ArticleAmerican journal of cancer research2026
Nomogram outperforms gradient boosting machine for prognostic prediction of laryngeal squamous cell carcinoma: a combined analysis of SEER and single-center data.
Article in American journal of cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The incidence of laryngeal squamous cell carcinoma (LSCC) remains persistently high, necessitating accurate prognostic prediction for clinical treatment guidance. By comparing the performance of LSCC models based on the Surveillance, Epidemiology, and End Results (SEER) database and those constructed from single-center datasets, this study provides an effective tool for clinical prognosis evaluation. Data from 526 patients with LSCC were extracted from the SEER database. Univariate and multivariate Cox regression analyses were performed to identify independent predictors of overall survival (OS) in LSCC patients. Subsequently, patients were randomly assigned in a 7:3 ratio to the modeling group and the test group. Based on the modeling group data, nomograms and gradient boosting machine (GBM) models were constructed using R software (version 4.4.1) and their performance was evaluated. The testing cohort was utilized to assess the predictive accuracy of the model. In addition, 207 LSCC patients diagnosed at The First Affiliated Hospital of Yangtze University from February 2020 to April 2024 were retrospectively selected as an external validation cohort. Univariate and Multivariate Cox regression analyses determined that age (60-75 years: HR=1.333, P=0.085; >75 years: HR=2.726, P<0.001), tumor size (HR=1.013, P=0.035), radiation (HR=7.555, P<0.001), cause of death (COD, HR=3.996, P<0.001), marital status at diagnosis (HR=1.444, P=0.006), and T stage (HR=1.652, P=0.017) were independent predictive indicators affecting the OS of LSCC patients (
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