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Guest Editor

1. Department of Urology, Shuang Ho Hospital, New Taipei City, Taiwan
2. TMU Research Center of Urology and Kidney, Department of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
Interests: uro-oncology; bladder; urology; endocrinology; molecular biology; translation medicine

Prof. Dr. Horng-Heng Juang

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Guest Editor

Department of Anatomy, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
Interests: prostate cancer; bladder cancer; genitourinary oncology; biomarkers; molecular biology

Special Issue Information

Dear Colleagues,

This Special Issue is about bladder cancer. Bladder cancer has become the ninth most common cancer worldwide, and the sixth most common malignancy in the United States, according to an epidemiologic statistics report published in 2017. Although many tumor markers associated with the development of bladder cancer have been widely reported, the rates of mortality and recurrence of bladder cancer are still high. Bladder cancer usually presents at an early stage, with most patients presenting with Tis or T1 disease and, thus, high recurrence rates. At present, different recurrence rates are observed according to the pathological staging and tumor grading. The reasons for this increase in recurrence, and tumor biology in particular, are poorly understood. Treatment of bladder cancer has evolved in recent years, with several new treatment techniques that lead to improvements in uro-oncology. This Special Issue mainly aims to discuss a collection of basic research and clinical treatments for the early detection, early diagnosis and early treatment of bladder cancer.

Here, we welcome papers outlining tumor biology, diagnostics, and treatment modalities of bladder cancer.

Prof. Dr. Ke-Hung Tsui
Prof. Dr. Horng-Heng Juang
Guest Editors

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Keywords

bladder neoplasm
carcinoma
biology
surgery
biomarker
tumor grading
tumor staging

Published Papers (2 papers)

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Research

Open AccessArticle

Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors

and

Cancers 2023, 15(17), 4372; https://doi.org/10.3390/cancers15174372 (registering DOI) - 01 Sep 2023

Abstract

Accurate survival prediction for bladder cancer patients who have undergone radical cystectomy can improve their treatment management. However, the existing predictive models do not take advantage of both clinical and radiological imaging data. This study aimed to fill this gap by developing an approach that leverages the strengths of clinical (C), radiomics (R), and deep-learning (D) descriptors to improve survival prediction. The dataset comprised 163 patients, including clinical, histopathological information, and CT urography scans. The data were divided by patient into training, validation, and test sets. We analyzed the clinical data by a nomogram and the image data by radiomics and deep-learning models. The descriptors were input into a BPNN model for survival prediction. The AUCs on the test set were (C): 0.82 ± 0.06, (R): 0.73 ± 0.07, (D): 0.71 ± 0.07, (CR): 0.86 ± 0.05, (CD): 0.86 ± 0.05, and (CRD): 0.87 ± 0.05. The predictions based on D and CRD descriptors showed a significant difference (

p

= 0.007). For Kaplan–Meier survival analysis, the deceased and alive groups were stratified successfully by C (

p

< 0.001) and CRD (

p

< 0.001), with CRD predicting the alive group more accurately. The results highlight the potential of combining C, R, and D descriptors to accurately predict the survival of bladder cancer patients after cystectomy. Full article

(This article belongs to the Special Issue Staging and Pathology of Bladder Cancer)

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Open AccessArticle

Prospective Validation of the ROL System in Substaging pT1 High-Grade Urothelial Carcinoma: Results from a Mono-Institutional Confirmatory Analysis in BCG Treated Patients

and

Cancers 2023, 15(3), 934; https://doi.org/10.3390/cancers15030934 - 01 Feb 2023

Cited by 1 | Viewed by 950

Abstract

Patients with pT1 high-grade (HG) urothelial carcinoma (UC) and a very high risk of progression might benefit from immediate radical cystectomy (RC), but this option remains controversial. Validation of a standardized method to evaluate the extent of lamina propria (LP) invasion (with recognized prognostic value) in transurethral resection (TURBT) specimens is still needed. The Rete Oncologica Lombarda (ROL) system showed a high predictive value for progression after TURBT in recent retrospective studies. The ROL system was supposed to be validated on a large prospective series of primary urothelial carcinomas from a single institution. From 2016 to 2020, we adopted ROL for all patients with pT1 HG UC on TURBT. We employed a 1.0-mm threshold to stratify tumors in ROL1 and ROL2. A total of 222 pT1 HG UC were analyzed. The median age was 74 years, with a predominance of men (73.8%). ROL was feasible in all cases: 91 cases were ROL1 (41%), and 131 were ROL2 (59%). At a median follow-up of 26.9 months (IQR 13.8–40.6), we registered 81 recurrences and 40 progressions. ROL was a significant predictor of tumor progression in both univariable (HR 3.53; CI 95% 1.56–7.99; p < 0.01) and multivariable (HR 2.88; CI 95% 1.24–6.66; p = 0.01) Cox regression analyses. At Kaplan-Meier estimates, ROL showed a correlation with both PFS (p = 0.0012) and RFS (p = 0.0167). Our results confirmed the strong predictive value of ROL for progression in a large prospective series. We encourage the application of ROL for reporting the extent of LP invasion, substaging T1 HG UC, and improving risk tables for urological decision-making. Full article

(This article belongs to the Special Issue Staging and Pathology of Bladder Cancer)

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