» Articles » PMID: 36291803

Predicting Recurrence of Non-Muscle-Invasive Bladder Cancer: Current Techniques and Future Trends

Overview
Journal Cancers (Basel)
Publisher MDPI
Specialty Oncology
Date 2022 Oct 27
PMID 36291803
Authors
Affiliations
Soon will be listed here.
Abstract

Bladder cancer (BC) is the 10th most common cancer globally and has a high mortality rate if not detected early and treated promptly. Non-muscle-invasive BC (NMIBC) is a subclassification of BC associated with high rates of recurrence and progression. Current tools for predicting recurrence and progression on NMIBC use scoring systems based on clinical and histopathological markers. These exclude other potentially useful biomarkers which could provide a more accurate personalized risk assessment. Future trends are likely to use artificial intelligence (AI) to enhance the prediction of recurrence in patients with NMIBC and decrease the use of standard clinical protocols such as cystoscopy and cytology. Here, we provide a comprehensive survey of the most recent studies from the last decade (N = 70 studies), focused on the prediction of patient outcomes in NMIBC, particularly recurrence, using biomarkers such as radiomics, histopathology, clinical, and genomics. The value of individual and combined biomarkers is discussed in detail with the goal of identifying future trends that will lead to the personalized management of NMIBC.

Citing Articles

A novel nomogram for predicting post-operative recurrence for patients with intermediate and high-risk non-muscle invasive bladder cancer after thulium laser resection of bladder tumors or conventional transurethral resection of bladder tumors....

Xu M, Sun J, Xiang Y, Hua Z, Liu C, An Y Transl Androl Urol. 2025; 14(1):91-102.

PMID: 39974795 PMC: 11833529. DOI: 10.21037/tau-24-535.


Evaluation of six novel biomarkers for predicting recurrence of non-muscle invasive bladder cancer after endoscopic resection- a prospective observational study.

Bardowska K, Krajewski W, Kolodziej A, Koscielska-Kasprzak K, Bartoszek D, Zabinska M World J Urol. 2025; 43(1):114.

PMID: 39928162 PMC: 11811479. DOI: 10.1007/s00345-025-05485-9.


Large-scale validation study of an improved semiautonomous urine cytology assessment tool: AutoParis-X.

Levy J, Chan N, Marotti J, Kerr D, Gutmann E, Glass R Cancer Cytopathol. 2023; 131(10):637-654.

PMID: 37377320 PMC: 11251731. DOI: 10.1002/cncy.22732.


Examining longitudinal markers of bladder cancer recurrence through a semiautonomous machine learning system for quantifying specimen atypia from urine cytology.

Levy J, Chan N, Marotti J, Rodrigues N, Ismail A, Kerr D Cancer Cytopathol. 2023; 131(9):561-573.

PMID: 37358142 PMC: 10527805. DOI: 10.1002/cncy.22725.


Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling.

Zhang Y, Zhang X, Cheng Y, Li B, Teng X, Zhang J Mil Med Res. 2023; 10(1):22.

PMID: 37189155 PMC: 10186733. DOI: 10.1186/s40779-023-00458-8.

References
1.
Albayrak S, Zengin K, Tanik S, Atar M, Unal S, Imamoglu M . Can the neutrophil-to-lymphocyte ratio be used to predict recurrence and progression of non-muscle-invasive bladder cancer?. Kaohsiung J Med Sci. 2016; 32(6):327-33. DOI: 10.1016/j.kjms.2016.05.001. View

2.
Ali-El-Dein B, Sooriakumaran P, Trinh Q, Barakat T, Nabeeh A, Ibrahiem E . Construction of predictive models for recurrence and progression in >1000 patients with non-muscle-invasive bladder cancer (NMIBC) from a single centre. BJU Int. 2013; 111(8):E331-41. DOI: 10.1111/bju.12026. View

3.
Shkolyar E, Jia X, Chang T, Trivedi D, Mach K, Meng M . Augmented Bladder Tumor Detection Using Deep Learning. Eur Urol. 2019; 76(6):714-718. PMC: 6889816. DOI: 10.1016/j.eururo.2019.08.032. View

4.
El-Assmy A, Abou-El-Ghar M, Refaie H, Mosbah A, El-Diasty T . Diffusion-weighted magnetic resonance imaging in follow-up of superficial urinary bladder carcinoma after transurethral resection: initial experience. BJU Int. 2012; 110(11 Pt B):E622-7. DOI: 10.1111/j.1464-410X.2012.11345.x. View

5.
Maldonado L, Brait M, Michailidi C, Munari E, Driscoll T, Schultz L . An epigenetic marker panel for recurrence risk prediction of low grade papillary urothelial cell carcinoma (LGPUCC) and its potential use for surveillance after transurethral resection using urine. Oncotarget. 2014; 5(14):5218-33. PMC: 4170626. DOI: 10.18632/oncotarget.2129. View