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Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis

PURPOSE: The purpose of this systematic literature review was to assess the usefulness of the Thyroid Image Reporting and Data System (K-TIRADS) classification proposed by Kwak for differentiation of thyroid nodules. MATERIAL AND METHODS: Four literature databases were searched for relevant articles...

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Autores principales: Migda, Bartosz, Migda, Michal, Migda, Marian S., Slapa, Rafal Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5938289/
https://www.ncbi.nlm.nih.gov/pubmed/29294156
http://dx.doi.org/10.1007/s00330-017-5230-0
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author Migda, Bartosz
Migda, Michal
Migda, Marian S.
Slapa, Rafal Z.
author_facet Migda, Bartosz
Migda, Michal
Migda, Marian S.
Slapa, Rafal Z.
author_sort Migda, Bartosz
collection PubMed
description PURPOSE: The purpose of this systematic literature review was to assess the usefulness of the Thyroid Image Reporting and Data System (K-TIRADS) classification proposed by Kwak for differentiation of thyroid nodules. MATERIAL AND METHODS: Four literature databases were searched for relevant articles through early January 2017. A meta-analysis was performed to calculate pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR). The area under the curve (AUC) from the pooled receiver operating characteristic (ROC) was used to assess the usefulness of this classification for differentiation of thyroid nodules. Meta-analysis was conducted by using meta-analysis software. RESULTS: We analysed six publications describing 10,926 nodules. Pooled sensitivity, specificity, LR+, LR-, DOR, and AUC for pooled ROC were 0.983 (95 % CI 0.976–0.989), 0.552 (95 % CI 0.542–0.562), 2.666 (95 % CI 1.692–4.198), 0.05 (95 % CI 0.035–0.072), 51.020 (95 % CI 15.241–170.79) and 0.938, respectively. CONCLUSIONS: Kwak TIRADS has high sensitivity and low specificity. Thus, it is very useful to discard the benign cases and to reduce the number of biopsies. KEY POINTS: • Routine, adequate standardization of thyroid nodules ultrasound classification is mandatory. • Kwak TIRADS parameters are accurate for differentiating focal thyroid lesions. • Kwak TIRADS system is simple to apply. • Kwak TIRADS system may become a useful diagnostic tool.
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spelling pubmed-59382892018-05-11 Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis Migda, Bartosz Migda, Michal Migda, Marian S. Slapa, Rafal Z. Eur Radiol Ultrasound PURPOSE: The purpose of this systematic literature review was to assess the usefulness of the Thyroid Image Reporting and Data System (K-TIRADS) classification proposed by Kwak for differentiation of thyroid nodules. MATERIAL AND METHODS: Four literature databases were searched for relevant articles through early January 2017. A meta-analysis was performed to calculate pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR). The area under the curve (AUC) from the pooled receiver operating characteristic (ROC) was used to assess the usefulness of this classification for differentiation of thyroid nodules. Meta-analysis was conducted by using meta-analysis software. RESULTS: We analysed six publications describing 10,926 nodules. Pooled sensitivity, specificity, LR+, LR-, DOR, and AUC for pooled ROC were 0.983 (95 % CI 0.976–0.989), 0.552 (95 % CI 0.542–0.562), 2.666 (95 % CI 1.692–4.198), 0.05 (95 % CI 0.035–0.072), 51.020 (95 % CI 15.241–170.79) and 0.938, respectively. CONCLUSIONS: Kwak TIRADS has high sensitivity and low specificity. Thus, it is very useful to discard the benign cases and to reduce the number of biopsies. KEY POINTS: • Routine, adequate standardization of thyroid nodules ultrasound classification is mandatory. • Kwak TIRADS parameters are accurate for differentiating focal thyroid lesions. • Kwak TIRADS system is simple to apply. • Kwak TIRADS system may become a useful diagnostic tool. Springer Berlin Heidelberg 2018-01-02 2018 /pmc/articles/PMC5938289/ /pubmed/29294156 http://dx.doi.org/10.1007/s00330-017-5230-0 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Ultrasound
Migda, Bartosz
Migda, Michal
Migda, Marian S.
Slapa, Rafal Z.
Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis
title Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis
title_full Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis
title_fullStr Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis
title_full_unstemmed Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis
title_short Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis
title_sort use of the kwak thyroid image reporting and data system (k-tirads) in differential diagnosis of thyroid nodules: systematic review and meta-analysis
topic Ultrasound
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5938289/
https://www.ncbi.nlm.nih.gov/pubmed/29294156
http://dx.doi.org/10.1007/s00330-017-5230-0
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