Construction And Evaluation Of Prognostic Nomogram Model Based On Preoperative SIRI,HELPP And CONUT For Radical Resection Of Pancreatic Head Cancer

Objective:1)To evaluate the Systemic Inflammatory Response Index(SIRI),Heidelberg Prognostic Pancreatic Cancer,The relationship of HELPP score and Controlling Nutritional Status(CONUT)score with clinicopathological characteristics and survival prognosis of patients after radical surgery for pancreatic head cancer,and the potential application value of these three nutritional indicators in prognosis of pancreatic head cancer.2)Based on the relevant factors affecting the postoperative survival prognosis obtained by the research,the paper constructs the postoperative survival prediction model and verifies it,in order to provide relevant theoretical basis for the individualized treatment and improvement of the prognosis of patients with pancreatic head cancer.MethodsIn this study,a total of 169 patients diagnosed with pancreatic head cancer and accompanied by radical pancreaticoduodenectomy were collected in the Department of Hepatobiliary,Pancreaticosplenic Surgery,Affiliated Hospital of Inner Mongolia Medical University from January 1,2012 to December 31,2020,and confirmed in postoperative pathological specimens with lesions limited to the pancreatic head.General clinical data and serological assay indexes of patients within 1 week before surgery were collected,and SIRI,HELPP and CONUT scores were calculated according to the hematological indexes.Patients were divided into high and low groups by SIRI,HELPP and CONUT scores according to the optimal cut-off value,and the differences in clinicopathological factors between the groups were compared.Kaplan-Meier method was used to calculate the postoperative survival rate and draw the survival curve.Overall survival was compared by Log-Rank test.COX proportional risk model was used to analyze the prognostic factors affecting the overall survival of patients with pancreatic head cancer.Adopt the receiver-operating characteristics(ROC)area under curve(AUC)to compare the diagnostic value of various factors;Med Calc software was used to compare the difference of area under ROC curve.The results of COX multifactor analysis were summarized,and P < 0.05 factors were selected to draw a Nomogram.The consistency index(C-index),calibration curve and ROC curve were used to test the predictive ability of the verification column graph compared with SIRI,HELPP score and CONUT score,and finally the online dynamic column graph was drawn.Results:1)The relationship between SIRI and clinicopathologic factors: SIRI was divided into low SIRI group(< 1.74)and high SIRI group(≥1.74)according to Yoden index,and the relationship between SIRI and clinicopathologic features of patients with pancreatic head cancer was observed:SIRI was correlated with gender,degree of yellow stain,TNM stage,lymph node metastasis,degree of differentiation,CA19-9,ASA grading,CONUT score and HELPP score(P < 0.05).Compared with the low SIRI group,patients in the high SIRI group had more yellow stain,later TNM stage,more lymph node metastasis,and lower degree of differentiation.The level of CA19-9,ASA,CONUT and HELPP were higher.2)The relationship between HELPP score and clinicopathological factors: The HELPP score was divided into high and low groups according to HELPP 3>or≤3,and the relationship between HELPP score and clinicopathological features of patients with pancreatic head cancer was observed:HELPP is correlated with degree of yellow stain,TNM stage,lymph node metastasis,nerve invasion,degree of differentiation,CA19-9,ASA grading,CONUT score and SIRI,Moreover,in the HELPP group,the skin and sclera yellowing were more serious,the TNM stage was more advanced,the lymph node metastasis was more common,the nerve invasion was more common,the differentiation degree was lower,the ASA grade was higher,the CONUT score was higher,and the SIRI was higher.3)The relationship between CONUT score and clinicopathologic factors: The score was divided into high and low groups according to ≥3 points and < 3 points,and the relationship between CONUT score and clinicopathologic features of patients with pancreatic head cancer was observed: preoperative CONUT score was statistically significant with gender,degree of yellow staining,TNM stage,degree of differentiation,HELPP score and SIRI(P <0.05).Among them,patients in the high CONUT group had deep scleral yellow staining,late TNM stage,low differentiation,high HELPP score and high SIRI.4)COX univariate and multivariate analysis of effects on prognosis after radical resection of pancreatic head carcinoma: Univariate COX regression analysis showed that:Yellow stain,TNM stage,lymph node metastasis,nerve invasion,differentiation degree,CA19-9,SIRI,HELPP score and CONUT score were risk factors for poor prognosis after radical resection of pancreatic head cancer(P < 0.05).Multivariate COX regression analysis showed that:TNM stage,tumor diameter,CA19-9,SIRI,HELPP score and CONUT score were all independent risk factors for prognosis(P < 0.05).5)According to the results of COX multivariate regression,a line graph model was constructed to predict the 1-year,2-year and 3-year survival rate of patients after radical surgery for pancreatic head cancer.The C-index of line graph was 0.841,and the 1-year,2-year and 3-year AUC of ROC curve were 0.948,0.909 and 0.895,respectively.The calibration curve showed a close correlation between the actual survival rate of patients with pancreatic head cancer in the three cohorts and the predicted survival rate estimated by the graph.In order to better and more convenient clinical application,we also build a web version of dynamic line graph based on the line graph model.Conclusions:Patients with SIRI < 1.74 have better prognosis.HELPP score and CONUT score are simple and practical prognostic scoring systems,which are expected to become potential prognostic indicators for patients with pancreatic head cancer after radical resection.TNM stage,tumor diameter,CA19-9,SIRI,HELPP score and CONUT score were independent risk factors for the prognosis of pancreatic head cancer.The establishment of a prognostic histogram model for patients with pancreatic head cancer can better predict the long-term survival of patients.