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Evaluation of head and neck soft tissue sarcoma 8th edition pathologic staging system and proposal of a novel stage grouping system.
Oral Oncology 2021 March
BACKGROUND: The AJCC 8th edition issued a dedicated staging system for head and neck soft tissue sarcomas (HN-STS) with 2 and 4 cm tumor cut-off points, as well as a T4 classification based on invasion of adjacent structures. Stage groupings were not provided due to a paucity of data.
METHODS: We identified HN-STS patients undergoing primary surgery without neoadjuvant therapy patients in the Surveillance, Epidemiology, and End Results (SEER) database. We used multivariable analysis to examine adverse prognosticators. Then, using, recursive partitioning analysis (RPA), we established a stage grouping system that was externally validated in the National Cancer Database (NCDB).
RESULTS: Multivariable analysis in the SEER cohort (N = 546) demonstrated worsened survival with tumors invading adjacent structures (P < 0.001) and increasing de-differentiation (P < 0.001). There was no prognostic difference based on size for T1-3 tumors; however, when assessed as a continuous variable, a 5 cm tumor size cut-off point was predictive of outcome. RPA generated a stage grouping system with the following five-year overall survival: RPA Stage I (pT1-3N0-1G1-2M0) 71.2%, RPA Stage II (pT4abN0-1G1-2M0/pT1-3N0-1G3-4M0) 53.4%, and RPA Stage III (pT4abN0-1G3-4M0) 17.5%. This was successfully externally validated in the NCDB cohort (P < 0.001).
CONCLUSIONS: We confirm the importance of structural invasion and grade and demonstrate that the currently used size cut-off points are not prognostic. We propose a novel stage grouping system. A 5 cm tumor size cut-off point for tumor stage should be further evaluated.
METHODS: We identified HN-STS patients undergoing primary surgery without neoadjuvant therapy patients in the Surveillance, Epidemiology, and End Results (SEER) database. We used multivariable analysis to examine adverse prognosticators. Then, using, recursive partitioning analysis (RPA), we established a stage grouping system that was externally validated in the National Cancer Database (NCDB).
RESULTS: Multivariable analysis in the SEER cohort (N = 546) demonstrated worsened survival with tumors invading adjacent structures (P < 0.001) and increasing de-differentiation (P < 0.001). There was no prognostic difference based on size for T1-3 tumors; however, when assessed as a continuous variable, a 5 cm tumor size cut-off point was predictive of outcome. RPA generated a stage grouping system with the following five-year overall survival: RPA Stage I (pT1-3N0-1G1-2M0) 71.2%, RPA Stage II (pT4abN0-1G1-2M0/pT1-3N0-1G3-4M0) 53.4%, and RPA Stage III (pT4abN0-1G3-4M0) 17.5%. This was successfully externally validated in the NCDB cohort (P < 0.001).
CONCLUSIONS: We confirm the importance of structural invasion and grade and demonstrate that the currently used size cut-off points are not prognostic. We propose a novel stage grouping system. A 5 cm tumor size cut-off point for tumor stage should be further evaluated.
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