Clinical utility of preoperative lymphocyte–albumin–neutrophil ratio for prognostication in oral cancer patients undergoing surgery

BACKGROUND: Systemic inflammation and nutritional status are key determinants of prognosis in oral squamous cell carcinoma (OSCC). The neutrophil-to-lymphocyte ratio and serum albumin in peripheral blood are established markers reflecting host immune response and nutritional condition, respectively. The lymphocyte-albumin-neutrophil ratio (LANR), a composite index integrating these parameters, has emerged as a potential prognostic biomarker in several cancers; however, its role in OSCC remains unclear. This study aimed to evaluate the prognostic value of preoperative LANR in OSCC. METHODS: We retrospectively analyzed OSCC patients who underwent radical surgery between 2007 and 2017, randomly dividing them into training and validation cohorts by 2:1 ratio. LANR was calculated by multiplying absolute lymphocyte count with serum albumin level and dividing by the absolute neutrophil count. The primary outcomes were 5-year overall survival (OS) and disease-free survival (DFS). Survival-associated factors were identified through univariate and multivariate Cox regression analyses, serving as the foundation for constructing a predictive nomogram model. RESULTS: This study included a total of 660 patients, with 440 assigned to the training cohort and 220 to the validation cohort. A LANR cutoff value of 18.7 effectively stratified patients into distinct prognostic groups, demonstrating significant differences in survival outcomes. Low LANR independently predicted worse OS (hazard ratio [HR]: 1.54; 95% confidence interval [CI]: 1.04-2.28, p = 0.03) and DFS (HR: 1.54, 95% CI: 1.08-2.19; p = 0.017). The LANR-based nomogram demonstrated strong predictive performance, with concordance index of 0.75 and 0.71 in the training and validation cohorts, respectively. CONCLUSION: Preoperative LANR serves as an independent prognostic marker in patients with OSCC. Incorporating LANR into risk models may enhance patient stratification and guide treatment strategies.