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Lymphedema Following Cervical Lymph Node Dissection for Head and Neck Cancer: A Decade of Outcomes and Risk Modeling
Stav Brown, MD, Sarah Fargey, BS, Mehra Golshan, MD MBA, Siba Haykal MD PhD
1. Yale School of Medicine, New Haven, CT, United States.
Background: Cervical lymph node dissection (CLND) remains a cornerstone in the treatment of head and neck malignancies, but it carries a significant risk of lymphedema. The role of autoimmune and metabolic comorbidities in modulating this risk is not well established.
Methods: We conducted a longitudinal analysis of all patients who underwent CLND for head and neck cancer at a tertiary cancer center between 2013 and 2025. Demographic, oncologic, metabolic, and autoimmune variables were analyzed. A multivariable logistic regression model was developed to identify independent predictors of lymphedema and support the construction of a clinical risk prediction tool.
Results: Among 4,925 patients, 752 (15.3%) developed lymphedema. Independent predictors of increased risk included radiation therapy (OR = 6.88; 95% CI: 5.66-8.39; p<0.0001), chemotherapy (OR = 1.98; 95% CI: 1.63-2.40; p<0.0001), older age (OR = 1.008 per year; 95% CI: 1.002-1.015; p=0.0096), Hispanic ethnicity (OR = 0.69; 95% CI: 0.49-0.96; p=0.0291), Hashimoto's thyroiditis (OR = 1.71; 95% CI: 1.00-2.85; p=0.0437), and scleroderma (OR = 4.61; 95% CI: 1.14-16.31; p=0.0221). The model demonstrated strong predictive performance, with an area under the ROC curve (AUC) of 0.803 (95% CI: 0.786-0.820; p<0.0001).
Conclusion: This is the first large-scale study to model lymphedema risk following CLND using autoimmune and treatment-related predictors. The resulting model, with strong discriminative ability, may serve as a clinically useful tool to guide surveillance and early intervention strategies in high-risk patients, taking into account autoimmune conditions in addition to known risk factors.
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