Construction of visualization model for predicting postoperative recurrence of bladder cancer based on preoperative IL-6,PGE2 and TNF-α levels
Objective To construct a visualization model for predicting the postoperative recurrence of bladder cancer based on preop-erative serum interleukin-6(IL-6),prostaglandin E2(PGE2),and tumor necrosis factor-alpha(TNF-α)levels.Methods The clin-ical data of 348 patients with bladder cancer admitted to our hospital from June 2018 to February 2023 were retrospectively collected,and they were randomly divided into the training set(n=232)and validation set(n=116)at a ratio of 2∶1 by the computer-generated random number table.All patients were followed up.The patients who had recurrence were included in the recurrence group,and those who did not have recurrence were included in the non-recurrence group.The levels of serum IL-6,PGE2,and TNF-α and general data of the recurrence group and non-recurrence group in the training set were compared.The Logistic regression model was used to analyze the influencing factors of postoperative recurrence of bladder cancer in the training set and establish a regression equation.The receiver operating characteristic(ROC)curve was used to analyze the efficacy of preoperative IL-6,PGE2,and TNF-α alone and their combi-nation in predicting the postoperative recurrence of bladder cancer.A risk prediction nomogram model for the postoperative recurrence of bladder cancer was established and validated.Results Compared with the non-recurrence group,the levels of serum IL-6,PGE2,and TNF-α,tumor diameter,and proportions of multifocal tumors,tumor stage T2～T4,and WHO tumor pathological gradeⅡ～Ⅲin the recurrence group were increased,while the proportion of regular bladder perfusion after surgery was decreased(P＜0.05).Logistic regression analysis showed that preoperative serum IL-6,PGE2,and TNF-α levels,tumor stage,and WHO tumor pathological grade were the influencing factors of postoperative recurrence of bladder cancer(P＜0.05).The established Logistic regression equation was:Y=1.718X1+2.081X2+1.815X3+2.319X4+1.868X5.The ROC curve showed that the optimal cut-off points of preoperative serum IL-6,PGE2,and TNF-α levels for predicting the postoperative recurrence of bladder cancer were 0.60 ng/L,57.13 pg/mL,and 2.10 ng/mL,respectively.The areas under the ROC curve(AUCROC)of serum IL-6,PGE2,and TNF-α alone and their combination were 0.729,0.743,0.733,and 0.825,respectively.Based on the structure of Logistic regression analysis in the training set,a risk nomo-gram model for predicting the postoperative recurrence of bladder cancer was established.The prediction sensitivity,specificity,and AUCROC of the model in the training set and validation set were 94.12%and 90.20%,90.06%and 87.29%,and 0.940 and 0.914,re-spectively.The internal validation results of the Bootstrap method showed that the C-index values of the training set and validation set were 0.918(95%CI:0.824-0.987)and 0.901(95%CI:0.835-0.957),respectively.Conclusion Preoperative serum IL-6,PGE2,and TNF-α levels are the influencing factors of postoperative recurrence of bladder cancer,and the risk nomogram model based on them has good prediction efficacy.
bladder cancerpostoperative recurrenceinterleukin-6prostaglandin E2tumor necrosis factor-alphaNomogram model
NETL
NSTL
万方数据
维普
