Predictive classifier for intensive treatment of head and neck cancer

Predictive classifier for intensive treatment of head and neck cancer:

Background

This study was designed to test the hypothesis that the effectiveness of intensive treatment for locoregionally advanced head and neck cancer (LAHNC) depends on the proportion of patients' overall event risk attributable to cancer.

Methods

This study analyzed 22,339 patients with LAHNC treated in 81 randomized trials testing altered fractionation (AFX; Meta‐Analysis of Radiotherapy in Squamous Cell Carcinomas of Head and Neck [MARCH] data set) or chemotherapy (Meta‐Analysis of Chemotherapy in Head and Neck Cancer [MACH‐NC] data set). Generalized competing event regression was applied to the control arms in MARCH, and patients were stratified by tertile according to the ω score, which quantified the relative hazard for cancer versus competing events. The classifier was externally validated on the MACH‐NC data set. The study tested for interactions between the ω score and treatment effects on overall survival (OS).

Results

Factors associated with a higher ω score were a younger age, a better performance status, an oral cavity site, higher T and N categories, and a p16‐negative/unknown status. The effect of AFX on OS was greater in patients with high ω scores (hazard ratio [HR], 0.92; 95% confidence interval [CI], 0.85‐0.99) and medium ω scores (HR, 0.91; 95% CI, 0.84‐0.98) versus low ω scores (HR, 0.97; 95% CI, 0.90‐1.05; P for interaction = .086). The effect of chemotherapy on OS was significantly greater in patients with high ω scores (HR, 0.81; 95% CI, 0.75‐0.88) and medium ω scores (HR, 0.86; 95% CI, 0.78‐0.93) versus low ω scores (HR, 0.96; 95% CI, 0.86‐1.08; P for interaction = .011).

Conclusions

LAHNC patients with a higher risk of cancer progression relative to competing mortality, as reflected by a higher ω score, selectively benefit from more intensive treatment.