Nicholas C J Lee1, Antoine Eskander2, Joseph A Miccio3, Henry S Park3, Chirag Shah4, Michael Rutenberg5, Ali Hosni6, Zain A Husain7. 1. Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA; Department of Internal Medicine, University of Texas Southwestern, Dallas, TX, USA; Department of Pediatrics, University of Texas Southwestern, Dallas, TX, USA. 2. Sunnybrook Health Sciences Centre, Odette Cancer Centre, Toronto, ON, Canada; Department of Otolaryngology-Head and Neck Surgery, University of Toronto, Toronto, ON, Canada. 3. Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA. 4. Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA. 5. Department of Radiation Oncology, University of Florida, Jacksonville, FL, USA. 6. Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON, Canada. 7. Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA; Sunnybrook Health Sciences Centre, Odette Cancer Centre, Toronto, ON, Canada; Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada. Electronic address: zain.husain@sunnybrook.ca.
Abstract
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.
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.
Authors: Ahmed Habib; Idara Edem; Diana Bell; Shirley Y Su; Ehab Y Hanna; Michael E Kupferman; Franco DeMonte; Shaan M Raza Journal: Curr Oncol Date: 2022-09-14 Impact factor: 3.109