Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis
BackgroundThe performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy.ObjectiveComparing diagnostic performance of detecting thyroid cancer among...
| Main Authors: | , , , , , |
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| Format: | Article |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2023.1227339/full |
| _version_ | 1827855199557910528 |
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| author | Longtao Yang Cong Li Zhe Chen Shaqi He Zhiyuan Wang Jun Liu Jun Liu Jun Liu |
| author_facet | Longtao Yang Cong Li Zhe Chen Shaqi He Zhiyuan Wang Jun Liu Jun Liu Jun Liu |
| author_sort | Longtao Yang |
| collection | DOAJ |
| description | BackgroundThe performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy.ObjectiveComparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years.Evidence acquisitionSystematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]). Based on golden diagnostic standard in histopathology and cytology, single meta-analysis was performed to obtain the optimal cut-off value for each system, and then network meta-analysis was conducted on the best risk stratification category in each system.Evidence synthesisThis network meta-analysis included 88 studies with a total of 59,304 nodules. The most accurate risk category thresholds were TR5 for Eu-TIRADS, TR5 for ACR TIRADS, TR4b and above for C-TIRADS, and possible malignancy for S-Detect. At the best thresholds, sensitivity of these systems ranged from 68% to 82% and specificity ranged from 71% to 81%. It identified the highest sensitivity for C-TIRADS TR4b and the highest specificity for ACR TIRADS TR5. However, sensitivity for ACR TIRADS TR5 was the lowest. The diagnostic odds ratio (DOR) and area under curve (AUC) were ranked first in C-TIRADS.ConclusionAmong four ultrasound risk stratification options, this systemic review preliminarily proved that C-TIRADS possessed favorable diagnostic performance for thyroid nodules.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, CRD42022382818. |
| first_indexed | 2024-03-12T11:41:40Z |
| format | Article |
| id | doaj.art-7869139d903144a1a5a651d553f6caa8 |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-03-12T11:41:40Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-7869139d903144a1a5a651d553f6caa82023-08-31T14:53:28ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922023-08-011410.3389/fendo.2023.12273391227339Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysisLongtao Yang0Cong Li1Zhe Chen2Shaqi He3Zhiyuan Wang4Jun Liu5Jun Liu6Jun Liu7Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Radiology, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Radiology, The Second Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Ultrasound, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, ChinaDepartment of Radiology, The Second Xiangya Hospital, Central South University, Changsha, ChinaClinical Research Center for Medical Imaging in Hunan Province, Changsha, ChinaDepartment of Radiology Quality Control Center in Hunan Province, Changsha, ChinaBackgroundThe performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy.ObjectiveComparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years.Evidence acquisitionSystematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]). Based on golden diagnostic standard in histopathology and cytology, single meta-analysis was performed to obtain the optimal cut-off value for each system, and then network meta-analysis was conducted on the best risk stratification category in each system.Evidence synthesisThis network meta-analysis included 88 studies with a total of 59,304 nodules. The most accurate risk category thresholds were TR5 for Eu-TIRADS, TR5 for ACR TIRADS, TR4b and above for C-TIRADS, and possible malignancy for S-Detect. At the best thresholds, sensitivity of these systems ranged from 68% to 82% and specificity ranged from 71% to 81%. It identified the highest sensitivity for C-TIRADS TR4b and the highest specificity for ACR TIRADS TR5. However, sensitivity for ACR TIRADS TR5 was the lowest. The diagnostic odds ratio (DOR) and area under curve (AUC) were ranked first in C-TIRADS.ConclusionAmong four ultrasound risk stratification options, this systemic review preliminarily proved that C-TIRADS possessed favorable diagnostic performance for thyroid nodules.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, CRD42022382818.https://www.frontiersin.org/articles/10.3389/fendo.2023.1227339/fullthyroid imaging reporting and data systemEu-TIRADSACR TIRADSC-TIRADSS-Detectdiagnostic performance |
| spellingShingle | Longtao Yang Cong Li Zhe Chen Shaqi He Zhiyuan Wang Jun Liu Jun Liu Jun Liu Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis Frontiers in Endocrinology thyroid imaging reporting and data system Eu-TIRADS ACR TIRADS C-TIRADS S-Detect diagnostic performance |
| title | Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis |
| title_full | Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis |
| title_fullStr | Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis |
| title_full_unstemmed | Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis |
| title_short | Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis |
| title_sort | diagnostic efficiency among eu c acr tirads and s detect for thyroid nodules a systematic review and network meta analysis |
| topic | thyroid imaging reporting and data system Eu-TIRADS ACR TIRADS C-TIRADS S-Detect diagnostic performance |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2023.1227339/full |
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