Analysis of risk factors for recurrence and prediction model of bladder cancer
10.19405/j.cnki.issn1000-1492.2023.05.023
- Author:
Rui Zhu
1
,
2
;
Yuelong Feng
1
,
2
;
Shuping Yang
1
,
2
;
Chao Chen
1
,
2
;
Lei Jia
1
,
2
Author Information
1. Dept of Urology,Ningxia Hui Autonomous Region People &prime
2. s Hospital , Yinchuan 750002
- Publication Type:Journal Article
- Keywords:
bladder cancer;
model;
recurrence
- From:
Acta Universitatis Medicinalis Anhui
2023;58(5):845-849
- CountryChina
- Language:Chinese
-
Abstract:
Objective:Review the independent risk factors of postoperative recurrence in surgical treatment of bladder cancer patients to construct a model of bladder cancer recurrence.
Methods :A total of 240 surgically treated bladder cancer patients were followed up for at least 1 year and divided into recurrence ( n = 54) and non⁃recurrence (n = 186) . The general data of patients were comparative analyzed , and the different and statistically significant data were further analyzed by ROC curve , and the statistically significant data were included in the multivariate analysis after logistic obtaining univariate analysis results. Risk factors were included in the model construction , and the model correction curve and clinical net benefit analysis were analyzed. The model could be used to predict postoperative recurrence in bladder cancer patients.
Results:The ROC curves of the statistically significant continuous variables were analyzed in the general data , and the results showed that the AUC of PNI , BLCA⁃4 , BTA , NMP22 and CEA were 0. 932 , 0. 979 , 0. 998 , 0. 677 and 0. 981 , respectively , and the optimal truncation values were ≤40. 18% , > 140. 04 ng/mg , ≤7. 22 U/mg , > 7. 68 μg/mg , and > 1. 99 ng/mg, respectively. Statistically significant data from univariate analysis were incorporated into the logistic regression model , and the results showed that PNI ≤40. 18% , BLCA⁃4 > 140. 04 ng/mg , BTA≤7. 22 U/mg , NMP22 > 7. 68 μg/mg was a risk factor for recurrence in patients with bladder cancer. Subsequently , PNI , BLCA⁃4 , BTA , and NMP22 were incorporated into the construction of the model as predictors of recurrence in patients with bladder cancer. Based on the model correction curve and clinical net benefit analysis , the internal verification results showed that the C ⁃index of the model predicting bladder cancer recurrence was 0. 296 (95% CI: 0. 078 - 1. 329) . The calibration curve showed good consistency between the observed and predicted values. The model predicted a risk threshold > 0. 128 for patients with bladder cancer, and the model provided a clinical net benefit; in addition , the model had a higher clinical net benefit than PNI ,BLCA⁃4 , BTA , and NMP22.
Conclusion:The model correction curve and clinical net benefit analysis , the results of internal verification show that the model can be used to predict recurrence in patients with bladder cancer.
- Full text:202408132141123780膀胱癌术后复发危险因素分析及模型构建_朱瑞.pdf
