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Advances in the Diagnosis and Treatment of Genitourinary Cancers (2nd...
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Advances in the Diagnosis and Treatment of Genitourinary Cancers (2nd Edition)

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 286

Special Issue Editors

Prof. Dr. Piotr Radziszewski

E-Mail Website
Guest Editor
Clinic of General, Oncological and Functional Urology, Medical University of Warsaw, Lindleya 4, 02-005 Warsaw, Poland
Interests: genitourinary cancer; urology oncology; point-of-care diagnostics; personalized treatment; immunotherapy
Special Issues, Collections and Topics in MDPI journals
Dr. Łukasz Zapała

E-Mail Website
Guest Editor
Clinic of General, Oncological and Functional Urology, Medical University of Warsaw, Lindleya 4, 02-005 Warsaw, Poland
Interests: genitourinary cancer; point-of-care diagnostics; personalized treatment; immunotherapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the second edition of "Advances in the Diagnosis and Treatment of Genitourinary Cancers", https://www.mdpi.com/journal/cancers/special_issues/303JT7BB09

Genitourinary cancers are diseases increasingly occurring in populations, the diagnosis and treatment of which are currently undergoing fast and sometimes dramatic changes, due to the current landscape of the suboptimal management of these diseases. A characteristic feature of urological cancers’ treatment is the significant heterogeneity of patients (including different stages of local advancement, different locations of metastases, the heterogeneity of pathological findings, etc.). Therefore, predicting the response to modern treatment remains the unmet need of modern urologic oncology. New diagnostic methods, including, but not limited to, point-of-care diagnostics, represent a challenge to current guidelines and require a verification process. Further development is awaited as far as sufficient neoadjuvant and adjuvant treatments in perioperative settings are concerned. Recent advancements in systematic treatments, i.e., immunotherapy, shed additional light on new treatment paradigms to be implemented in various clinical scenarios, including localized disease. Finally, the recent progress in the minimally invasive surgical techniques leads to the revision of concepts on the treatment of many urological tumors.

This Special Issue aims to cover novel approaches in genitourinary cancers. We opt for original papers and reviews relating to advances in the treatment of male genitourinary cancers.

Prof. Dr. Piotr Radziszewski
Dr. Łukasz Zapała
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • genitourinary cancer
  • point-of-care diagnostics
  • personalized treatment
  • immunotherapy

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Published Papers (1 paper)

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Research

16 pages, 1395 KiB  
Article
Prediction of Glomerular Filtration Rate Following Partial Nephrectomy for Localized Renal Cell Carcinoma with Different Machine Learning Techniques
by Aleksander Ślusarczyk, Sumit Sharma, Karolina Garbas, Hanna Piekarczyk, Piotr Zapała, Jinhao Shi, Piotr Radziszewski, Le Qu and Łukasz Zapała
Cancers 2025, 17(10), 1647; https://doi.org/10.3390/cancers17101647 - 13 May 2025
Viewed by 200
Abstract
Background and Objectives: Partial nephrectomy (PN) is the preferred option for treating localized cT1 renal cell carcinoma (RCC), as it preserves renal function in most patients and offers non-inferior oncological outcomes compared to radical nephrectomy. In this study, we aimed to construct [...] Read more.
Background and Objectives: Partial nephrectomy (PN) is the preferred option for treating localized cT1 renal cell carcinoma (RCC), as it preserves renal function in most patients and offers non-inferior oncological outcomes compared to radical nephrectomy. In this study, we aimed to construct a predictive model for estimating the glomerular filtration rate (GFR) at one year after PN in patients with RCC, using various machine learning techniques. Methods: Retrospective data were collected from two academic centers, covering surgeries performed between 2010 and 2022. GFR was estimated using the Chronic Kidney Disease Epidemiology Collaboration 2021 (CKD-EPI) formula. Univariable linear regression (LR) was used to identify significant clinical predictors of 1-year postoperative GFR, followed by multivariable LR. The dataset was split into training and testing cohorts in a 70:30 ratio. Internal validation was performed on the test cohort, and various machine learning methods, including artificial neural networks (ANNs), support vector machines (SVMs), random forests (RFs), and XGBoost, were compared. Results: Among 615 patients treated with PN, 415 had complete follow-up GFR data and were included in the analysis. Only 8.7% of patients experienced significant GFR loss (>30% decrease) at 1 year. Multivariable LR identified baseline GFR (Estimate: 0.76, p < 0.001), tumor diameter on imaging (Estimate: −1.65, p = 0.005), and Charlson Comorbidity Index (Estimate: −1.95, p < 0.001) as independent predictors of 1-year GFR (R2 = 0.67). A 10-fold cross-validation of the multivariable model yielded an R2 of 0.68. In the testing cohort, ANN, SVM, RF, and XGBoost did not outperform the LR model, with R2 values of 0.68, 0.66, 0.64, and 0.55, respectively. Conclusions: Preoperative factors, including baseline GFR, tumor size on imaging, and Charlson Comorbidity Index, are effective predictors of GFR at 1 year following PN. Our study demonstrates that a conventional LR model based on preoperative variables provides acceptable accuracy for predicting GFR after PN and is not inferior to more complex machine learning techniques. Full article
(This article belongs to the Special Issue Advances in the Diagnosis and Treatment of Genitourinary Cancers (2nd Edition))
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