Eleonora Horvath1, Claudio F Silva2, Sergio Majlis3, Ignacio Rodriguez4, Velimir Skoknic4, Alex Castro5, Hugo Rojas6, Juan-Pablo Niedmann2, Arturo Madrid6, Felipe Capdeville6, Carolina Whittle2, Ricardo Rossi6, Miguel Domínguez3, Hernán Tala3. 1. Radiology Department, Clinica Alemana, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo, Santiago, Chile. eleonora.horvath@gmail.com. 2. Radiology Department, Clinica Alemana, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo, Santiago, Chile. 3. Internal Medicine Department, Clinica Alemana, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo, Santiago, Chile. 4. Medical School, Clinica Alemana, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo, Santiago, Chile. 5. Pathology Department, Clinica Alemana, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo, Santiago, Chile. 6. Surgery Department, Clinica Alemana, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo, Santiago, Chile.
Abstract
OBJECTIVE: To assess performance of TIRADS classification on a prospective surgical cohort, demonstrating its clinical usefulness. METHODS: Between June 2009 and October 2012, patients assessed with pre-operative ultrasound (US) were included in this IRB-approved study. Nodules were categorised according to our previously described TIRADS classification. Final pathological diagnosis was obtained from the thyroidectomy specimen. Sensitivity, specificity, positive/negative predictive values and likelihood ratios were calculated. RESULTS: The study included 210 patients with 502 nodules (average: 2.39 (±1.64) nodules/patient). Median size was 7 mm (3-60 mm). Malignancy was 0 % (0/116) in TIRADS 2, 1.79 % (1/56) in TIRADS 3, 76.13 % (185/243) in TIRADS 4 [subgroups: TIRADS 4A 5.88 % (1/17), TIRADS 4B 62.82 % (49/78), TIRADS 4C 91.22 % (135/148)], and 98.85 % (86/87) in TIRADS 5. With a cut-off point at TIRADS 4-5 to perform FNAB, we obtained: sensitivity 99.6 % (95 % CI: 98.9-100.0), specificity 74.35 % (95 % CI: 68.7-80.0), PPV 82.1 % (95 % CI: 78.0-86.3), NPV 99.4 % (95 % CI: 98.3-100.0), PLR 3.9 (95 % CI: 3.6-4.2) and an NLR 0.005 (95 % CI: 0.003-0.04) for malignancy. CONCLUSION: US-based TIRADS classification allows selection of nodules requiring FNAB and recognition of those with a low malignancy risk. KEY POINTS: • TIRADS classification allows accurate selection of thyroid nodules requiring biopsy (TIRADS 4-5). • The recognition of benign/possibly benign patterns can avoid unnecessary procedures. • This classification and its sonographic patterns are validated using surgical specimens.
OBJECTIVE: To assess performance of TIRADS classification on a prospective surgical cohort, demonstrating its clinical usefulness. METHODS: Between June 2009 and October 2012, patients assessed with pre-operative ultrasound (US) were included in this IRB-approved study. Nodules were categorised according to our previously described TIRADS classification. Final pathological diagnosis was obtained from the thyroidectomy specimen. Sensitivity, specificity, positive/negative predictive values and likelihood ratios were calculated. RESULTS: The study included 210 patients with 502 nodules (average: 2.39 (±1.64) nodules/patient). Median size was 7 mm (3-60 mm). Malignancy was 0 % (0/116) in TIRADS 2, 1.79 % (1/56) in TIRADS 3, 76.13 % (185/243) in TIRADS 4 [subgroups: TIRADS 4A 5.88 % (1/17), TIRADS 4B 62.82 % (49/78), TIRADS 4C 91.22 % (135/148)], and 98.85 % (86/87) in TIRADS 5. With a cut-off point at TIRADS 4-5 to perform FNAB, we obtained: sensitivity 99.6 % (95 % CI: 98.9-100.0), specificity 74.35 % (95 % CI: 68.7-80.0), PPV 82.1 % (95 % CI: 78.0-86.3), NPV 99.4 % (95 % CI: 98.3-100.0), PLR 3.9 (95 % CI: 3.6-4.2) and an NLR 0.005 (95 % CI: 0.003-0.04) for malignancy. CONCLUSION: US-based TIRADS classification allows selection of nodules requiring FNAB and recognition of those with a low malignancy risk. KEY POINTS: • TIRADS classification allows accurate selection of thyroid nodules requiring biopsy (TIRADS 4-5). • The recognition of benign/possibly benign patterns can avoid unnecessary procedures. • This classification and its sonographic patterns are validated using surgical specimens.
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