BACKGROUND: In soft tissue sarcoma, better distinction of high-risk and low-risk patients is needed to individualize treatment and improve survival. Prognostic systems used in clinical practice identify high-risk patients based on various factors, including age, tumor size and depth, histological type, necrosis, and grade. METHODS: Whole-tumor sections from 239 soft tissue sarcomas of the extremities were reviewed for the following prognostic factors: size, vascular invasion, necrosis, and growth pattern. A new prognostic model, referred to as SING (Size, Invasion, Necrosis, Growth), was established and compared with other clinically applied systems. RESULTS: Size, vascular invasion, necrosis, and peripheral tumor growth pattern provided independent prognostic information with hazard ratios of 2.2-2.6 for development of metastases in multivariate analysis. When these factors were combined into the prognostic model SING, high risk of metastasis was predicted with a sensitivity of 74% and a specificity of 85%. Moreover, the prognostic performance of SING compared favorably with other widely used systems. CONCLUSIONS: SING represents a promising prognostic model, and vascular invasion and tumor growth pattern should be considered in soft tissue sarcoma prognostication.
BACKGROUND: In soft tissue sarcoma, better distinction of high-risk and low-risk patients is needed to individualize treatment and improve survival. Prognostic systems used in clinical practice identify high-risk patients based on various factors, including age, tumor size and depth, histological type, necrosis, and grade. METHODS: Whole-tumor sections from 239 soft tissue sarcomas of the extremities were reviewed for the following prognostic factors: size, vascular invasion, necrosis, and growth pattern. A new prognostic model, referred to as SING (Size, Invasion, Necrosis, Growth), was established and compared with other clinically applied systems. RESULTS: Size, vascular invasion, necrosis, and peripheral tumor growth pattern provided independent prognostic information with hazard ratios of 2.2-2.6 for development of metastases in multivariate analysis. When these factors were combined into the prognostic model SING, high risk of metastasis was predicted with a sensitivity of 74% and a specificity of 85%. Moreover, the prognostic performance of SING compared favorably with other widely used systems. CONCLUSIONS: SING represents a promising prognostic model, and vascular invasion and tumor growth pattern should be considered in soft tissue sarcoma prognostication.
Authors: Cecilia G Ethun; Alexandra G Lopez-Aguiar; Jeffery M Switchenko; Theresa W Gillespie; Keith A Delman; Charles A Staley; Shishir K Maithel; Kenneth Cardona Journal: Ann Surg Oncol Date: 2019-09-09 Impact factor: 5.344
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