Evidence map›Paper›PMID 42038134›Full record

ReviewGalen medical journal2024

Emerging Diagnostic Modalities in Oral Cancer Detection and Management.

Ashkan Badkoobeh, Shadi Zarakhsh, Mehrnaz Fayazi, Pouya Kavianpour, Zahra Bahman, Maryam Onsori, Mahsa Etemadi

Abstract readReview
In one paragraph

Review in Galen medical journal, 2024. 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

7 authors.

Ashkan BadkoobehDepartment of Oral and Maxillofacial Surgery, School of Dentistry, Qom University of Medical Sciences, Qom, Iran.
Shadi ZarakhshFaculty of Dentistry, Isfahan, Khorasgan Branch, Islamic Azad University, Isfahan, Iran.
Mehrnaz FayaziSchool of Dentistry, Islamic Azad University of Medical sciences, Tehran, Iran.
Pouya KavianpourDepartment of Endodontics, School of Dentistry, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Zahra BahmanFaculty of Dentistry, Belarusian State Medical University, Belarus, Minsk.
Maryam OnsoriDepartment of Operative Dentistry, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Mahsa EtemadiDepartment of Periodontology, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oral cancer remains a significant global health concern, yet it is often detected at an advanced stage. The limitations of traditional diagnostic techniques have prompted increased research efforts towards the development of more efficient and early detection methods. Recent advancements in oral cancer diagnosis include the use of salivary biomarkers, optical imaging, liquid biopsy, advanced imaging, and AI algorithms. These non-invasive and painless sampling methods have shown high sensitivity and specificity, particularly in the case of salivary biomarkers. Clinical trials and cooperation are necessary to demonstrate the effectiveness of these technologies and gain approval from relevant authorities and acceptance among clinicians. This review highlights the potential of these new modalities in transforming the approach to oral cancer diagnosis, leading to early detection, accurate diagnosis, and quality treatment for patients, ultimately reducing the global burden of this disease.

Indexed as

Artificial IntelligenceDiagnosticsEarly DetectionLiquid BiopsyMRI SpectroscopyOptical ImagingOral CancerPersonalized MedicinePET-CTSalivary Biomarkers

Identifiers

PMID42038134
PMCPMC11826402

What OpenQuestion holds

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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.