| Background:Colorectal cancer is one of the most common cancers in the world and is now the third largest cancer in the world that kills patients.At present,surgery-based comprehensive treatment can effectively prolong the survival of patients.but early postoperative recurrence is still the main cause of death,and some scholars have found that relevant clinicopathological indicators and other factors can have a certain impact on early postoperative recurrence of patients,and the probability of recurrence can be reduced through the intervention of influencing factors,thereby improving the prognosis of patients.At present,there are a variety of markers for predicting early recurrence of colorectal cancer after surgery,but the predictive ability of many of these indicators is controversial and needs to be further verified.At the same time,some scholars only predict it from a single factor,and its results are not comprehensive,while nomogram,as a graphical tool,can use charts to directly calculate the value of variables,provide the overall probability of a specific outcome,and have greater advantages than traditional models in clinical practice,and predict patient outcomes by predicting patient outcomes through relevant risk variables and risk scores,while also being able to predict individual clinical outcomes with individual characteristics,thereby promoting personalized treatment.Objective:In this study,we try to explore the independent risk factors for early recurrence of colorectal cancer through clinicopathological features,and further construct a nomogram prediction model for early recurrence of CRC,so as to assist clinical decision-making and achieve individualized and precise treatment.Materials and Methods:The clinicopathological data of 406 patients admitted to the First Affiliated Hospital of Henan University from October 2013 to October 2020 with initial diagnosis of colorectal cancer and radical colorectal cancer resection were retrospectively and continuously included,and the modeling group(285cases)and the validation group(121 cases)were randomly selected according to the ratio of 7:3,and gender,age,BMI,tumor location,TNM stage,CEA,CA199,LMR,NLR,PLR,PNI,SII,AST,ALT,albumin,Variables such as tumor diameter,vasculature invasion,etc.The nomogram model was established by performing single-factor and multivariate logistic regression analysis on patients in the modeling group(285cases)to screen for independent risk factors.The factors of P<0.05 were included in the model,and R(4.2.0)software was used to construct a nomogram prediction model;at the same time,the discrimination degree of the model was evaluated by using the area under the receiver working characteristic(ROC)curve(AUC)in the modeling group(285 cases)and the validation group(121 cases),the calibration curve of Calibration Calibration was used to evaluate the consistency between the predicted probability of the model and the actual results,and the clinical application value of the model was evaluated by decision curve analysis(DCA).Results:1.There was no significant difference in the basic clinicopathological data of patients in the modeling group(285 cases)and the verification group(121 cases)(P>0.05);2.The basic clinicopathological data of patients in the early recurrence group(111 cases)and the non-early recurrence group(295 cases)showed that TNM stage,CEA,NLR,PLR,PNI,SII,ALB,vascular invasion and other indicators were statistically significant(P<0.05),while gender,age,BMI,tumor location,CA19-9,LMR,ALT,AST,tumor size,etc.were not statistically significant(P>0.05).3.Univariate analysis of patients in the modeling group(285 patients)showed that TNM staging(P = 0.005),CEA(P = 0.036),NLR(P<0.001),PLR(P<0.001),PNI(P<0.001),SII(P<0.001),vascular invasion(P=0.019),ALB(P=0.001)were associated with early recurrence after colorectal cancer surgery;4.Multivariate logistic regression analysis showed that TNM staging(OR=2.547,95%CI 1.282-5.060,P = 0.008),NLR(OR=6.133,95%CI 2.592-14.515,P<0.001),PLR(OR=3.619,95%CI 1.613-8.121,P=0.002),PNI(OR=0.095,95%CI 0.033-0.272,P<0.001)were independent risk factors for early recurrence of colorectal cancer after surgery.5.According to the results of univariate and multivariate analysis,the nomogram prediction model has good prediction performance,the modeling group AUC=0.879(95%CI 0.839-0.919)the verification group AUC=0.856(95%CI 0.780-0.931),the area under the ROC curve(AUC)of the modeling group is less different from the verification group,indicating that the nomogram has good discrimination,and the calibration curves of both groups are close to the ideal curve.This shows that the model has a good degree of calibration,and the corresponding decision curve is drawn according to the nomogram model,whether it is the modeling group group or the validation group,the model results can obtain positive benefits in most thresholds,suggesting that the model has good clinical applicability.Conclusion:1.Univariate analysis showed that TNM staging,CEA>5g/L,NLR≥2.37,PLR≥168,PNI<45.6,SII≥521,vascular invasion,ALB were associated with early recurrence after colorectal cancer surgery;2.Multivariate analysis showed that TNM staging,NLR≥2.37,PLR≥168,PNI<45.6 were independent risk factors for early recurrence of colorectal cancer after surgery;3.By establishing a predictive and clinically applicable nomogram model,this study can provide a reference for clinicians to individualize diagnosis and treatment of patients. |
