| Background:Small cell lung cancer(SCLC)is a highly aggressive malignancy that accounts for 15%-20% of all lung cancer cases.Despite progress in diagnosis and treatment,the 5-year survival rate for SCLC remains low,at only around 6%-7%.Limited-stage small cell lung cancer(LS-SCLC)is a subtype that represents cancer confined to one hemithorax and regional lymph nodes,without distant metastasis.Currently,standard treatment for LS-SCLC typically involves a combination of chemotherapy and radiation therapy.However,the role of surgery in treating LS-SCLC is still a controversial topic.This study aims to collect and analyze clinical data from a large number of LS-SCLC patients using real-world data,and establish and validate a model that can predict the probability of surgical benefit for LS-SCLC patients.This will help doctors to develop more personalized treatment plans,maximizing the survival rate and quality of life for patients.Objective:To analyze factors related to the prognosis of surgery for limited-stage small cell lung cancer and to construct and validate a predictive model that predicts the probability of surgical benefit in patients with LS-SCLC.Methods:This study utilized the Surveillance,Epidemiology,and End Results(SEER)database to select 9,173 patients diagnosed with primary limited-stage small-cell lung cancer between 2010 and 2015,who met the inclusion criteria.General clinical and pathological information was collected,including age,sex,race,primary tumor site,tumor-related location,tumor grade,T stage,N stage,and treatment modality(including surgery,radiotherapy,and chemotherapy).The staging of all small-cell lung cancer patients was reclassified according to the eighth edition TNM staging of the American Joint Committee on Cancer.Propensity score matching(PSM)was used to eliminate related biases between the surgical and non-surgical groups.Based on the median survival of the non-surgical group,the surgical group was further divided into surgical benefit and non-benefit subgroups.R software(version 4.0.5)was used for data statistics,analysis,and visualization.The main endpoint of this study was overall survival(OS)of the study subjects,and the secondary endpoint was lung cancerspecific survival rate(LCSS).Kaplan-Meier method and Log-rank test were used to compare the survival analysis between groups.Multivariate Cox regression analysis was performed to further screen for independent prognostic factors for small-cell lung cancer survival.After incorporating relevant independent prognostic factors,multivariate logistic regression analysis was used to screen for prognostic factors associated with surgical benefit and to establish a model for predicting the probability of surgical benefit in this patient population.The nomogram prediction model was used,and the C-index,ROC curve,and calibration curve were used to validate and evaluate the effectiveness of the model.Finally,the prediction model was used to classify all patients who underwent surgery for survival analysis,further validating the feasibility and accuracy of the model.Results:A total of 9,173 patients with LS-SCLC were finally included,including a total of 724 patients in the group undergoing surgery and 8,449 patients in the non-surgical group.When the study’s endpoint was OS,the pre-PSM surgery group had a longer median survival than the non-surgical group,31 months vs.13 months(HR=0.50,95% CI:0.45-0.54,P<0.001).After PSM,median survival remained at 28 months vs.13 months(HR = 0.57,95% CI: 0.50– 0.65,P<0.001).Age,gender,race,T-stage,Nstage,chemotherapy treatment,and radiotherapy treatment were included in the model after multivariate Cox regression analysis to perform multivariate logistic regression analysis for the prognosis of LS-SCLC,and the final model incorporated the six best variables of age,gender,race,T-stage,N-stage,and chemotherapy treatment to construct the prediction model.The C-index value of the model was0.724,and the AUC value was 0.723.The ROC curve and calibration curve showed that the prediction model was in good agreement with the actual observed results and had high application value.Finally,the 724 patients with limited-stage small cell lung cancer who underwent surgery were grouped according to the high probability of surgical benefit,and the survival curves showed that the survival time was significantly longer in the surgical benefit group than in the non-benefit group(HR=0.39,95% CI: 0.28-0.53,P<0.001)or the non-surgical group(HR=0.47,95% CI:0.43-0.52,P< 0.001),but there was no statistically significant difference in survival between the non-surgical and surgical non-benefit groups(HR = 0.97,95% CI: 0.88-1.07,P=0.520).Conclusion:Patients with limited-stage small cell lung cancer who undergo surgery have a good prognosis,and undergoing surgery is important for the prognosis of limitedstage small cell lung cancer.We also developed a nomogram model that predicts the probability of benefit from surgical treatment in patients with limited-stage small cell lung cancer and has good predictive and discriminatory ability.Our findings will assist physicians and patients in better understanding the benefits of surgical treatment for LS-SCLC,as well as provide guidance based on realistic data to assist physicians in developing more individualized treatment plans,thereby maximizing patient survival and quality of life. |
PDF Full Text Request