Body Composition Metrics and Overall Survival in Head and Neck Cancer Radiotherapy

Importance Advancing the prognostication of patients with head and neck cancer who are undergoing radiotherapy may guide clinicians to better individualize support throughout oncologic treatment. Objective To evaluate how automated 3-dimensional soft tissue phenotyping, as extracted from routine computed tomography (CT) scans, provides deeper biological granularity into body composition and mortality risk and examine the prognostic utility of baseline body mass index. Design, Setting, and Participants This retrospective cohort study evaluated a consecutive sample of patients who were receiving conventionally fractionated definitive-intent radiotherapy for head and neck cancer between January 1, 2014, and December 31, 2024, at a single-center tertiary academic referral center. Cohort filtering was applied to exclude palliative, abbreviated, or nonstandard treatment regimens. Data were analyzed from October 2025 to May 2026. Exposures Baseline body composition metrics, including body mass index and 3-dimensional volumetric soft tissue indices, extracted automatically from pretreatment CT simulation scans using an open-source deep learning segmentation pipeline. Main Outcomes and Measures The primary outcome was overall survival. Multivariable Cox proportional hazards models were used to assess the independent prognostic associations of baseline body mass index and volumetric soft tissue indices, controlling for standard clinical confounders. Results The primary clinical cohort comprised 1187 patients (median [range] age, 64.0 [5.0-100.0] years; 323 female individuals [27.2%] and 864 male individuals [72.8%]), with an imaging subcohort of 659 patients (55.5%). While elevated body mass index categories were associated with overall survival (overweight: hazard ratio [HR], 0.70; 95% CI, 0.56-0.89; obesity: HR, 0.67; 95% CI, 0.50-0.89), a volumetric analysis revealed that this expansion was disproportionately associated with subcutaneous adiposity gain rather than muscle growth. In the imaging subcohort, elevated skeletal muscle was associated with improved overall survival (HR, 0.67; 95% CI, 0.50-0.89; P = .001). Conversely, elevated intermuscular adiposity was independently associated with an increased mortality risk (HR, 1.28; 95% CI, 1.03-1.58; P = .02). Conclusions and Relevance The results of this cohort study suggest that higher body mass index was associated with improved overall survival. Automated volumetric CT phenotyping revealed that higher skeletal muscle and lower intermuscular adiposity were also associated with improved survival outcomes. This scalable, opportunistic framework may guide pretreatment risk stratification to identify vulnerable patients who may benefit from targeted supportive care.

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Publication Details

Journal
JAMA Otolaryngology–Head & Neck Surgery
Published
2026-10-08
DOI
https://doi.org/10.1001/jamaoto.2026.2951
Primary Topic
Head and Neck Cancer Studies
Type
article
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article

Body Composition Metrics and Overall Survival in Head and Neck Cancer Radiotherapy

Jasmine Gillett, Ricky R. Savjani, Kyunghyun Sung, Chulmin Bang et al.
JAMA Otolaryngology–Head & Neck Surgery
Head and Neck Cancer Studies
article

Body Composition Metrics and Overall Survival in Head and Neck Cancer Radiotherapy

Jasmine Gillett, Ricky R. Savjani, Kyunghyun Sung, Chulmin Bang, Erika Jank, Lily Chau, Cesar Vincent Villafuerte, Robert Chin, Vinith B Raj, Anthony Militchin, Changsuk Oh, X. Sharon Qi
article en

Abstract

Importance Advancing the prognostication of patients with head and neck cancer who are undergoing radiotherapy may guide clinicians to better individualize support throughout oncologic treatment. Objective To evaluate how automated 3-dimensional soft tissue phenotyping, as extracted from routine computed tomography (CT) scans, provides deeper biological granularity into body composition and mortality risk and examine the prognostic utility of baseline body mass index. Design, Setting, and Participants This retrospective cohort study evaluated a consecutive sample of patients who were receiving conventionally fractionated definitive-intent radiotherapy for head and neck cancer between January 1, 2014, and December 31, 2024, at a single-center tertiary academic referral center. Cohort filtering was applied to exclude palliative, abbreviated, or nonstandard treatment regimens. Data were analyzed from October 2025 to May 2026. Exposures Baseline body composition metrics, including body mass index and 3-dimensional volumetric soft tissue indices, extracted automatically from pretreatment CT simulation scans using an open-source deep learning segmentation pipeline. Main Outcomes and Measures The primary outcome was overall survival. Multivariable Cox proportional hazards models were used to assess the independent prognostic associations of baseline body mass index and volumetric soft tissue indices, controlling for standard clinical confounders. Results The primary clinical cohort comprised 1187 patients (median [range] age, 64.0 [5.0-100.0] years; 323 female individuals [27.2%] and 864 male individuals [72.8%]), with an imaging subcohort of 659 patients (55.5%). While elevated body mass index categories were associated with overall survival (overweight: hazard ratio [HR], 0.70; 95% CI, 0.56-0.89; obesity: HR, 0.67; 95% CI, 0.50-0.89), a volumetric analysis revealed that this expansion was disproportionately associated with subcutaneous adiposity gain rather than muscle growth. In the imaging subcohort, elevated skeletal muscle was associated with improved overall survival (HR, 0.67; 95% CI, 0.50-0.89; P = .001). Conversely, elevated intermuscular adiposity was independently associated with an increased mortality risk (HR, 1.28; 95% CI, 1.03-1.58; P = .02). Conclusions and Relevance The results of this cohort study suggest that higher body mass index was associated with improved overall survival. Automated volumetric CT phenotyping revealed that higher skeletal muscle and lower intermuscular adiposity were also associated with improved survival outcomes. This scalable, opportunistic framework may guide pretreatment risk stratification to identify vulnerable patients who may benefit from targeted supportive care.

JAMA Otolaryngology–Head & Neck Surgery
University of California, Los Angeles (US)
Openalex Percentile: Top 9%
Head and Neck Cancer Studies
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