Prognostic Classification Model For Brain Metastases Of Lung Adenocarcinoma Based On EGFR Mutation Status

Objective:To better guide the clinical decision and predicting prognosis,radiation oncology group(RTOG)successively set up several predictive tools for brain metastases from malignant tumors,which included Recombinase Polymerase Amplification(RPA),Graded Prognostic Assessment(GPA),and basic score for brain metastases(BS-BM).However,they vary by primary cancer and histological subtypes.In addtion,the intrinsic molecular biological profiles may also be the prognostic factors.Recent work suggests that epidermal growth factor receptor(EGFR)mutations are closely associated with brain metastases of non-small cell lung cancer,especially for adenocarcinomas.Thus we wanted to further define the importance of EGFR mutation for predicting patient survival for these particular individuals and devolop a new pronostic medel specific for this kind of patients.Methods:A total of 304 patients with pathologically confirmed lung adenocarcinoma of brain metastasis and known EGFR mutation status were analyzed retrospectively.The overall survival(OS)were calculated by the Kaplan-Meier method.The univariate prognostic analyses were performed by the log-rank test.The Cox proportional hazards model was used for multivariate prognostic analysis.A new prognostic classification model was developed based on the results of multivariable analyses.The independent significant prognostic factors were integrated into the prognostic system.The model predictive ability was compared to three published models.Results:EGFR mutation status(p<0.001)and Karnofsky performance status(KPS)(p<0.001)were independent prognostic factors of the brain metasteses from lung adenocarcinoma in multivariate prognostic analysis.They are integrated in the new prognostic model and the model yielded scores for low-,medium-,and high-risk patients accorrding to the6-month survival.The new model outperformed the three published models with regard to 3-,6-,and 12-month survival using pairwise comparison of AUC.Moreover,in this study,log-rank test show the new prognostic model and the other three known prognostic index between each groups were statistically different(P < 0.001).New prognostic model for different treatment also have significant statistical difference(P < 0.001).Conclusion:The new prognostic classification model integrated within EGFR mutation can be used to predict the prognosis of brain metastases from lung adenocarcinoma.It shows an obvious superiority than other three recognized prognostic classification indexes,and it was valid for patient survival estimation and warrants more study in larger trials.