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

ABSTRACT: 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.

SUBMITTER: Wu Z

PROVIDER: S-EPMC7288828 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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

Wu Zhulin Z Ouyang Chensheng C Peng Lisheng L

Medical science monitor : international medical journal of experimental and clinical research 20200601

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 ...[more]

PMID: 32479428

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Project description:BackgroundVarious studies reported that the prognosis of patients with cervical cancer (CC) was significantly associated with immunity, whereas limited studies have explored whether immune-associated genes could be classifiers for recurrence-free survival (RFS) of stage I CC. Thus, an improved immune-related gene signature for stage I CC patients' prognosis is urgently required.Materials and methodsWe retrospectively analyzed the gene expression profiles of stage I CC patients in the GSE44001 set from the Gene Expression Omnibus (GEO) database. The stage I CC patients were randomly divided into the training group and the internal validation group. The training patients were adopted to develop a prognostic immune gene-based signature; meanwhile, the internal validation patients were used to validate the power of the selected immune gene-related signature using univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. The accuracy and reliability of the immune gene-related signature were evaluated based on Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curves.ResultsHigh power of the 8-immune gene signature was found on the basis of ROC analysis (AUC at 1, 3, and 5 years were exhibited in the internal validation group (0.702, 0.715, and 0.728, respectively), external validation group (0.702, 0.825, and 0.842, respectively), and entire GEO dataset (0.840, 0.894, and 0.852, respectively)). Besides, C-index, ROC, calibration plots, and decision curve analysis (DCA) also acted well in our nomogram, suggestive of a high ability of the nomogram to elevate the prognostic prediction of stage I CC patients.ConclusionsIn this study, we successfully constructed an integrated 8-immune gene-based signature which could accurately identify patients with low prognostic risk from those with high prognostic risk. In addition, we developed an immune-related nomogram which can elevate the prognostic prediction of stage I CC patients.

Dataset Information

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

Publications

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

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