Evidence map›Paper›PMID 35646702›Full record

SynthesisFrontiers in oncology2022

Association Between Benign Ovarian Tumors and Ovarian Cancer Risk: A Meta-Analysis of Ten Epidemiological Studies.

Jiao Guo, Haoshen Feng, Xi Gu

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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

3 authors at 1 institution in 1 country.

Jiao GuoDepartment of Oncology, Shengjing Hospital of China Medical University, Shenyang, China.
Haoshen FengDepartment of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China.
Xi GuDepartment of Oncology, Shengjing Hospital of China Medical University, Shenyang, China.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Epidemiological evidence on the relationship between benign ovarian tumors and ovarian cancer risk has been controversial; therefore, this systematic review and meta-analysis evaluated this association. Methods: The PubMed and Web of Knowledge databases were searched for eligible studies published up to April 30, 2020. The study-specific risk estimates were pooled using a random-effects model. Results: Ten articles (two cohorts, seven case-control studies, and one pooled analysis of eight case-control studies) with 10331 ovarian cancer patients were included. Benign ovarian tumors were associated with an increased risk of ovarian cancer (pooled relative risk [RR]=1.39, 95% confidence interval [CI]: 1.01-1.90), with high heterogeneity among studies. The pooled RR was 2.02 (95%CI: 1.32-3.11) for two cohort studies, which was higher than the pooled result of eight case-control studies (pooled RR: 1.15; 95%CI: 0.92-1.44). When stratifying by histological type, the pooled RRs were 1.53 (95% CI: 0.37-6.29) and 3.62 (95%CI: 0.81-16.20) for serous and mucinous tumors, respectively. The pooled RRs were 1.61 (95%CI: 0.65-3.95) and 1.54 (95%CI: 1.29-1.84) for the associations of ovarian cyst with invasive and borderline cancers, respectively. Conclusions: Benign ovarian tumors were associated with an increased risk of ovarian cancer. Due to the high heterogeneity among the studies and the risks of bias, more studies are warranted to confirm these findings.

Indexed as

benign ovarian tumorsepidemiological studyincidence riskmeta-analysisovarian cancer

Identifiers

PMID35646702
PMCPMC9133501
OpenAlexW4280563270

What OpenQuestion holds

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LicenceCC BY
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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.