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Development and internal validation of risk stratification tool for lymph node metastasis in pT3-4 laryngeal squamous cell carcinoma patients. | LitMetric

Development and internal validation of risk stratification tool for lymph node metastasis in pT3-4 laryngeal squamous cell carcinoma patients.

Braz J Otorhinolaryngol

Fudan University, Department of Otorhinolaryngology, Eye and ENT Hospital, Shanghai, China. Electronic address:

Published: November 2024

AI Article Synopsis

  • The study aims to identify risk factors for Lymph Node Metastasis (LNM) in patients with advanced Laryngeal Squamous Cell Carcinoma (LSCC) who have negative surgical margins and to create a predictive tool (nomogram) for LNM risk.
  • A total of 872 patients were analyzed, and significant LNM risk factors discovered included smoking history, larger tumor size, deeper tumor invasion, and specific tumor locations.
  • The developed nomogram demonstrated good accuracy in predicting risk and categorized patients into low, moderate, and high-risk groups, assisting in treatment decisions and neck management for these patients.

Article Abstract

Objective: To identify risk factors for Lymph Node Metastasis (LNM) in pT3-4 Laryngeal Squamous Cell Carcinoma (LSCC) patients with negative margins, and develop a nomogram to predict LNM risk.

Methods: 872 patients were divided into training (2010-2014) and validation (2015-2016) cohorts. Univariate and multivariate analyses identified LNM risk factors. A nomogram incorporating significant factors was developed in the training cohort.

Results: Smoking history, maximal tumor diameter ≥3.0 cm, depth of tumor invasion >1.0 cm, and supraglottic tumor location were significantly associated with LNM on multivariate analysis. A predictive nomogram incorporating these factors showed good discrimination (C-index > 0.7) in both cohorts. Patients were stratified into low, moderate and high-risk subgroups based on total risk scores.

Conclusions: A LNM risk prediction model and risk grouping system was established, which may aid treatment selection for pT3-4 LSCC patients. The model and algorithm could help optimize neck management for this high-risk patient population.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11615891PMC
http://dx.doi.org/10.1016/j.bjorl.2024.101535DOI Listing

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