@article{d24e7dd6383c40509dfadc736df6834e,
title = "Establishment and Validation of Pre-Therapy Cervical Vertebrae Muscle Quantification as a Prognostic Marker of Sarcopenia in Patients With Head and Neck Cancer",
abstract = "Background: Sarcopenia is prognostic for survival in patients with head and neck cancer (HNC). However, identification of this high-risk feature remains challenging without computed tomography (CT) imaging of the abdomen or thorax. Herein, we establish sarcopenia thresholds at the C3 level and determine if C3 sarcopenia is associated with survival in patients with HNC. Methods: This retrospective cohort study was conducted in consecutive patients with a squamous cell carcinoma of the head and neck with cross-sectional abdominal or neck imaging within 60 days prior to treatment. Measurement of cross-sectional muscle area at L3 and C3 levels was performed from CT imaging. Primary study outcome was overall survival. Results: Skeletal muscle area at C3 was strongly correlated with the L3 level in both men (n = 188; r = 0.77; p < 0.001) and women (n = 65; r = 0.80; p < 0.001), and C3 sarcopenia thresholds of 14.0 cm2/m2 (men) and 11.1 cm2/m2 (women) were best predictive of L3 sarcopenia thresholds. Applying these C3 thresholds to a cohort of patients with neck imaging alone revealed that C3 sarcopenia was independently associated with reduced overall survival in men (HR = 2.63; 95% CI, 1.79, 3.85) but not women (HR = 1.18, 95% CI, 0.76, 1.85). Conclusions: This study identifies sarcopenia thresholds at the C3 level that best predict L3 sarcopenia in men and women. In HNC, C3-defined sarcopenia is associated with poor survival outcomes in men, but not women, suggesting sarcopenia may differentially affect men and women with HNC.",
keywords = "body composition, cachexia, head and neck cancer, muscle wasting, sarcopenia, squamous cell carcinoma, surgery",
author = "Brennan Olson and Jared Edwards and Catherine Degnin and Nicole Santucci and Michelle Buncke and Jeffrey Hu and Yiyi Chen and Fuller, {Clifton D.} and Mathew Geltzeiler and Grossberg, {Aaron J.} and Daniel Clayburgh",
note = "Funding Information: This work was supported National Cancer Institute grants CA254033 (BO) and CA245188 (AG), AACR The Mark Foundation “Science of the Patient” Award 20-60-51-MARK (AG and Daniel L. Marks), as well as RSNA Research Medical Student Grant RMS2026 (BO). CF received/receives funding and salary support during the period of study execution unrelated to this work from: the National Institutes of Health (NIH) National Cancer Institute (NCI) Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science Program (R01CA214825); Joint NSF/NIH Initiative on Quantitative Approaches to Biomedical Big Data program (R01CA225190); NIH National Institute of Biomedical Imaging and Bioengineering (NIBIB) Research Education Programs for Residents and Clinical Fellows Grant (R25EB025787); NIH National Institute of Dental and Craniofacial Research (NIDCR) Academic Industrial Partnership Grant (R01DE028290); NIDCR Establishing Outcome Measures for Clinical Studies of Oral and Craniofacial Diseases and Conditions award (R01DE025248); NCI Parent Research Project Grant (R01CA258827); NCI Early Phase Clinical Trials in Imaging and Image-Guided Interventions Program (1R01CA218148); an NIH/NCI Cancer Center Support Grant (CCSG) Pilot Research Program Award from the UT MD Anderson CCSG Radiation Oncology and Cancer Imaging Program (P30CA016672); a sub-award from the Small Business Innovation Research Grant Program (R43CA254559); a sub-award from the The Human BioMolecular Atlas Program (HuBMAP) Integration, Visualization & Engagement (HIVE) Initiative (OT2OD026675); the Patient-Centered Outcomes Research Institute (PCS-1609-36195); a National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation (CMMI) grant (NSF 1933369); and the NSF/NCI Smart connected Health Program (R01CA257814). CF receives infrastructure support from MD Anderson Cancer Center under the The Image Guided Cancer Therapy (IGCT) Research Program, and grant and infrastructure support via the Charles and Daneen Stiefel Center for Head and Neck Cancer Oropharyngeal Cancer Research Program. CF has received direct industry grant/in-kind support, honoraria, and travel funding from Elekta AB unrelated to this project. Finally, we thank Haley Knapp-Berry for thoroughly proofreading this manuscript. Funding Information: This work was supported National Cancer Institute grants CA254033 (BO) and CA245188 (AG), AACR The Mark Foundation “Science of the Patient” Award 20-60-51-MARK (AG and Daniel L. Marks), as well as RSNA Research Medical Student Grant RMS2026 (BO). CF received/receives funding and salary support during the period of study execution unrelated to this work from: the National Institutes of Health (NIH) National Cancer Institute (NCI) Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science Program (R01CA214825); Joint NSF/NIH Initiative on Quantitative Approaches to Biomedical Big Data program (R01CA225190); NIH National Institute of Biomedical Imaging and Bioengineering (NIBIB) Research Education Programs for Residents and Clinical Fellows Grant (R25EB025787); NIH National Institute of Dental and Craniofacial Research (NIDCR) Academic Industrial Partnership Grant (R01DE028290); NIDCR Establishing Outcome Measures for Clinical Studies of Oral and Craniofacial Diseases and Conditions award (R01DE025248); NCI Parent Research Project Grant (R01CA258827); NCI Early Phase Clinical Trials in Imaging and Image-Guided Interventions Program (1R01CA218148); an NIH/NCI Cancer Center Support Grant (CCSG) Pilot Research Program Award from the UT MD Anderson CCSG Radiation Oncology and Cancer Imaging Program (P30CA016672); a sub-award from the Small Business Innovation Research Grant Program (R43CA254559); a sub-award from the The Human BioMolecular Atlas Program (HuBMAP) Integration, Visualization & Engagement (HIVE) Initiative (OT2OD026675); the Patient-Centered Outcomes Research Institute (PCS-1609-36195); a National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation (CMMI) grant (NSF 1933369); and the NSF/NCI Smart connected Health Program (R01CA257814). CF receives infrastructure support from MD Anderson Cancer Publisher Copyright: Copyright {\textcopyright} 2022 Olson, Edwards, Degnin, Santucci, Buncke, Hu, Chen, Fuller, Geltzeiler, Grossberg and Clayburgh.",
year = "2022",
month = feb,
day = "14",
doi = "10.3389/fonc.2022.812159",
language = "English (US)",
volume = "12",
journal = "Frontiers in Oncology",
issn = "2234-943X",
publisher = "Frontiers Media S. A.",
}