Aaron J Grossberg1, Crosby D Rock2, Jared Edwards3, Abdallah S R Mohamed4, Debra Ruzensky5, Angela Currie5, Patricia Rosemond5, Jack Phan4, G Brandon Gunn4, Steven J Frank4, William H Morrison4, Adam S Garden4, Clifton D Fuller4, David I Rosenthal6. 1. Department of Radiation Medicine, Brenden Colson Center for Pancreatic Care, Cancer Early Detection Advanced Research Center, Oregon Health & Science University, Portland, USA. Electronic address: grossber@ohsu.edu. 2. Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, USA. 3. School of Medicine, Oregon Health & Science University, Portland, USA. 4. Department of Radiation Oncology, MD Anderson Cancer Center, Houston, USA. 5. Department of Clinical Nutrition, MD Anderson Cancer Center, Houston, USA. 6. Department of Radiation Oncology, MD Anderson Cancer Center, Houston, USA. Electronic address: dirosenthal@mdanderson.org.
Abstract
BACKGROUND AND PURPOSE: Sarcopenia is associated with decreased survival in head and neck cancer patients treated with radiotherapy. This study sought to determine whether in-clinic multifrequency bioelectrical impedance analysis (BIA) can identify survival-associated sarcopenia in patients with head and neck cancer. MATERIALS AND METHODS: This prospective observational study enrolled 50 patients with head and neck cancer undergoing radiation therapy. Baseline BIA measures of skeletal muscle (SM) mass, fat-free mass (FFM), and fat mass (FM) were compared to CT-based estimates using linear regression. Sex-specific BIA-derived thresholds for sarcopenia were defined by the maximum Youden Index on receiver operator characteristic (ROC) curves. Patients were stratified by sarcopenia status and OS was compared using the Kaplan-Meier method and log-rank test. RESULTS: Among 48 evaluable patients, BIA measures of body composition were strongly correlated with CT measures: SM mass (r = 0.97; R2 = 0.94; p < 0.0001), FFM (r = 0.97; R2 = 0.94; p < 0.0001) and FM (r = 0.95; R2 = 0.90; p < 0.0001). SM mass index < 9.19 kg/m2 identified sarcopenia men with high sensitivity (91.7%) and specificity (92.9%), whereas in women SM mass index < 6.53 kg/m2 was sensitive for sarcopenia (100%), but not specific. Patients with sarcopenia, defined by either CT or BIA, exhibited decreased OS (HR = not estimable; CT p = 0.009; BIA p = 0.03). CONCLUSION: BIA provides accurate estimates of body composition in head and neck cancer patients. Implementation of BIA in clinical practice may identify patients with sarcopenia at risk for poor survival.
BACKGROUND AND PURPOSE: Sarcopenia is associated with decreased survival in head and neck cancer patients treated with radiotherapy. This study sought to determine whether in-clinic multifrequency bioelectrical impedance analysis (BIA) can identify survival-associated sarcopenia in patients with head and neck cancer. MATERIALS AND METHODS: This prospective observational study enrolled 50 patients with head and neck cancer undergoing radiation therapy. Baseline BIA measures of skeletal muscle (SM) mass, fat-free mass (FFM), and fat mass (FM) were compared to CT-based estimates using linear regression. Sex-specific BIA-derived thresholds for sarcopenia were defined by the maximum Youden Index on receiver operator characteristic (ROC) curves. Patients were stratified by sarcopenia status and OS was compared using the Kaplan-Meier method and log-rank test. RESULTS: Among 48 evaluable patients, BIA measures of body composition were strongly correlated with CT measures: SM mass (r = 0.97; R2 = 0.94; p < 0.0001), FFM (r = 0.97; R2 = 0.94; p < 0.0001) and FM (r = 0.95; R2 = 0.90; p < 0.0001). SM mass index < 9.19 kg/m2 identified sarcopenia men with high sensitivity (91.7%) and specificity (92.9%), whereas in women SM mass index < 6.53 kg/m2 was sensitive for sarcopenia (100%), but not specific. Patients with sarcopenia, defined by either CT or BIA, exhibited decreased OS (HR = not estimable; CT p = 0.009; BIA p = 0.03). CONCLUSION: BIA provides accurate estimates of body composition in head and neck cancer patients. Implementation of BIA in clinical practice may identify patients with sarcopenia at risk for poor survival.
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