, Meta-Analysis)
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Chemical References |
- Anti-Citrullinated Protein Antibodies
- Biomarkers
- Rheumatoid Factor
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Topics |
- Anti-Citrullinated Protein Antibodies
- Arthritis, Rheumatoid
(diagnosis)
- Biomarkers
- Humans
- ROC Curve
- Rheumatoid Factor
- Sensitivity and Specificity
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