Precision Diagnostics in Kidney Cancer

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 791

Special Issue Editors


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Guest Editor
Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210036, China
Interests: bladder cancer; prostate cancer; kidney cancer; renal pelvis cancer; adrenal gland tumors
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210036, China
Interests: bladder cancer; urology
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210036, China
Interests: kidney cancer; bladder cancer; prostate cancer; benign prostatic hyperplasia; adrenal tumors

Special Issue Information

Dear Colleagues,

Kidney cancer remains a heterogeneous disease in presentation, biology, and therapeutic response. While cross-sectional imaging has long been the diagnostic technique of choice, rapid advances in liquid biopsy, radionuclide techniques, and artificial intelligence (AI) now offer opportunities to detect disease earlier, subtype tumors more accurately, and monitor response and minimal residual disease with higher accuracy. This Special Issue invites original research and authoritative reviews that advance diagnostic science across the entire kidney cancer field, from population-level screening concepts and early diagnosis to risk stratification, active surveillance, perioperative decision-making, and longitudinal post-treatment monitoring.

The diagnostic landscape of kidney cancer is undergoing precise characterization at baseline, and, over time, will become increasingly central to surgical planning, systemic therapy selection, and surveillance. Bringing together innovations in imaging, radionuclide diagnostics, liquid biopsy, and AI will accelerate bench-to-bedside translation and clarify which tools improve outcomes for patients.

We welcome translational, clinical, methodological, and implementation studies that demonstrate clinical utility or provide robust analytical/clinical validation, with an emphasis on reproducibility, external validation, and equity.

Topics of interest, include but are not limited to, the following:

  • Early detection and risk stratification;
  • Imaging science;
  • Nuclear medicine and molecular imaging;
  • Liquid biopsy and multi-omics;
  • AI and computational diagnostics;
  • Pathology and digital pathology;
  • Precision diagnosis informing precision therapy;
  • Implementation science and health systems.

Prof. Dr. Qiang Lv
Dr. Xiao Yang
Dr. Qiang Cao
Guest Editors

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Keywords

  • renal tumor
  • diagnostic and prognostic markers
  • non-invasive
  • artificial intelligence
  • precision diagnosis

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Published Papers (1 paper)

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Research

11 pages, 1526 KB  
Article
Assessment of Meet-URO and CANLPH Prognostic Models in Metastatic RCC: Insights from a Single-Institution Cohort Predominantly Treated with TKIs
by Ömer Faruk Kuzu, Nuri Karadurmuş, Nebi Batuhan Kanat, Dilruba İlayda Özel Bozdağ, Berkan Karadurmuş, Esmanur Kaplan Tüzün, Hüseyin Atacan, Nurlan Mammadzada, Emre Hafızoğlu, Gizem Yıldırım, Musa Barış Aykan, Selahattin Bedir and İsmail Ertürk
Diagnostics 2026, 16(3), 428; https://doi.org/10.3390/diagnostics16030428 - 1 Feb 2026
Viewed by 543
Abstract
Background/Objectives: Accurate prognostic assessment remains crucial in metastatic renal cell carcinoma (mRCC), especially as treatment options have expanded beyond vascular endothelial growth factor (VEGF)-targeted therapies to include immune checkpoint inhibitors (ICIs) and ICI–TKI combinations. The widely used IMDC classification shows important limitations [...] Read more.
Background/Objectives: Accurate prognostic assessment remains crucial in metastatic renal cell carcinoma (mRCC), especially as treatment options have expanded beyond vascular endothelial growth factor (VEGF)-targeted therapies to include immune checkpoint inhibitors (ICIs) and ICI–TKI combinations. The widely used IMDC classification shows important limitations in the modern therapeutic era, highlighting the need for complementary prognostic tools. In this context, the Meet-URO and CANLPH scores—incorporating clinical, inflammatory, and nutritional markers—have emerged as promising alternatives. To evaluate and compare the prognostic performance of the Meet-URO and CANLPH scoring systems in a real-world mRCC cohort predominantly treated with first-line tyrosine kinase inhibitor (TKI) monotherapy due to limited access to ICI-based combinations. Methods: This retrospective single-center study included 112 patients with mRCC. The Meet-URO score was calculated for all patients, while the CANLPH score was assessed in 56 patients with complete laboratory data. CAR, NLR, and PHR were computed using baseline pre-treatment measurements. Overall survival (OS) and progression-free survival (PFS), the latter defined exclusively for first-line therapy, were estimated using the Kaplan–Meier method. Correlations between inflammatory markers and survival outcomes were analyzed using Spearman’s rho. Results: Meet-URO demonstrated clear prognostic stratification across all five categories, with the most favorable outcomes in score group 2 and progressively poorer OS and PFS in higher-risk groups. CANLPH also showed meaningful survival discrimination, with the highest inflammatory group (score 3) exhibiting markedly reduced OS and PFS. CAR was the strongest individual predictor of survival, while NLR and PHR showed weaker associations. Conclusions: Both Meet-URO and CANLPH provide strong, complementary prognostic information in mRCC, even in a cohort largely treated with TKI monotherapy. Their integration into routine risk assessment may enhance clinical decision-making, particularly in resource-limited settings. Full article
(This article belongs to the Special Issue Precision Diagnostics in Kidney Cancer)
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