SynthesisDisease markers2019
Synthesis in Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- The Accuracy of Single MicroRNAs in Peripheral Blood to Diagnose Ovarian Cancer: An Updated Meta-Analysis.Disease markers · 2020Pooled it
- The Evolving Landscape of Ovarian Cancer: Innovations in Biotechnology and Artificial Intelligence- Based Screening and Treatment.Current treatment options in oncology · 2025Review
- Ribosomal rodeo: wrangling translational machinery in gynecologic tumors.Cancer metastasis reviews · 2024Review
- Diagnostic and therapeutic challenges of a rare large ovarian strumal carcinoid in pregnancy, about a case report.International journal of surgery case reports · 2024Article
- Current strategies for early epithelial ovarian cancer detection using miRNA as a potential tool.Frontiers in molecular biosciences · 2024Review
- Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment.Cancers · 2023Review
- Advances on Prevention and Screening of Gynecologic Tumors: Are We Stepping Forward?Healthcare (Basel, Switzerland) · 2022Article
- KAZN as a diagnostic marker in ovarian cancer: a comprehensive analysis based on microarray, mRNA-sequencing, and methylation data.BMC cancer · 2022Article
- Predict ovarian cancer by pairing serum miRNAs: Construct of single sample classifiers.Frontiers in medicine · 2022Article
- Early diagonosis of ovarian cancer: serum HE4, CA125 and ROMA model.American journal of translational research · 2021Article
- MiR-429 Involves in the Pathogenesis of Colorectal Cancer via Directly Targeting LATS2.Oxidative medicine and cellular longevity · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current screening tests for the diagnosis of ovarian cancer (OC) face enduring challenges. However, microRNAs (miRNAs) are stable in the circulation and may be promising molecular biomarkers for OC prediction. Circulating miRNA expression profiles in OC were analyzed using sequencing data from the Gene Expression Omnibus database. Differentially expressed miRNAs were generated from GSE94533, of which some were selected as candidate miRNAs based on an electronic search of the literature and comprehensive evaluation. A meta-analysis was preformed to integrate an evaluation index for these miRNAs in diagnosing OC patients. An independent validation set (GSE106817) was also conducted to further confirm the roles of these miRNAs. We identified four
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.