Clinical and prognostic value of dynapenia in patients with head and neck cancer: a multicenter cohort study. VALOR...

Head and neck cancer (HNC), particularly in patients requiring intensive multimodal treatment, may substantially impair nutritional and functional status due to tumor burden and treatment-related toxicity. Dynapenia, defined as reduced muscle strength independent of muscle mass, has emerged as a critical prognostic marker in cancer, yet its role in HNC remains underexplored. This study aimed to assess the utility of handgrip strength (HGS) in identifying dynapenia and predicting clinical outcomes, in conjunction with advanced morphofunctional tools.

In this prospective multicenter observational cohort study, 514 HNC patients undergoing active radiotherapy were evaluated. Muscle strength was assessed via HGS. Dynapenia was defined using two criteria: EWGSOP2 cut-offs and sex- and age-adjusted percentiles (P10) from Spanish normative data (dynapenia-PCO). Complementary assessments included bioelectrical impedance analysis (phase angle [PA], standardized phase angle [SPA], body cell mass [BCM], and fat-free mass index [FFMI]), nutritional ultrasound® (rectus femoris cross-sectional area [RF-CSA]), the Timed Up and Go test (TUG), and routine biochemical parameters. Logistic regression, ROC curves, Cox proportional hazards models, and machine learning techniques (random forest and decision trees) were used to identify predictors of dynapenia and overall survival.

Dynapenic patients presented significantly lower values of SPA, FFMI, BCM, and RF-CSA, as well as poorer performance (TUG) and nutritional biomarkers (e.g., albumin, total proteins). In multivariate logistic regression models adjusted for age, sex, and BMI, BIA (SPA: OR 0.80; p = 0.04) and ultrasound markers (RF-CSA: OR 0.62; p < 0.001) were independently associated with dynapenia. Random forest analysis identified SPA, FFMI, and TUG as the most relevant predictors of dynapenia (mean decrease accuracy >10), and combined ROC analysis for these three variables achieved an AUC of 0.77 (95% CI: 0.715-0.831; p < 0.001). Regarding prognosis, dynapenia-PCO showed the highest predictive power for mortality, with a hazard ratio (HR) of 2.95 (95% CI: 1.49-5.88; p < 0.01) in Cox regression.

In HNC patients, dynapenia defined by population-based percentiles provides a robust marker of impaired body composition and reduced survival. The integration of simple functional tools like dynamometry with advanced morphofunctional assessments offers a comprehensive and feasible strategy to identify high-risk patients.