Unknown

Dataset Information

Bayesian Monte Carlo Simulation Based on Systematic Review for Personalized Risk Stratification of Contralateral Lymph Node Metastasis in Oral Squamous Cell Carcinoma.


ABSTRACT: Background: Contralateral lymph node metastasis (CLNM) in oral squamous cell carcinoma (OSCC) represents a major clinical challenge, in patients with a clinically contralateral node-negative neck. Individualized risk stratification is crucial to guide decisions on elective contralateral neck dissection. This study aimed to synthesize existing evidence and apply Bayesian Monte Carlo Simulation (MCS) to estimate CLNM probability across various clinic-pathological scenarios. Methods: A systematic search of PubMed, PubMed Central, and Embase (2000-2024) identified 26 eligible studies. Effect sizes for seven key risk factors-midline-crossing tumours, extranodal extension (ENE), ≥2 ipsilateral lymph nodes, depth of invasion (DOI) >10 mm, perineural invasion and lymphovascular invas

SUBMITTER: Rao KN 

PROVIDER: S-EPMC12607710 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature