Predicting treatment intolerance in operable head and neck cancer using the modified head and neck surgery risk index

Head and neck cancer (HNC) treatment often involves multimodal regimens, with 30-40% of patients experiencing significant toxicity or treatment intolerance. Existing risk models do not fully capture the complex interplay of sarcopenia, frailty, and treatment factors, limiting their utility for surgical decision-making.

We developed and validated the modified Head and Neck Surgery Risk Index (mHNSRI), a tool incorporating multimodal domains of sarcopenia (cervical paraspinal skeletal muscle index, SMI), frailty (modified Frailty Index, Clinical Risk Analysis Index) and treatment factors, using an ambispective cohort of patients with operable HPV-negative stage II-IV HNC. Treatment intolerance was defined as a severe toxicity or therapy non-completion. Logistic regression and recursive partitioning analysis were used to identify predictors variables for treatment intolerance. The mHNSRI's performance was compared to traditional preoperative risk indices using internal and external validation cohorts.

In 568 patients, including 343 in the derivation and 225 in the validation cohort, the mean age was 65 with 228 (40%) patients being frail and 259 (46%) sarcopenic. Treatment intolerance occurred in 270 (48%) patients. Independent predictors of treatment intolerance included low cervical paraspinal SMI, elevated Risk Analysis Index (RAI), reduced high-to-low attenuation SMI ratio and obesity. Sarcopenia and frailty had a synergistic effect on treatment intolerance. Adding cervical paraspinal SMI and high-to-low attenuation SMI ratio improved model performance (Δc-statistic 0.069, P = 0.05). The mHNSRI had an AUC of 0.71 (95% CI:0.61-0.80) in external validation cohort and demonstrated superior predictive ability compared to the RAI (Δc 0.14, modified Frailty Index-5 (Δc 0.13), ASA (Δc 0.2) and Charlson Comorbidity Index (Δc 0.14, all P < 0.05) CONCLUSION: The mHNSRI offers a personalized approach to preoperative risk stratification in HNC surgery, integrating sarcopenia and frailty metrics to better predict treatment intolerance.