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Search for other papers by Roberto Negro in
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Biomedical Sciences, Università della Svizzera Italiana (USI), Lugano, Switzerland
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Servizio di Endocrinologia e Diabetologia, Ospedale Regionale di Lugano, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland
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University of Latvia, Faculty of Medicine, Riga, Latvia
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Facoltà di Scienze Biomediche, Università della Svizzera Italiana (USI), Lugano, Switzerland
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Context
Ultrasound-based risk stratification systems (Thyroid Imaging Reporting and Data Systems (TIRADSs)) of thyroid nodules (TNs) have been implemented in clinical practice worldwide based on their high performance. However, it remains unexplored whether different TIRADSs perform uniformly across a range of TNs in routine practice. This issue is highly relevant today, given the ongoing international effort to establish a unified TIRADS (i.e. I-TIRADS), supported by the leading societies specializing in TNs. The study aimed to conduct a direct comparison among ACR-, EU-, and K-TIRADS in the distribution of TNs: (1) across the TIRADS categories, and (2) based on their estimated cancer risk.
Methods
A search was conducted on PubMed and Embase until June 2023. Original studies that sequentially assessed TNs using TIRADSs, regardless of FNAC indication, were selected. General study characteristics and data on the distribution of TNs across TIRADSs were extracted.
Results
Seven studies, reporting a total of 41,332 TNs, were included in the analysis. The prevalence of ACR-TIRADS 1–2 was significantly higher than that of EU-TIRADS 2 and K-TIRADS 2, with no significant difference observed among intermediate- and high-risk categories of TIRADSs. According to malignancy risk estimation, K-TIRADS often classified TNs as having more severe risk, ACR-TIRADS as having moderate risk, and EU-TIRADS classified TNs as having lower risk.
Conclusion
ACR-, EU-, and K-TIRADS assess TNs similarly across their categories, with slight differences in low-risk classifications. Despite this, focusing on cancer risk estimation, the three TIRADSs assess TNs differently. These findings should be considered as a prerequisite for developing the I-TIRADS.
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Faculty of Biomedical Sciences, Università Della Svizzera Italiana, Lugano, Switzerland
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Faculty of Biomedical Sciences, Università Della Svizzera Italiana, Lugano, Switzerland
Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
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Faculty of Biomedical Sciences, Università Della Svizzera Italiana, Lugano, Switzerland
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Objective
Thyroid nodule (TN) is usually managed according to Thyroid Imaging And Reporting Data Systems (TIRADS) with the major aim to reduce as much as possible unnecessary fine-needle aspiration cytologies (UN-FNACs). Since the assessment of autonomously functioning thyroid nodule (AFTN) according to TIRADS is heterogeneous, that virtually benign entity may increase the rate of UN-FNAC. This study retrospectively analyzed the appropriateness of TIRADS-based FNAC indication in AFTNs, also looking at the impact of TSH and nodule size.
Methods
Cases diagnosed with AFTN on scintigraphy were searched. Patients who had undergone AFTN treatment, were on medications or supplementation that could affect thyroid function, or had multiple AFTNs were excluded. The AFTNs were assessed according to ACR-TIRADS.
Results
Forty-eight AFTNs were included of which 37.5% had FNAC indication according to TIRADS. The FNAC indication rate in the case of TSH lower than 0.4 mIU/L was significantly higher than in other cases (P = 0.0078). The most accurate TSH cut-off and AFTN size associated with UN-FNAC were ≤ 0.41 mIU/L and > 22 mm, respectively. The multivariate analysis showed that both TSH and nodule size were independent predictors of UN-FNAC with OR of 6.65 and 6.46, respectively. According to these data, the rate of FNAC indication dropped to 4.16%.
Conclusion
Inappropriate FNACs in AFTNs are primarily observed in patients with low TSH and large AFTN. Since these cases typically undergo scintigraphy, the risk of TIRADS-based UN-FNAC is clinically negligible. There is no need for integrating other imaging procedures into the TIRADS model.
