Modified Naples Prognostic Score for Postoperative Prognostic Stratification in Patients with Oral Squamous Cell...

The Naples Prognostic Score (NPS) is a composite index that combines serum albumin (ALB), total cholesterol (TC), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR). It has proven prognostic value across various cancers. However, its use in oral squamous cell carcinoma (OSCC) has not been sufficiently recognized for disease-specific characteristics. This study aimed to create and validate a modified NPS (mNPS) specifically for OSCC, comparing its prognostic effectiveness to that of the conventional NPS and other established indices.

A total of 479 patients with histologically confirmed OSCC who underwent curative-intent surgery between 2012 and 2019 were enrolled. Patients were randomly assigned to development (n=335) and validation (n=144) cohorts. Cohort-specific optimal cut-off values for ALB, TC, NLR, and LMR were determined using X-Tile software to construct the mNPS. Prognostic performance of mNPS was compared with conventional NPS, SII, SIRI, and CONUT using ROC analysis, C-index, and Cox regression. A nomogram incorporating mNPS and other independent risk factors was constructed and validated.

Multivariate Cox regression confirmed mNPS as an independent predictor of OS (Group 1: HR 2.18; Group 2: HR 3.10; P<0.01). The mNPS-based nomogram showed superior prognostic accuracy for 1-, 3-, and 5-year OS with AUCs of 0.83, 0.80, and 0.83 in the development cohort, and 0.80, 0.79, and 0.82 in the validation cohort. Corresponding C-index values were 0.73 (OS), 0.72 (DFS), and 0.73 (DSS) in the development cohort, and 0.74, 0.71, and 0.76 in the validation cohort, all outperforming the NPS-based model. Calibration and decision curve analyses confirmed the model's robustness and clinical utility.

Through OSCC-specific threshold recalibration, mNPS demonstrated improved prognostic discrimination compared with conventional indices. Incorporating mNPS into a nomogram enhances individualized risk stratification and provides a practical tool for guiding clinical decision-making in OSCC.