Influencing Factors and Predictive Model Construction for Survival Prognosis in Patients After Radical Cystectomy
Li Yueming
Wang Jiaxin
Li Xinyi
Lin Jielin
Luo Jinquan
Gong Mancheng
Abstract：Objective To investigate the influencing factors of survival prognosis in patients after radical cystectomy and to further construct a nomogram predictive model,aiming to provide more guidance for early identification of high-risk groups with poor prognosis and subsequent formulation of individualized treatment plans.Methods A total of 136 patients with bladder cancer who underwent radical cystectomy at Zhongshan People's Hospital of Guangdong Province from January 2014 to January 2022 were retrospectively enrolled.Clinical,imaging,and follow-up survival data were recorded.Univariate and multivariate Cox proportional hazards models were used to identify independent influencing factors for overall survival(OS)after radical cystectomy.A nomogram predictive model for postoperative survival prognosis was constructed,and its clinical predictive efficacy was further evaluated.Results The median follow-up time for the 136 patients was 47.0(range,1.0-122.0)months,and the median OS was 32.0 months.Univariate analysis revealed that age,pathological histological grade,neutrophil-to-lymphocyte ratio(NLR),lymphocyte-to-monocyte ratio(LMR),platelet-to-lymphocyte ratio(PLR),and Magnetic Resonance Imaging Reporting and Data System(MRI-RADS)score for the bladder were all associated with survival prognosis after radical cystectomy(P<0.05).Multivariate analysis using the Cox proportional hazards model identi-fied age,pathological histological grade,NLR,LMR,PLR,and MRI-RADS score as independent influencing factors for survival prognosis(P<0.05).A nomogram was constructed based on these independent factors identified by multivariate analysis.The scores assigned were as follows:age(24 points),pathological histological grade(17 points),NLR(39 points),LMR(51 points),PLR(25 points),and MRI-RADS score(104 points).Receiver operating characteristic(ROC)curve analysis demonstrated that the model had an area under the curve(AUC)of 0.918(95%CI:0.844-0.982,P<0.001),a sensitivity of 91.47%,a specificity of 85.90%,and a Youden index of 0.786 for predicting survival prognosis after radical cys-tectomy.Conclusion The survival prognosis of patients after radical cystectomy were not only affected by age,histopatho-logical grade and surgical method,but also independently correlated with MRI bladder imaging report and data system score.Based on the above factors related to the nomogram model can accurately identify the high-risk population of poor postopera-tive survival prognosis.
Keywords：bladder cancerradical cystectomyoverall survival timenomogram
Publication Date：2025-12-28
Online Publishing Date：2026-03-11(First online date of this platform, not the publication date of the document)
Pages：6( 385-390 )