Evidence map›Paper›PMID 27253331›Full record

SynthesisPloS one2016

Circulating Cell Free DNA as the Diagnostic Marker for Ovarian Cancer: A Systematic Review and Meta-Analysis.

Quan Zhou, Wei Li, Bingjie Leng, Wenfei Zheng, Ze He, Manzhen Zuo, Aihua Chen

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 5 pooled it
4.2field-weighted citation impact, top 6% of its field
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

41 citing papers in PubMed, 5 syntheses or guidelines pooled it, 80 citations in OpenAlex.

  1. Pooled it
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  6. Trial
  7. Article
  8. Review
  9. Breast cancer: pathogenesis and treatments.Signal transduction and targeted therapy · 2025
    Review
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  12. Review
  13. Article
  14. Article
  15. Article
  16. Molecular Management of High-Grade Serous Ovarian Carcinoma.International journal of molecular sciences · 2022
    Review
  17. Review
  18. Article
  19. ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors.International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2021
    Review
  20. 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

7 authors at 1 institution in 1 country.

Quan ZhouDepartment of Gynecology and Obstetrics, the People's Hospital of Three Gorges University/the First People's Hospital of Yichang, Yichang 443000, China.
Wei LiDepartment of Gynecology and Obstetrics, the People's Hospital of Three Gorges University/the First People's Hospital of Yichang, Yichang 443000, China.
Bingjie LengDepartment of Gynecology and Obstetrics, the People's Hospital of Three Gorges University/the First People's Hospital of Yichang, Yichang 443000, China.
Wenfei ZhengDepartment of Gynecology and Obstetrics, the People's Hospital of Three Gorges University/the First People's Hospital of Yichang, Yichang 443000, China.
Ze HeDepartment of Gynecology and Obstetrics, the People's Hospital of Three Gorges University/the First People's Hospital of Yichang, Yichang 443000, China.
Manzhen ZuoDepartment of Gynecology and Obstetrics, the People's Hospital of Three Gorges University/the First People's Hospital of Yichang, Yichang 443000, China.
Aihua ChenDepartment of Gynecology and Obstetrics, the People's Hospital of Three Gorges University/the First People's Hospital of Yichang, Yichang 443000, China.
Yichang Central People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuantitative analyses of circulating cell-free DNA (cfDNA) are potential methods for the detection of ovarian cancer. Many studies have evaluated these approaches, but the results were too inconsistent to be conclusive. This study is the first to systematically evaluate the accuracy of circulating cfDNA for the diagnosis of ovarian cancer by conducting meta-analysis.

methodsWe searched PubMed, Embase, Cochrane Library and the Chinese National Knowledge Infrastructure (CNKI) databases systematically for relevant literatures up to December 10, 2015. All analyses were conducted using Meta-DiSc1.4 and Stata 12.0 software. Sensitivity, specificity and other measures of accuracy of circulating cfDNA for the diagnosis of ovarian cancer were pooled. Meta-regression was performed to identify the sources of heterogeneity.

resultsThis meta-analysis included a total of 9 studies, including 462 ovarian cancer patients and 407 controls. The summary estimates for quantitative analysis of circulating cfDNA in ovarian cancer screen were as follows: sensitivity, 0.70 (95% confidence interval (CI), 0.65-0.74); specificity, 0.90 (95% CI, 0.87-0.93); positive likelihood ratio, 6.60 (95% CI, 3.90-11.17); negative likelihood ratio, 0.34 (95% CI, 0.25-0.47); diagnostic odds ratio, 26.05 (95% CI, 14.67-46.26); and area under the curve, 0.89 (95% CI, 0.83-0.95), respectively. There was no statistical significance for the evaluation of publication bias.

conclusionsCurrent evidence suggests that quantitative analysis of cfDNA has unsatisfactory sensitivity but acceptable specificity for the diagnosis of ovarian cancer. Further large-scale prospective studies are required to validate the potential applicability of using circulating cfDNA alone or in combination with conventional markers as diagnostic biomarker for ovarian cancer and explore potential factors that may influence the accuracy of ovarian cancer diagnosis.

Indexed as

Early Detection of CancerBiomarkers, TumorDNA, NeoplasmFemaleHumansOvarian NeoplasmsBiomarkers, TumorDNA, Neoplasm

Identifiers

PMID27253331
PMCPMC4890757
OpenAlexW2418515714

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.