Evidence map›Paper›PMID 29572027›Full record

ArticleGynecologic oncology2018

A novel multiple biomarker panel for the early detection of high-grade serous ovarian carcinoma.

Chanhee Han, Stefania Bellone, Eric R Siegel, Gary Altwerger, Gulden Menderes, Elena Bonazzoli, Tomomi Egawa-Takata, Francesca Pettinella, Anna Bianchi, Francesco Riccio and 14 more

Abstract read
In one paragraph

Article in Gynecologic oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

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  19. Molecular Management of High-Grade Serous Ovarian Carcinoma.International journal of molecular sciences · 2022
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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

24 authors.

Chanhee HanDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Stefania BelloneDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Eric R SiegelDepartment of Biostatistics, University of Arkansas for Medical Science, Little Rock, AR 72205, USA.
Gary AltwergerDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Gulden MenderesDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Elena BonazzoliDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Tomomi Egawa-TakataDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Francesca PettinellaDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Anna BianchiDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Francesco RiccioDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Luca ZammataroDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Ghanshyam YadavDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Jarrod A MartoDepartment of Cancer Biology, Department of Oncologic Pathology, Blais Proteomic Center, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Marie-France PenetDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Douglas A LevineDivision of Gynecologic Oncology, Laura and Isaac Perlmutter Cancer Center, NYU Langone Health, New York, NY 10016, USA.
Ronny DrapkinDepartment of Obstetrics and Gynecology, Penn Ovarian Cancer Research Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
Abhijit PatelDepartment of Therapeutic Radiology, Yale School of Medicine, New Haven, CT 06510, USA.
Babak LitkouhiDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Elena RatnerDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Dan-Arin SilasiDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Gloria S HuangDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Masoud AzodiDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Peter E SchwartzDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA.
Alessandro D SantinDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale University School of Medicine, New Haven, CT 06520, USA. Electronic address: alessandro.santin@yale.edu.

Funding

Integrated genomic analysis of racial disparities in endometrial cancerU01CA176067 · NCI · YALE UNIVERSITY · PI SANTIN, ALESSANDRO D · 2014 to 2018
$1.7M
NCI NIH HHS U01 CA176067
6 · The paper itself

Abstract

introductionSince the majority of patients are diagnosed at an advanced stage, ovarian cancer remains the most lethal gynecologic malignancy. There is no single biomarker with the sensitivity and specificity required for effective cancer screening; therefore, we investigated a panel of novel biomarkers for the early detection of high-grade serous ovarian carcinoma.

methodsTwelve serum biomarkers with high differential gene expression and validated antibodies were selected: IL-1Ra, IL-6, Dkk-1, uPA, E-CAD, ErbB2, SLPI, HE4, CA125, LCN2, MSLN, and OPN. They were tested using Simple Plex™, a multi-analyte immunoassay platform, in samples collected from 172 patients who were either healthy, had benign gynecologic pathologies, or had high-grade serous ovarian adenocarcinomas. The receiver operating characteristic (ROC) curve, ROC area under the curve (AUC), and standard error (SE) of the AUC were obtained. Univariate ROC analyses and multivariate ROC analyses with the combination of multiple biomarkers were performed.

resultsThe 4-marker panel consisting of CA125, HE4, E-CAD, and IL-6 had the highest ROC AUC. When evaluated for the ability to distinguish early stage ovarian cancer from a non-cancer control, not only did this 4-marker panel (AUC=0.961) performed better than CA 125 alone (AUC=0.851; P=0.0150) and HE4 alone (AUC=0.870; P=0.0220), but also performed significantly better than the 2- marker combination of CA125+HE4 (AUC=0.922; P=0.0278). The 4-marker panel had the highest average sensitivity under the region of its ROC curve corresponding to specificity ranging from 100% down to ~95%.

conclusionThe four-marker panel, CA125, HE4, E-CAD, and IL-6, shows potential in detecting serous ovarian cancer at earlier stages. Additional validation studies using the biomarker combination in ovarian cancer patients are warranted.

Indexed as

Biomarkers, TumorCase-Control StudiesCystadenocarcinoma, SerousFemaleGene ExpressionHumansMesothelinMiddle AgedNeoplasm GradingOvarian NeoplasmsROC CurveBiomarkers, TumorMesothelinMSLN protein, humanBiomarkersEarly detectionOvarian cancerSerous ovarian cancer

Identifiers

PMID29572027
PMCPMC5986604

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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.