Purpose: Aim of the study was to assess the impact of the Italian Society of Anatomic Pathology and Diagnostic Cytology (SIAPEC) classification of 2014, on the treatment of indeterminate thyroid lesions (TIR3). Methods: We retrospectively analyzed patients undergoing thyroid surgery for TIR3 lesions between 2013 and 2018, at the General Surgery Department of Trieste University Hospital. According to the SIAPEC classification, patients were divided into TIR3A and TIR3B groups. All patients treated before 2014 underwent surgical treatment, and surgical specimens were retrospectively classified after revision of fine-needle aspiration cytology. Starting 2014, TIR3A patients were treated only when symptomatic (i.e., coexistent bilateral thyroid goiter or growing TIR3A nodules), whereas TIR3B patients always received surgical treatment. Hemithyroidectomy (HT) was the procedure of choice. Total thyroidectomy (TT) was performed in case of concurrent bilateral goiter, autoimmune thyroid disease, and/or presence of BRAF and/or RAS mutation. Lastly, we analyzed the malignancy rate in the two groups. Results: 29 TIR3A and 90 TIR3B patients were included in the study. HT was performed in 10 TIR3A patients and 37 TIR3B patients, respectively, with need for reoperation in 4 TIR3B (10.8%) patients due to histological findings of follicular thyroid carcinoma >1 cm. The malignancy rates were 17.2% in TIR3A and 31.1% in TIR3B, (p = 0.16). Predictability of malignancy was almost 89% in BRAF mutation and just 47% in RAS mutation. Conclusions: The new SIAPEC classification in association with biomolecular markers has improved diagnostic accuracy, patient selection, and clinical management of TIR3 lesions.

Impact of the Italian Society of Anatomic Pathology and Diagnostic Cytology Classification of Thyroid Nodules in the Treatment of Indeterminate Follicular Lesions: Five-Year Results at a Single Center

Pastoricchio, M.
Data Curation
;
Cubisino, A.
Data Curation
;
Lanzaro, A.
Data Curation
;
Troian, M.
Data Curation
;
Zanconati, F.
Writing – Original Draft Preparation
;
Bernardi, S.
Writing – Review & Editing
;
Fabris, B.
Writing – Original Draft Preparation
;
de Manzini, N.
Visualization
;
Dobrinja, C.
Writing – Review & Editing
2020-01-01

Abstract

Purpose: Aim of the study was to assess the impact of the Italian Society of Anatomic Pathology and Diagnostic Cytology (SIAPEC) classification of 2014, on the treatment of indeterminate thyroid lesions (TIR3). Methods: We retrospectively analyzed patients undergoing thyroid surgery for TIR3 lesions between 2013 and 2018, at the General Surgery Department of Trieste University Hospital. According to the SIAPEC classification, patients were divided into TIR3A and TIR3B groups. All patients treated before 2014 underwent surgical treatment, and surgical specimens were retrospectively classified after revision of fine-needle aspiration cytology. Starting 2014, TIR3A patients were treated only when symptomatic (i.e., coexistent bilateral thyroid goiter or growing TIR3A nodules), whereas TIR3B patients always received surgical treatment. Hemithyroidectomy (HT) was the procedure of choice. Total thyroidectomy (TT) was performed in case of concurrent bilateral goiter, autoimmune thyroid disease, and/or presence of BRAF and/or RAS mutation. Lastly, we analyzed the malignancy rate in the two groups. Results: 29 TIR3A and 90 TIR3B patients were included in the study. HT was performed in 10 TIR3A patients and 37 TIR3B patients, respectively, with need for reoperation in 4 TIR3B (10.8%) patients due to histological findings of follicular thyroid carcinoma >1 cm. The malignancy rates were 17.2% in TIR3A and 31.1% in TIR3B, (p = 0.16). Predictability of malignancy was almost 89% in BRAF mutation and just 47% in RAS mutation. Conclusions: The new SIAPEC classification in association with biomolecular markers has improved diagnostic accuracy, patient selection, and clinical management of TIR3 lesions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3027850
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