Evidence map›Paper›PMID 29087294›Full record

ArticleeLife2017

Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer.

Kevin M Elias, Wojciech Fendler, Konrad Stawiski, Stephen J Fiascone, Allison F Vitonis, Ross S Berkowitz, Gyorgy Frendl, Panagiotis Konstantinopoulos, Christopher P Crum, Magdalena Kedzierska and 2 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in eLife, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed, 3 pooled it
4.3field-weighted citation impact, top 4% 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

87 citing papers in PubMed, 3 syntheses or guidelines pooled it, 144 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Disease markers · 2019
    Pooled it
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Effects of Clinical Covariates on Serum miRNA Expression among Women without Ovarian Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Serum Lipidome Profiling Reveals a Distinct Signature of Ovarian Cancer in Korean Women.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024
    Article
  18. Article
  19. Review
  20. Article

27 more citing papers are in PubMed but not listed here.

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

12 authors at 2 institutions in 2 countries.

Kevin M EliasDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Boston, United States.ORCID http://orcid.org/0000-0003-1502-5553
Wojciech FendlerHarvard Medical School, Boston, United States.ORCID http://orcid.org/0000-0002-5083-9168
Konrad StawiskiDepartment of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland.ORCID http://orcid.org/0000-0002-6550-3384
Stephen J FiasconeDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Boston, United States.
Allison F VitonisHarvard Medical School, Boston, United States.
Ross S BerkowitzDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Boston, United States.
Gyorgy FrendlHarvard Medical School, Boston, United States.
Panagiotis KonstantinopoulosHarvard Medical School, Boston, United States.
Christopher P CrumHarvard Medical School, Boston, United States.
Magdalena KedzierskaDepartment of Clinical Oncology, Medical University of Lodz, Lodz, Poland.
Daniel W CramerHarvard Medical School, Boston, United States.
Dipanjan ChowdhuryHarvard Medical School, Boston, United States.ORCID http://orcid.org/0000-0001-5645-3752
Boston University · USMedical University of Lodz · PL

Funding

REPRODUCTIVE SCIENTIST TRAINING PROGRAMK12HD000849 · NICHD · WASHINGTON UNIVERSITY · PI Danny J Schust · 1988 to 2026
$33.2M
Novel Serum, Plasma, and Urine Biomarkers of Ovarian CanP50CA105009 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI CRAMER, DANIEL WILLIAM · 2004 to 2010
$13.3M
Molecular mechanism and relevance of microRNAs in DSB repair pathway choiceR01CA142698 · NCI · DANA-FARBER CANCER INST · PI CHOWDHURY, DIPANJAN · 2010 to 2019
$3.8M
NCI NIH HHS P50 CA105009NCI NIH HHS R01 CA142698NICHD NIH HHS K12 HD000849
6 · The paper itself

Abstract

Recent studies posit a role for non-coding RNAs in epithelial ovarian cancer (EOC). Combining small RNA sequencing from 179 human serum samples with a neural network analysis produced a miRNA algorithm for diagnosis of EOC (AUC 0.90; 95% CI: 0.81-0.99). The model significantly outperformed CA125 and functioned well regardless of patient age, histology, or stage. Among 454 patients with various diagnoses, the miRNA neural network had 100% specificity for ovarian cancer. After using 325 samples to adapt the neural network to qPCR measurements, the model was validated using 51 independent clinical samples, with a positive predictive value of 91.3% (95% CI: 73.3-97.6%) and negative predictive value of 78.6% (95% CI: 64.2-88.2%). Finally, biologic relevance was tested using in situ hybridization on 30 pre-metastatic lesions, showing intratumoral concentration of relevant miRNAs. These data suggest circulating miRNAs have potential to develop a non-invasive diagnostic test for ovarian cancer.

Indexed as

AgedBiomarkers, TumorFemaleHumansMicroRNAsMiddle AgedNeural Networks, ComputerOvarian NeoplasmsPredictive Value of TestsReal-Time Polymerase Chain ReactionSensitivity and SpecificitySerumBiomarkers, TumorMicroRNAscancer biologyhumanmachine learningmiRNAneural networknext generation sequencingovarian cancerserum

Identifiers

PMID29087294
PMCPMC5679755
OpenAlexW2765410042

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.