Evidence map›Paper›PMID 41036092›Full record

ReviewBreast cancer (Dove Medical Press)2025

Clinical Management of Circulating Tumor DNA in Breast Cancer: Detection, Prediction, and Monitoring.

Yongqu Lu, Lehao Ren, Meng Yang, Jun Liu

Abstract readReview
In one paragraph

Review in Breast cancer (Dove Medical Press), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. 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.

Yongqu Lu *Department of Breast and Thyroid Surgery, China-Japan Friendship Hospital, Beijing, 100029, People's Republic of China.
Lehao Ren *Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Meng YangDepartment of Breast and Thyroid Surgery, China-Japan Friendship Hospital, Beijing, 100029, People's Republic of China.
Jun LiuDepartment of Breast and Thyroid Surgery, China-Japan Friendship Hospital, Beijing, 100029, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite substantial progress in the diagnosis and treatment of breast cancer, current therapeutic regimens exhibit limitations, necessitating the identification of more robust biomarkers to optimize personalized strategies. Circulating tumor DNA (ctDNA), as a non-invasive liquid biopsy modality, overcomes the inherent constraints of biopsies in capturing tumor heterogeneity. Accumulating evidence from prospective cohort studies demonstrates the clinical utility of ctDNA in risk stratification, guidance of therapeutic decision-making, recurrence surveillance and other clinical applications. Furthermore, ctDNA profiling enhances real-time pharmacodynamic monitoring and accelerates drug development by identifying molecular responders. The methodical requirements and challenges inherent in implementing liquid biopsy assessments in the clinic are examined. These encompass critical pre-analytical variables, the need for highly sensitive and specific analytical techniques, standardization of assays and bioinformatics pipelines across laboratories and the complexities of interpreting results. This review synthesizes current evidence supporting ctDNA integration into breast cancer management frameworks and systematically addresses its methodological challenges and clinical limitations.

Indexed as

breast cancercirculating tumor DNAminimal residual diseaseneoadjuvant therapy

Identifiers

PMID41036092
PMCPMC12479222

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.