Evidence map›Paper›PMID 41425536›Full record

ReviewBJUI compass2025

Urinary biomarkers in multicentric studies: Shaping the future of bladder cancer diagnosis and follow-up.

Alexandrine Martel, Lucas Raue, Patrice Hodonou Avogbe, Jennifer Raisch, Claudio Jeldres, Thorsten Ecke, Emmanuel Vian, Md Ismail Hosen, Anja Rabien, Florence Le Calvez-Kelm and 1 more

Abstract readReview
In one paragraph

Review in BJUI compass, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Alexandrine MartelDepartment of Immunology and Cell Biology, Faculty of Medicine and Health Sciences Université de Sherbrooke Sherbrooke Canada.ORCID https://orcid.org/0009-0005-0126-8257
Lucas RaueUrology Universitätsmedizin Berlin Charité Berlin Germany.ORCID https://orcid.org/0009-0003-2974-4505
Patrice Hodonou AvogbeInternational Agency for Research on Cancer (IARC) Lyon France.ORCID https://orcid.org/0000-0003-4436-3981
Jennifer RaischDepartment of Immunology and Cell Biology, Faculty of Medicine and Health Sciences Université de Sherbrooke Sherbrooke Canada.ORCID https://orcid.org/0000-0003-4393-5933
Claudio JeldresDivision of Urology, Faculty of Medicine and Health Sciences Université de Sherbrooke Sherbrooke Canada.
Thorsten EckeUrology Universitätsmedizin Berlin Charité Berlin Germany.ORCID https://orcid.org/0000-0002-0787-2763
Emmanuel VianUrology Department Protestant Clinic of Lyon Lyon France.
Md Ismail HosenDepartment of Biochemistry and Molecular Biology University of Dhaka Dhaka Bangladesh.ORCID https://orcid.org/0000-0003-0862-7206
Anja RabienUrology Universitätsmedizin Berlin Charité Berlin Germany.ORCID https://orcid.org/0000-0003-0124-4878
Florence Le Calvez-KelmInternational Agency for Research on Cancer (IARC) Lyon France.ORCID https://orcid.org/0000-0003-0063-5068
Francois-Michel BoisvertDepartment of Immunology and Cell Biology, Faculty of Medicine and Health Sciences Université de Sherbrooke Sherbrooke Canada.ORCID https://orcid.org/0000-0001-8882-8619

Funding

World Health Organization 001
6 · The paper itself

Abstract

Background and Objective: Bladder cancer (BC), a prevalent malignancy, poses significant diagnostic and surveillance challenges due to its high recurrence rates and reliance on cystoscopy, an invasive procedure for diagnosis and monitoring. While urine-based genomic and proteomic biomarkers offer promising non-invasive alternatives, their clinical implementation remains limited. This review synthesizes evidence from multicentric studies on urinary biomarkers for BC and evaluates their potential in reducing unnecessary invasive cystoscopies. Methods: A comprehensive review of literature was conducted searching for multicentric studies on urine-based genomic and proteomic biomarkers for BC detection and/or surveillance. MEDLINE/Pubmed, Embase and Scopus databases and BJUI, UroToday and European Urology Oncology registries were searched using National Library of Medicine Medical Subject Headings (MeSH) terms. Emphasis was placed on the comparative performance of diagnostic platforms across different research and clinical settings. Key Findings and Limitations: The literature search yielded 51 reports that were included for analysis. Multicentre studies enhance the generalizability of findings by addressing inter-laboratory variability and population diversity. This review underscores the importance of standardization, comparative performance analyses that these studies provide, and the potential for cost-effective non-invasive diagnostic tools. However, despite FDA approvals, no biomarker has replaced cystoscopy in clinical settings due to an inconsistent and insufficient combination of sensitivity, specificity and cost-effectiveness parameters. The performance of AssureMDX and Enhanced CxBladder tests showed the most promise, but further large-scale, standardized validation is still necessary. Conclusions and Clinical Implications: Urine-based biomarkers have the potential to improve early BC detection and surveillance while reducing reliance on invasive procedures and costs related to the disease. Future efforts should prioritize cost-effective, large-scale multicentric studies to facilitate the adoption of these biomarkers into routine practice.

Indexed as

bladder cancercystoscopy alternativescytologygenomichaematuria detectionliquid biopsiesmulticentre studiesnon‐invasive diagnosisproteomicurinary biomarkersurothelial carcinoma

Identifiers

PMID41425536
PMCPMC12715348

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.