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01 June 2020 : Database Analysis  

A Novel Nomogram Based on Immune Scores for Predicting Survival in Patients with Early-Stage Non-Small Cell Lung Cancer (NSCLC)

Zhulin Wu1ABCE, Chensheng Ouyang2ACD, Lisheng Peng3ADE*

DOI: 10.12659/MSM.923231

Med Sci Monit 2020; 26:e923231


BACKGROUND: The role of immune parameters in the prognosis of lung cancer has attracted more and more attention. However, studies of the association between immune scores and prognosis of lung cancer are scarce. The goal of our research was to investigate the correlation between immune scores and overall survival (OS) of early-stage non-small cell lung cancer (NSCLC).

MATERIAL AND METHODS: All data regarding patient immune and stromal scores, clinicopathological features, and survival was obtained from the TCGA datasets. Univariable and multivariable Cox regression analyses were utilized to recognize risk factors associated with OS. Afterward, a prognostic nomogram was constructed for predicting 3- and 5-year OS of stage I and II NSCLC patients. Calibration curves and receiver operating characteristic (ROC) were performed to assess the predictive accuracy of the nomogram. Kaplan-Meier methodology was also applied for the survival analysis.

RESULTS: In total, 764 NSCLC (stage I–II) patients were analyzed, and all patients were classified into 3 groups based on immune scores. Results showed that patients with medium-immune scores had significantly worse OS (hazard ratio=1.73, 95% confidence interval: 1.22–2.46) compared with those with low- and high immune scores. Area under the ROC curves (AUC) values for 3- and 5-year OS were 0.65 and 0.64, respectively. Calibration plots demonstrated good consistency in the probability of OS between nomogram predictions and actual observations.

CONCLUSIONS: Medium-immune scores are correlated with unsatisfactory prognosis in NSCLC (stage I–II) patients. In addition, the prognostic nomogram may be helpful in predicting OS for stage I and II NSCLC patients.

Keywords: Immunologic Factors, nomograms, Aged, 80 and over, Databases, Factual, Probability, ROC Curve

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Dinah V. Parums

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Med Sci Monit 2024; 30:e945583


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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750