PURPOSE: Parathyroid cancer is rare and often has a poor outcome. There is no classification system that permits prediction of outcome in patients with parathyroid cancer. This study was designed to validate two prognostic classification systems developed by Talat and Schulte in 2010 ("Clinical Presentation, Staging and Long-term Evolution of Parathyroid Cancer," Ann Surg Oncol 2010;17:2156-74) derived from a retrospective literature review of 330 patients. METHODS: This study contains 82 formerly unreported patients with parathyroid cancer. Death due to disease was the primary end point, and recurrence and disease-free survival were the secondary end points. Data acquisition used a questionnaire of predefined criteria. Low risk was defined by capsular and soft tissue invasion alone; high risk was defined by vascular or organ invasion, and/or lymph node or distant metastasis. A differentiated classification system further classified high-risk cancer into vascular invasion alone (class II), lymph node metastasis or organ invasion (class III), and distant metastasis (class IV). Statistical analyses included risk analysis, Kaplan-Meier analysis, and receiver-operating characteristic (ROC) analysis. RESULTS: Follow-up ranged 2-347 months (mean 76 months). Mortality was exclusive to the high- risk group, which also predicted a significant risk of recurrence (risk ratio 9.6; 95% confidence interval 2.4-38.4; P < 0.0001), with significantly lower 5-year disease-free survival (χ(2) = 8.7; P < 0.005 for n = 45). The differentiated classification also provided a good prognostic model with an area under the ROC curve of 0.83 in ROC analysis, with significant impairment of survival between classes (98.6%, 79.2%, 71.4%, 40.0%, P < 0.05 between each class). CONCLUSIONS: This study confirms the validity of both classification systems for disease outcome in patients with parathyroid cancer.
PURPOSE:Parathyroid cancer is rare and often has a poor outcome. There is no classification system that permits prediction of outcome in patients with parathyroid cancer. This study was designed to validate two prognostic classification systems developed by Talat and Schulte in 2010 ("Clinical Presentation, Staging and Long-term Evolution of Parathyroid Cancer," Ann Surg Oncol 2010;17:2156-74) derived from a retrospective literature review of 330 patients. METHODS: This study contains 82 formerly unreported patients with parathyroid cancer. Death due to disease was the primary end point, and recurrence and disease-free survival were the secondary end points. Data acquisition used a questionnaire of predefined criteria. Low risk was defined by capsular and soft tissue invasion alone; high risk was defined by vascular or organ invasion, and/or lymph node or distant metastasis. A differentiated classification system further classified high-risk cancer into vascular invasion alone (class II), lymph node metastasis or organ invasion (class III), and distant metastasis (class IV). Statistical analyses included risk analysis, Kaplan-Meier analysis, and receiver-operating characteristic (ROC) analysis. RESULTS: Follow-up ranged 2-347 months (mean 76 months). Mortality was exclusive to the high- risk group, which also predicted a significant risk of recurrence (risk ratio 9.6; 95% confidence interval 2.4-38.4; P < 0.0001), with significantly lower 5-year disease-free survival (χ(2) = 8.7; P < 0.005 for n = 45). The differentiated classification also provided a good prognostic model with an area under the ROC curve of 0.83 in ROC analysis, with significant impairment of survival between classes (98.6%, 79.2%, 71.4%, 40.0%, P < 0.05 between each class). CONCLUSIONS: This study confirms the validity of both classification systems for disease outcome in patients with parathyroid cancer.
Authors: G Cocorullo; G Scerrino; G Melfa; C Raspanti; G Rotolo; V Mannino; P Richiusa; D Cabibi; A G Giannone; C Porrello; G Gulotta Journal: G Chir Date: 2017 Sep-Oct
Authors: L Rosato; M Raffaelli; R Bellantone; A Pontecorvi; N Avenia; M Boniardi; M L Brandi; F Cetani; M G Chiofalo; G Conzo; M De Palma; G Gasparri; A Giordano; N Innaro; E Leopaldi; G Mariani; C Marcocci; P Marini; P Miccoli; P Nasi; F Pacini; R Paragliola; M R Pelizzo; M Testini; G De Toma Journal: J Endocrinol Invest Date: 2014-01-09 Impact factor: 4.256
Authors: Loredana De Pasquale; Antonio Mario Bulfamante; Giovanni Felisati; Luca Castellani; Giorgio Ghilardi; Alberto Maria Saibene Journal: Int J Endocrinol Date: 2021-10-07 Impact factor: 3.257