Evidence map›Paper›PMID 40277570›Full record

ReviewBiosensors2025

Innovative Methodologies for the Early Detection of Breast Cancer: A Review Categorized by Target Biological Samples.

Antonella Grasso, Vittorio Altomare, Giulia Fiorini, Alessandro Zompanti, Giorgio Pennazza, Marco Santonico

Abstract readReview
In one paragraph

Review in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
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

6 authors.

Antonella GrassoBreast Unit, Policlinico Campus Bio-Medico di Roma, 00128 Rome, Italy.ORCID 0000-0003-3328-3644
Vittorio AltomareBreast Unit, Policlinico Campus Bio-Medico di Roma, 00128 Rome, Italy.
Giulia FioriniUnit of Electronics for Sensor Systems, Department of Science and Technology for Sustainable Development and One-Health, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
Alessandro ZompantiUnit of Electronics for Sensor Systems, Department of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.ORCID 0000-0001-5986-4426
Giorgio PennazzaUnit of Electronics for Sensor Systems, Department of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.ORCID 0000-0003-4843-9445
Marco SantonicoUnit of Electronics for Sensor Systems, Department of Science and Technology for Sustainable Development and One-Health, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Innovative biosensor technologies are revolutionizing cancer detection by offering non-invasive, sensitive, and rapid diagnostic tools, addressing the limitations of conventional screening. Non-invasive samples like breath, saliva, urine, and sweat, analyzed using advanced technologies like electronic nose systems and AI, show promise for early detection and frequent monitoring, though validation is needed. AI integration enhances data analysis and personalization. While blood-based methods remain the gold standard, combining them with less invasive sample types like saliva or sweat, and using sensitive techniques, is a promising direction. Conventional methods (mammography, MRI, etc.) offer proven efficacy, but are costly and invasive. Innovative methods using biosensors offer reduced infrastructure needs, lower costs, and patient-friendly sampling. However, challenges remain in validation, standardization, and low biomarker concentrations. Integrating both methodologies could create a comprehensive framework, combining reliability with accessibility. Future research should focus on robust biosensor development, standardization, expanding application to other cancers, exploring less-studied samples like sweat, and improving affordability for wider adoption, especially in resource-limited settings. The future lies in integrating diverse approaches for more sensitive, specific, and patient-friendly screening, improving early detection and outcomes.

Indexed as

Biosensing TechniquesBreast NeoplasmsEarly Detection of CancerFemaleHumansSalivaSweatbiosensor technologiesearly detectionnon-invasive cancer detection

Identifiers

PMID40277570
PMCPMC12026102

What OpenQuestion 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 OpenQuestion graph.