Development and validation of a diagnostic model for predicting cervical lymph node metastasis in laryngeal and hypopharyngeal carcinoma

作者全名：Wu, Xingdong; Xie, Yuhua; Zeng, Wanting; Wu, Xiaoping; Chen, Jichuan; Li, Genping

作者地址：[Wu, Xingdong; Zeng, Wanting; Wu, Xiaoping; Chen, Jichuan] Army Med Univ, Daping Hosp, Dept Otolaryngol Head & Neck Surg, Chongqing, Peoples R China; [Xie, Yuhua] Chongqing Med Univ, Affiliated Hosp 2, Dept Crit Care Med, Chongqing, Peoples R China; [Li, Genping] Chongqing Med Univ, Affiliated Hosp 2, Dept Otolaryngol Head & Neck Surg, Chongqing, Peoples R China

通信作者：Chen, JC (通讯作者)，Army Med Univ, Daping Hosp, Dept Otolaryngol Head & Neck Surg, Chongqing, Peoples R China.; Li, GP (通讯作者)，Chongqing Med Univ, Affiliated Hosp 2, Dept Otolaryngol Head & Neck Surg, Chongqing, Peoples R China.

来源：FRONTIERS IN ONCOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001216666300001

JCR分区：Q2

影响因子：3.5

年份：2024

卷号：14

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：laryngeal carcinoma; hypopharyngeal carcinoma; lymph node metastasis; diagnostic model; nomogram

摘要：Objectives The lymph node status is crucial for guiding the surgical approach for patients with laryngeal and hypopharyngeal carcinoma (LHC). Nonetheless, occult lymph node metastasis presents challenges to assessment and treatment planning. This study seeks to develop and validate a diagnostic model for evaluating cervical lymph node status in LHC patients.Materials and methods This study retrospectively analyzed a total of 285 LHC patients who were treated at the Department of Otolaryngology Head and Neck Surgery, Daping Hospital, Army Medical University, from January 2015 to December 2020. Univariate and multivariate logistic regression analyses were employed to construct the predictive model. Discrimination and calibration were used to assess the predictive performance of the model. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the model, and validation was conducted using 10-fold cross-validation, Leave-One-Out Cross Validation, and bootstrap methods.Results This study identified significant predictors of lymph node metastasis in LHC. A diagnostic predictive model was developed and visualized using a nomogram. The model demonstrated excellent discrimination, with a C-index of 0.887 (95% CI: 0.835-0.933). DCA analysis indicated its practical applicability, and multiple validation methods confirmed its fitting and generalization ability.Conclusion This study successfully established and validated a diagnostic predictive model for cervical lymph node metastasis in LHC. The visualized nomogram provides a convenient tool for personalized prediction of cervical lymph node status in patients, particularly in the context of occult cervical lymph node metastasis, offering valuable guidance for clinical treatment decisions.

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