Irfan Vardarli, Susanne Tan, Rainer Görges, Bernhard K Krämer, Ken Herrmann, Christoph Brochhausen
{"title":"Afirma 基因表达分类器、Afirma 基因测序分类器、ThyroSeq v2 和 ThyroSeq v3 对不确定甲状腺结节(Bethesda III 和 IV)的诊断准确性:一项荟萃分析。","authors":"Irfan Vardarli, Susanne Tan, Rainer Görges, Bernhard K Krämer, Ken Herrmann, Christoph Brochhausen","doi":"10.1530/EC-24-0170","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":11634,"journal":{"name":"Endocrine Connections","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11227067/pdf/","citationCount":"0","resultStr":"{\"title\":\"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.\",\"authors\":\"Irfan Vardarli, Susanne Tan, Rainer Görges, Bernhard K Krämer, Ken Herrmann, Christoph Brochhausen\",\"doi\":\"10.1530/EC-24-0170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":11634,\"journal\":{\"name\":\"Endocrine Connections\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11227067/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Endocrine Connections\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1530/EC-24-0170\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/1 0:00:00\",\"PubModel\":\"Print\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine Connections","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1530/EC-24-0170","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/1 0:00:00","PubModel":"Print","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
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.
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.
期刊介绍:
Endocrine Connections publishes original quality research and reviews in all areas of endocrinology, including papers that deal with non-classical tissues as source or targets of hormones and endocrine papers that have relevance to endocrine-related and intersecting disciplines and the wider biomedical community.