ArticleFrontiers in oncology2025
A nomogram for predicting overall survival in oral squamous cell carcinoma: a SEER database and external validation study.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Modulation ofInternational journal of molecular sciences · 2026Article
- Development and internal validation of a prognostic nomogram incorporating F-NLR and HAGR scores in patients with oral squamous cell carcinoma: a single-center retrospective cohort study.Frontiers in oncology · 2026Article
- Perioperative symptom burden as an independent predictor of long-term functional and survival outcomes in oral squamous cell carcinoma patients undergoing free flap reconstruction: a retrospective cohort study.American journal of cancer research · 2026Article
- Development and validation of a novel hepato-metabolic-renal score nomogram for predicting disease-free survival in head and neck squamous cell carcinoma.Frontiers in oncology · 2026Article
- Tomatidine suppresses PI3K/Akt signaling to induce apoptosis in oral squamous cell carcinoma: An in vitro and molecular docking study.Journal of oral biology and craniofacial researchArticle
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Authors and funding
6 authors.
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Abstract
Purpose: Oral squamous cell carcinoma (OSCC) often presents with unsatisfactory survival outcomes, especially in advanced stages. This study aimed to develop and validate a nomogram incorporating demographic, clinicopathologic, and treatment-related factors to improve the prediction of overall survival (OS) in OSCC patients. Methods: Data from 15,204 OSCC patients in a US database were retrospectively utilized to construct a prognostic model and generate a nomogram. External validation was performed using an independent cohort of 359 patients from a specialized cancer center in China. Prognostic factors were identified using Cox regression analysis and incorporated into the nomogram. Model performance was evaluated by concordance index (C-index), time-dependent area under the receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis (DCA). A risk stratification system was developed to classify patients into high- and low-risk groups. Results: Age, sex, primary tumor site, T and N staging, and treatment modalities (including surgery, chemotherapy, and radiotherapy) were found to be independent prognostic factors. The nomogram achieved a C-index of 0.727 in the training set and 0.6845 in the validation set, outperforming the conventional TNM staging system. The nomogram's superior predictive accuracy was confirmed by higher AUC values, better calibration, and improved clinical utility as demonstrated by DCA. Risk stratification, based on the nomogram, distinguished patients into distinct prognostic groups with significant OS differences. Conclusions: This nomogram provides an effective, personalized tool for predicting OS in OSCC. It offers clinicians a valuable aid for treatment decision-making and improves patient management.
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