Evidence map›Paper›PMID 40165898›Full record

ArticleFrontiers in oncology2025

A nomogram for predicting overall survival in oral squamous cell carcinoma: a SEER database and external validation study.

Ziye Xu, Manbin Xu, Zhichen Sun, Qin Feng, Shaowei Xu, Hanwei Peng

Abstract read
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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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Modulation ofInternational journal of molecular sciences · 2026
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ziye XuDepartment of Head and Neck Surgery, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Manbin XuDepartment of Head and Neck Surgery, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Zhichen SunOtolaryngology Department of The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Qin FengDepartment of Head and Neck Surgery, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Shaowei XuDepartment of Head and Neck Surgery, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Hanwei PengDepartment of Head and Neck Surgery, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

nomogramoral canceroral squamous cell carcinomaoverall survivalprognosis

Identifiers

PMID40165898
PMCPMC11955675

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.