ORIGINAL RESEARCH article
Front. Oncol.
Sec. Genitourinary Oncology
Modeling and Validation of Serum miR-18a and miR-122 Levels as Predictors of Recurrence after Laparoscopic Radical Cystectomy Procedure for Bladder Cancer Based on Nomogram Model
Provisionally accepted- Qingdao Hospital, University of Health and Rehabilitation Sciences, Qingdao, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Objective: This study aimed to identify factors influencing recurrence after laparoscopic radical cystectomy for bladder cancer (BC) based on serum levels of miR-18a and miR-122, and to develop and validate a nomogram prediction model. Methods: The relevant information of BC patients who received laparoscopic radical cystectomy procedure in our hospital from January 2021 to October 2022 was collected retrospectively. The patients were divided into a training set and a validation set at a ratio of 7:3 by the complete randomization method. Independent predictive variables included in the Nomogram model were determined and modeled through univariate analysis and multivariate Logistic regression analysis. The receiver operating characteristic curve (ROC) and calibration curves were used to evaluate the predictive efficacy of the model, and decision curve analysis (DCA) was used to evaluate its clinical application value. Results: A total of 280 research subjects were included. Recurrence occurred in 46 (23.47%) of the 196 patients in the training set and 21 (25.00%) of the 84 patients in the validation set. The results of the multivariate logistic regression analysis showed that preoperative serum miR-18a levels, preoperative serum miR-122 levels, postoperative serum carcinoembryonic antigen levels, postoperative serum carbohydrate antigen 19-9 levels, and postoperative antibiotic use duration were significantly associated with recurrence after laparoscopic radical cystectomy for BC. The model was well calibrated and fitted in the training and validation sets. The ROC curve showed that the AUC of the nomogram model to predict postoperative recurrence were 0.796(95% CI: 0.688-0.904) and 0.762(95% CI: 0. 578-0.946), respectively. DCA indicated that the model had clinical application value. Conclusion: The Nomogram model for recurrence after laparoscopic radical cystectomy procedure for BC has good prediction ability.
Keywords: Bladder cancer, Laparoscopic radical cystectomy, Nomogram prediction model, Serum miR-122, Serum mir-18a
Received: 19 Feb 2025; Accepted: 16 Dec 2025.
Copyright: © 2025 Wang, Deng and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Shuai Wu
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
