A Multi-Index Model Based on Serum miR-504-3p，miR-151a-5p，and VEGF for Predicting Long-Term Survival and Metastatic Risk in Patients with Advanced Non-Small Cell Lung Cancer

Kai HUANG; Haibing DING

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Kai HUANG, Haibing DING. A Multi-Index Model Based on Serum miR-504-3p，miR-151a-5p，and VEGF for Predicting Long-Term Survival and Metastatic Risk in Patients with Advanced Non-Small Cell Lung Cancer[J]. Journal of Kunming Medical University.

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A Multi-Index Model Based on Serum miR-504-3p，miR-151a-5p，and VEGF for Predicting Long-Term Survival and Metastatic Risk in Patients with Advanced Non-Small Cell Lung Cancer

Kai HUANG¹,
Haibing DING²

1.
Department of Laboratory Medicine
2.
Department of Thoracic Surgery，Taizhou Second People’s Hospital Affiliated to Yangzhou University，Taizhou Jiangsu 225500，China

Received Date: 2026-01-07

Abstract

Abstract

Objective To establish and internally validate a multi-indicator predictive model incorporating serum miR-504-3p, miR-151a-5p, and vascular endothelial growth factor （VEGF） to evaluate its predictive value for the 5-year survival rate and metastasis risk in patients with advanced non-small cell lung cancer （NSCLC）. Methods A retrospective cohort study was conducted on 264 advanced NSCLC patients diagnosed between January 2016 and December 2019 at our institution, all of whom completed a 5-year follow-up. Patients were stratified into survival （n = 58） and mortality （n = 206） groups based on survival status. Multivariate Cox regression analysis was used to identify key factors affecting 5-year survival in advanced NSCLC patients, and a linear prognostic index （PI） model was constructed. Time-dependent receiver operating characteristic （ROC） curves were generated, and the area under the curve （AUC） was calculated to evaluate model discrimination. Internal validation was performed using the Bootstrap method （500 iterations）, with calibration curves, intercepts, and slopes used to assess model calibration. Decision curve analysis （DCA） was employed to evaluate the clinical net benefit of the model. Results miR-151a-5p, VEGF, and clinical stage IV were independent risk factors for 5-year survival in patients with advanced NSCLC （P < 0.05）, while miR-504-3p was a protective factor （P < 0.05）. Time-dependent ROC curves demonstrated that the model's AUC for predicting mortality risk increased from 0.703 （95%CI: 0.637-0.769） at 1 year to 0.859 （95%CI: 0.814～0.904） at 5 years, and for predicting metastasis risk increased from 0.694 （95%CI: 0.624～0.764） at 1 year to 0.847 （95%CI: 0.802～0.892） at 5 years, with discriminatory ability progressively strengthening over time. Calibration curves and quantitative metrics demonstrated good calibration of the model for predicting 3-, 4-, and 5-year mortality and metastasis risk （calibration intercept approaching 0, calibration slope approaching 1）, but suboptimal calibration at 1 and 2 years. DCA results demonstrated that for predicting 3-, 4-, and 5-year mortality and metastasis risk, the PI model provided net benefit superior to both "intervene all" and “intervene none” strategies across a wide range of threshold probabilities. Using the PI median, 264 patients were stratified into high-risk （n = 175） and low-risk （n = 89） groups. Kaplan-Meier survival analysis showed that 5-year survival and metastasis-free rates in the low-risk group were significantly superior to the high-risk group （P < 0.05）. Conclusion Serum miR-504-3p, miR-151a-5p, and VEGF are closely associated with long-term survival and metastasis in advanced NSCLC patients. A multi-indicator model integrating these three markers and clinical staging demonstrates good predictive accuracy for long-term survival and metastasis risk at 3 years and beyond in advanced NSCLC patients and may facilitate clinical identification of patients at high risk for recurrence and metastasis.
- Non-small cell lung cancer,
- MicroRNA,
- Vascular endothelial growth factor,
- Predictive model

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References(24)

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