Exploration Of Best Nomogram To Predict Recurrence Of Pathological Stage IA Lung Adenocarcinoma Patients Treated By Radical Surgery

Purpose:Previous recurrence risk models offered individualized prediction using a more diverse set of factors than traditional staging measures American Joint Committee on Cancer Tumor Node Metastasis(AJCC TNM)Staging System.Several studies have demonstrated gene mutation as a new prognostic factor,such as Epidermal growth factor receptor(EGFR),V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog(KRAS)and so on.This study aimed to analyze a comprehensive and reliable Nomogram prognostic model to predict recurrence in stage IA lung adenocarcinoma(ADC)with radical resection.Methods:This was a retrospective,single-center and case-control study.Clinicopathologic,genetic,therapeutic features and survival status were collected.Univariate and multivariate Cox proportional hazards model was conducted.The nomogram for recurrence prediction was developed using Cox proportional hazards regression.Three nomograms were established based on a)AJCC 8th TNM Staging,b)multivariate analysis results and c)risk factors recorded in published references.The higher concordance index(C-index)of model identified better performance of nomogram.Results:1499 patients with pathological stage IA ADC from Cancer Hospital,Chinese Academy of Medical Sciences from October 2012 to December 2015 were enrolled in this study.The recurrence rate was 3.5%(53/1499)which have included local recurrence,distant metastasis and death.No recurrence of 180 patients randomly selected and analyzed in this study.Median disease free survival(DFS)was not reached.The C-index of AJCC 8th TNM staging and the nomogram based on multivariate analysis was 0.598(95%CI 0.538-0.659)and 0.696(95%CI 0.629-0.764),respectively.The nomogram established on prognostic factors in previous studies,which included gene mutation such as EGFR,KRAS and ALK,showed higher discrimination with C-index 0.833(95%CI 0.786-0.879).Conclusion:This was individualized nomogram combining clinicopathologic features with genetic information to predict recurrence in ADC.Our nomogram was more reliable to guide prognostic factors and recurrence rate in stage IA ADC patients.