| Background:Lung cancer is one of the malignant tumors with high morbidity and mortality worldwide,whether male or female.Lung cancer is classified into non-small cell lung cancer(NSCLC)and small cell lung cancer(SCLC).Small cell lung cancer is the main pulmonary neuroendocrine tumor.Due to the characteristics of susceptible to blood vessels invasion,short doubling time and earlier metastasis,the prognosis is poor.Systemic platinum-based chemotherapy either alone or combined with concurrent radiotherapy is currently considered to be standard or preferred treatment for SCLC patients,because most SCLC cases are highly sensitive to initial chemotherapy and radiotherapy.However,drug resistance and relapse often occur quickly,leading to adverse outcomes.In recent years,the role of surgery in multimodal treatment protocols has been mentioned again.But because the prognosis of resectable patients cannot be accurately predicted,surgery has not been fully utilized in early-stage patients.Survival outcomes of patients with resected SCLC differ widely.The aim of our study was to build a model for individualized risk assessment and accurate prediction of overall survival(OS)in resectable SCLC patients.Methods:We collected 1052 patients with resected SCLC from the Surveillance,Epidemiology,and End Results(SEER)database.Independent prognostic factors were selected by COX regression analyses,based on which a nomogram was constructed by R code.External validation were performed in 114 patients from Shandong Provincial Hospital.The C-index and calibration curve are used to assess the prediction accuracy and reliability of the new model.The decision curve analyses(DCA)and integrated discrimination improvement(IDI)were used to conduct comparison between the new model and the AJCC staging system.And z-test was used to test the IDI index for significance.Kaplan-Meier survival analyses were applied to test the application of the risk stratification system.The endpoint of this study was overall survival(OS).All above data analysis was performed by SPSS 25.0(IBM,SPSS Statistics,Chicago,IL,USA)software and RStudio software(version 1.1.463).Results:Sex,age,T stage,N stage,LNR,surgery and chemotherapy were identified to be independent predictors of OS,according which a nomogram was built.Concordance index(C-index)of the training cohort were 0.721,0.708,0.726 for 1-,3-and 5-year OS respectively.And that in the validation cohort were 0.819,0.656,0.708 respectively.Calibration curves also showed great prediction accuracy.In comparison with 8th AJCC staging system,improved net benefits in decision curve analyses(DCA)and evaluated integrated discrimination improvement(IDI)were obtained.The risk stratification system can significantly distinguish the ones with different survival risk.We implemented the nomogram in a user-friendly webserver.Conclusions:We built a novel nomogram and risk stratification system integrating clinicopathological characteristics and surgical procedure for resectable SCLC.The model showed superior prediction ability for resectable SCLC and performs better than the 8th AJCC TNM staging system.This model is expected to provide prognostic assessment and clinical consultation for patients with resectable small cell lung cancer. |
PDF Full Text Request