Predictors Of Prognosis After Radical Gastrectomy And Establishment Of Nomogram Model

BackgroundGastric cancer(GC)is a common malignancy worldwide and the third leading cause of cancer-related death.The incidence of GC varies greatly in different regions of the world,and it is second only to lung cancer in China.Radical surgery is an important means to improve the survival of gastric cancer.At present,the proportion of early GC in China remains low,and the survival of most advanced GC is still poor even with multi-disciplinary treatment based on surgery.It is important to predict the survival of GC patients underwent radical surgery,which is helpful for early detection of high-risk patients and development of individualized treatment.Currently,a variety of methods and markers have been proved to be effective,but most of these indicators are still controversial.There are also some shortcomings,such as:evaluating one or a few indicators and technical limitations.Therefore,it is of clinical importance to evaluate the predicting value of clinicopathological features and routine laboratory indicators for GC prognosis.Nomogram is a tool to calculate the predicted value of individual outcome events.It quantifies the individual risk,and the visual characteristics make the prediction model more readable and convenient for clinical application.ObjectiveAssessing the predictive value of clinicopathological features and routine laboratory indicators in GC,to explore the factors with predictive value,and create a nomogram for individual risk prediction.MethodsThe complete clinicopathological and follow-up data of patients with gastric cancer who underwent radical gastrectomy in the First Affiliated Hospital of Zhengzhou University from October 2007 to May 2016 were collected retrospectively.Cox proportional hazard model was used to identify the independent predictors of disease-free survival time(DFS)and cancer-specific survival time(CSS)respectively,and incorporated into their respective nomogram models.ResultsThrough univariate and multivariate survival analysis,age(>60 years),depth of invasion(pT3-4),lymph node invasion(pN1-3),histologic classification(poor),adjuvant chemotherapy(no),albumin fibrinogen ratio(AFR)(<13.33),and carbohydrate antigen 19-9(CA19-9)(>27 U/mL)independently indicated inferior disease-free survival(DFS).Meanwhile,depth of invasion,lymph node invasion,histologic classification,adjuvant chemotherapy,AFR and CA19-9 were incorporated in the prediction of cancer-specific survival(CSS).A combined AFR and CA19-9 prognostic score(CACPS)was established.Lower AFR(<13.33)and higher CA19-9(>27 U/mL)were allocated 1 point each in the CACPS(ranging from 0 to 2).The CACPS can be used as an independent predictor for DFS and CSS respectively in multivariate analysis(for DFS:CACPS 1:HR=2.039,P=0.001;CACPS 2:HR=2.419,P=0.002;for CSS:CACPS 1:HR=2.035,P=0.002;CACPS 2:HR=2.255,P=0.007),with a higher CACPS indicating poor survival according to Kaplan-Meier curves(both P<0.001).Moreover,a nomogram for DFS and CSS was generated using the significant characteristics in the multivariate analysis,and it exhibited high accuracy(for DFS:C-index=0.743,95%CI:0.698-0.788;for CSS:C-index=0.766,95%CI:0.718-0.814)in compared tumor-node-metastasis staging(for DFS:C-index=0.692,95%CI:0.650-0.734;for CSS:C-index=0.720,95%CI:0.675-0.764).Conclusions1.For gastric cancer after R0 resection,CACPS is a relatively accurate independent prognostic factor.2.The preoperative CACPS and nomogram exhibited high accuracy in predicting the DFS and CSS for GC patients who underwent curative resection economically and conveniently.