Prognostic factors and novel prediction models for overall survival of patients with submandibular gland cancer: A population-based retrospective cohort study
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View abstract on PubMed
Summary
This summary is machine-generated.This study identified key factors predicting survival in submandibular gland cancer (SGC) patients. Novel nomograms were developed for accurate survival prediction and personalized risk assessment in SGC.
Area Of Science
- Oncology
- Medical Statistics
Background
- Submandibular gland cancer (SGC) survival prediction is crucial for treatment planning.
- Accurate prognostic models are needed to improve patient outcomes.
Purpose Of The Study
- Identify independent prognostic factors for overall survival (OS) in SGC.
- Develop and validate novel prediction models for SGC survival probability.
Main Methods
- Utilized SEER database for SGC patient data (post-2010).
- Employed COX regression analysis to identify prognostic factors.
- Developed graphical and online dynamic nomograms for survival prediction.
- Validated models using C-index, calibration curves, and ROC analysis.
Main Results
- Identified age, sex, marital status, tumor histology, summary stage, bone metastases, and tumor size as independent prognostic factors for OS.
- Established novel nomograms with favorable discrimination (C-indices: 0.77) and consistency.
- Online dynamic nomogram available at: https://yangxg1209.shinyapps.io/overall_survival_submandibular_gland_tumor/
Conclusions
- Successfully identified independent prognostic factors for SGC.
- Developed and validated accurate nomograms for predicting SGC survival.
- These tools enable personalized risk assessment for SGC patients.
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