OBJECTIVE: To find out the most predictive staging system for papillary thyroid carcinoma (PTC) currently available in the literature. BACKGROUND: Various staging systems or risk group stratifications have been used extensively in the clinical management of patients with PTC, but the most predictive system for cancer-specific survival (CSS) based on distinct histologic types remains unclear. METHODS: Through a comprehensive MEDLINE search from 1965 to 2005, a total of 17 staging systems were found in the literature and 14 systems were applied to the 589 PTC patients managed at our institution from 1961 to 2001. CSS were calculated by Kaplan-Meier method and were compared by log-rank test. Using Cox proportional hazards analysis, the relative importance of each staging system in determining CSS was calculated by the proportion of variation (PVE). RESULTS: All 14 staging systems significantly predicted CSS (P < 0.001). The 3 highest ranked staging systems by PVE were the Metastases, Age, Completeness of Resection, Invasion, Size (MACIS) (18.7) followed by the new AJCC/UICC 6th edition tumor, node, metastases (TNM) (17.9), and the European Organization for Research and Treatment of Cancer (EORTC) (16.6). CONCLUSIONS: All of the currently available staging systems predicted CSS well in patients with PTC regardless of which histologic type from which they were derived. When predictability was measured by PVE, the MACIS system was the most predictive staging system and so should be the staging system of choice for PTC in the future.
OBJECTIVE: To find out the most predictive staging system for papillary thyroid carcinoma (PTC) currently available in the literature. BACKGROUND: Various staging systems or risk group stratifications have been used extensively in the clinical management of patients with PTC, but the most predictive system for cancer-specific survival (CSS) based on distinct histologic types remains unclear. METHODS: Through a comprehensive MEDLINE search from 1965 to 2005, a total of 17 staging systems were found in the literature and 14 systems were applied to the 589 PTC patients managed at our institution from 1961 to 2001. CSS were calculated by Kaplan-Meier method and were compared by log-rank test. Using Cox proportional hazards analysis, the relative importance of each staging system in determining CSS was calculated by the proportion of variation (PVE). RESULTS: All 14 staging systems significantly predicted CSS (P < 0.001). The 3 highest ranked staging systems by PVE were the Metastases, Age, Completeness of Resection, Invasion, Size (MACIS) (18.7) followed by the new AJCC/UICC 6th edition tumor, node, metastases (TNM) (17.9), and the European Organization for Research and Treatment of Cancer (EORTC) (16.6). CONCLUSIONS: All of the currently available staging systems predicted CSS well in patients with PTC regardless of which histologic type from which they were derived. When predictability was measured by PVE, the MACIS system was the most predictive staging system and so should be the staging system of choice for PTC in the future.
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