Design of a Predictive Recurrence Scoring System in Oral Squamous Cell Carcinoma

Area of Science:

• Oncology
• Head and Neck Surgery
• Cancer Prognostics

Background:

• Oral squamous cell carcinoma (OSCC) presents significant morbidity and mortality.
• Locoregional recurrence is a primary factor influencing long-term prognosis in OSCC.
• Current predictive models for OSCC recurrence are limited.

Purpose of the Study:

• To identify clinicopathological predictors of locoregional recurrence in OSCC.
• To develop a nomogram-based Recurrence Risk Score (RRS) for patient stratification.
• To enhance personalized patient management strategies for OSCC.

Main Methods:

• Retrospective analysis of 332 surgically treated OSCC patients (2012-2022).
• Analysis of clinical and pathological variables including surgical margins and tumor differentiation.
• Application of statistical methods: Chi-squared tests, Cox regression, Kaplan-Meier analysis, and multivariate modeling.

Main Results:

• Close or involved surgical margins (33.4%) and poor differentiation (66.9%) were common.
• Locoregional recurrence was observed in 34.6% of cases, predominantly within 24 months.
• The developed RRS accurately stratified patients into low (21.6%), intermediate (50.6%), and high (82.1%) risk groups for recurrence.

Conclusions:

• The Recurrence Risk Score (RRS) serves as a practical tool for predicting OSCC recurrence.
• RRS facilitates patient stratification, potentially guiding personalized follow-up and adjuvant therapy decisions.
• Prospective validation of the RRS is recommended for broader clinical implementation.