Evidence map›Paper›PMID 40868379›Full record

ReviewBioengineering (Basel, Switzerland)2025

Advances in Label-Free Detection of Non-Muscle Invasive Bladder Cancer: A Critical Review.

Gabriela Vera, Javier Cerda-Infante, Mario I Fernández, Miguel Sánchez-Encinas, Pablo A Rojas

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Gabriela VeraServicio de Urología, Complejo Asistencial Dr. Sotero del Rio, Santiago 8150215, Chile.ORCID 0009-0008-4681-5826
Javier Cerda-InfanteEnviron SPA, Santiago 7750000, Chile.
Mario I FernándezDepartamento de Urología, Clínica Alemana Universidad del Desarrollo, Santiago 7610315, Chile.ORCID 0000-0001-6424-4977
Miguel Sánchez-EncinasServicio de Urología, Hospital Universitario Rey Juan Carlos, 28933 Madrid, Spain.
Pablo A RojasServicio de Urología, Complejo Asistencial Dr. Sotero del Rio, Santiago 8150215, Chile.ORCID 0009-0009-1854-8334

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-muscle invasive bladder cancer (NMIBC) accounts for about 75% of new bladder cancer diagnoses. Early detection improves survival, yet routine white-light cystoscopy is invasive, costly, and can miss up to 45% of flat or small lesions. These shortcomings have prompted development of label-free diagnostic tools that read the intrinsic optical, electrical, or mechanical signatures of urinary biomarkers without added labels. This review examines recent engineering advances in such platforms for NMIBC detection, focusing on analytical performance, readiness for clinical translation, and remaining barriers to adoption. We compare each technology with conventional cytology using key metrics such as limit of detection, diagnostic accuracy, analysis time, cohort size, and stage of clinical development. Surface-enhanced Raman spectroscopy and interferometric flow cytometry offer femtomolar sensitivity and more than 98% accuracy within minutes, while compact electrochemical sensors targeting NMP22, Galectin-1, and microRNAs reach sub-picogram levels on disposable chips. Standardized sample handling, multicenter validation, and robust cost-effectiveness data are now essential for these tools to advance point-of-care NMIBC surveillance.

Indexed as

electrochemical biosensorinterferometric flow cytometrylabel-free biosensorsnon-muscle invasive bladder cancerRaman spectroscopySERSurinary biomarkers

Identifiers

PMID40868379
PMCPMC12383690

What OpenQuestion holds

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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 OpenQuestion graph.