Evidence map›Paper›PMID 40804879›Full record

ReviewDiagnostics (Basel, Switzerland)2025

Unlocking the Potential of Liquid Biopsy: A Paradigm Shift in Endometrial Cancer Care.

Nannan Gui, Chalong Cheewakriangkrai, Parunya Chaiyawat, Sasimol Udomruk

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Nannan GuiDepartment of Obstetrics and Gynecology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.
Chalong CheewakriangkraiDepartment of Obstetrics and Gynecology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.ORCID 0000-0002-8846-2618
Parunya ChaiyawatCenter of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.ORCID 0000-0003-0047-5578
Sasimol UdomrukCenter of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endometrial cancer is one of the most prevalent gynecologic malignancies in developed countries, with its incidence steadily increasing each year. Early diagnosis is crucial for a favorable prognosis; however, certain patients experience recurrence and distant metastasis after surgery, similar to advanced cancer patients, with limited treatment options. Therefore, effective strategies for early screening, diagnosis, predicting local recurrence, and guiding rapid treatment interventions are essential for improving survival rates and prognosis. Liquid biopsy, a method known for being non-invasive, safe, and effective, has attracted widespread attention for cancer diagnosis and treatment. Although its clinical application in endometrial cancer is less established than in other cancers, research on biomarkers using liquid biopsy in endometrial cancer patients is currently in progress. This review examines the latest advancements in non-invasive biomarkers identified through liquid biopsy and provides a comprehensive overview of their clinical applications in endometrial cancer. Additionally, it discusses the challenges and future prospects of liquid biopsy, offering valuable insights into the diagnosis and personalized treatment of endometrial cancer.

Indexed as

biomarkersearly diagnosisendometrial cancerliquid biopsynon-invasivepersonalized medicine

Identifiers

PMID40804879
PMCPMC12346894

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.