A predictive model for prognostic risk stratification of early-stage NSCLC based on clinicopathological and miRNA panel

Abstract

Objective

The 5-year survival rate of early-stage non-small cell lung cancer (NSCLC) is still not optimistic. We aimed to construct prognostic tools using clinicopathological (CP) and serum 8-miRNA panel to predict the risk of overall survival (OS) in early-stage NSCLC.

Materials and methods

A total of 799 patients with early-stage NSCLC, treated between April 2008 and September 2019, were included in this study. A sub-group of patients with serum samples, 280, were analyzed for miRNA profiling. The primary endpoint of the study was OS. The CP panel for prognosis was developed using multivariate and forward stepwise selection analyses. The serum 8-miRNA panel was developed using the miRNAs that were significant for prognosis, screened using real-time quantitative PCR (qPCR) followed by differential, univariate and Cox regression analyses. The combined model was developed using CP panel and serum 8-miRNA panel. The predictive performance of the panels and the combined model was evaluated using the area under curve (AUC) values of receiver operating characteristics (ROC) curves and Kaplan-Meier survival analysis.

Result

The prognostic panels and the combined model (comprising CP panel and serum 8-miRNA panel) was used to classify the patients into high-risk and low-risk groups. The OS rates of these two groups were significantly different (P<0.05). The two panels had higher AUC than the two guidelines, and the combined model had the highest AUC. The AUC of the combined model (AUC=0.788; 95 %CI 0.706–0.871) was better than that of the National Comprehensive Cancer Network (NCCN) guideline (AUC=0.601; 95 %CI 0.505–0.697) and Chinese Society of Clinical Oncology (CSCO) guideline (AUC=0.614; 95 %CI 0.520–0.708).

Conclusion

The combined model based on CP panel and serum 8-miRNA panel allows better prognostic risk stratification of patients with early-stage NSCLC to predict risk of OS.