Diagnostic accuracy of Afirma gene expression classifier, Afirma gene sequencing classifier, ThyroSeq v2 and ThyroSeq v3 for indeterminate (Bethesda III and IV) thyroid nodules: a meta-analysis
Author:
Vardarli Irfan1ORCID, Tan Susanne2, Görges Rainer3, Krämer Bernhard K4, Herrmann Ken3, Brochhausen Christoph5
Affiliation:
1. 5th Medical Department, Division of Endocrinology and Diabetes, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany 2. Department of Endocrinology, Diabetes and Metabolism, Clinical Chemistry – Division of Laboratory Research Endocrine Tumor Center at WTZ/Comprehensive Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany 3. Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany 4. 5th Medical Department, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany 5. Institue of Pathology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
Abstract
Objective
The management of thyroid nodules with indeterminate cytology (ITN) is still a challenge. To evaluate the performance of commercial molecular tests for ITN, we performed this comprehensive meta-analysis.
Methods
We performed an electronic search using PubMed/Medline, Embase, and the Cochrane Library. Studies assessing the diagnostic accuracy of Afirma gene expression classifier (GEC), Afirma gene sequencing classifier (GSC), ThyroSeq v2 (TSv2), or ThyroSeq v3 (TSv3) in patients with ITN (only Bethesda category III or IV) were selected; Statistical analyses were performed by using Stata.
Results
Seventy-one samples (GEC, n = 38; GSC, n = 16; TSv2, n = 9; TSv3, n = 8) in 53 studies, involving 6490 fine needle aspirations (FNAs) with ITN cytology with molecular diagnostics (GEC, GSC, TSv2, or TSv3), were included in the study. The meta-analysis showed the following pooled estimates: sensitivity 0.95 (95% CI: 0.94–0.97), specificity 0.35 (0.28–0.43), positive likelihood ratio (LR+) 1.5 (1.3–1.6), and negative likelihood ratio (LR−) 0.13 (0.09–0.19), with the best performance for TSv3 (area under the ROC curve 0.95 (0.93–0.96), followed by TSv2 (0.90 (0.87–0.92)), GSC (0.86 (0.82–0.88)), and GEC (0.82 (0.78–0.85)); the best rule-out property was observed for GSC (LR−, 0.07 (0.02–0.19)), followed by TSv3 (0.11 (0.05–0.24)) and GEC (0.16 (0.10–0.28), and the best rule-in was observed for TSv2 (LR+, 2,9 (1.4–4.6)), followed by GSC (1.9 (1.6–2.4)). A meta-regression analysis revealed that study design, Bethesda category, and type of molecular test were independent factors.
Conclusion
We showed that in patients with ITN, TSv3 has the best molecular diagnostic performance, followed by TSv2, GSC, and GEC. As regards rule-out malignancy, GSC, and rule-in, TSV2 is superior to other tests.
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