Evidence map›Paper›PMID 29995790›Full record

SynthesisMedicine2018

Predictive value of circulating cell-free DNA in the survival of breast cancer patients: A systemic review and meta-analysis.

Jing Yang, Li Cheng, Jing Zhang, Linyan Chen, Denian Wang, Xinli Guo, Xuelei Ma

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. The Combined Assessment of CTC andInternational journal of molecular sciences · 2025
    Article
  2. Circulating tumor cellsTranslational breast cancer research : a journal focusing on translational research in breast cancer · 2024
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. 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

7 authors.

Jing YangState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center for Biotherapy, Chengdu West China School of Stomatology Sichuan University, Chengdu, China.
Li Cheng
Jing Zhang
Linyan Chen
Denian Wang
Xinli Guo
Xuelei Ma

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeCirculating cell-free DNA (cfDNA) has been reported to predict outcomes in patients with various types of cancer. However, its prognostic value in patients with breast cancer is not well established still now. In this meta-analysis, we evaluated the prognostic role of cfDNA in breast cancer patients.

methodsWe performed systematic searches in electronic databases to identify studies that evaluated the prognostic value of cfDNA in breast cancer patients. The end points were progression-free survival (PFS) and overall survival (OS). The hazard ratios (HRs) and their 95% confidence intervals (95% CIs) were extracted to assess the prognostic significance of cfDNA. Subgroup analyses were also conducted.

resultsA total of 11 publications involving 1467 patients were included in this meta-analysis. cfDNA was shown to be significantly associated with PFS (HR 2.02, 95% CI 1.51-2.72, P < .001, I = 82%) and OS (HR 1.75, 95% CI 1.01-3.05, P < .001, I = 92%). The results of subgroup analyses also revealed that cfDNA was a good predictor of prognosis in breast cancer patients.

conclusionOur meta-analysis indicated that cfDNA was associated with poor PFS and OS, thus it may help to predict outcomes of patients with breast cancer. However, further studies are needed to confirm our results.

Indexed as

Biomarkers, TumorBreast NeoplasmsCell-Free Nucleic AcidsFemaleHumansPredictive Value of TestsPrognosisSurvival RateBiomarkers, TumorCell-Free Nucleic Acids

Identifiers

PMID29995790
PMCPMC6076113

What OpenQuestion holds

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Registered trials

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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.