Evidence map›Paper›PMID 29696206›Full record

ArticleContemporary clinical trials communications2017

Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project.

Julie L Hentze, Claus Høgdall, Susanne K Kjær, Jan Blaakær, Estrid Høgdall

Open access · goldAbstract read
In one paragraph

Article in Contemporary clinical trials communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 15 citations in OpenAlex.

  1. Potential Targeted Therapies in Ovarian Cancer.Pharmaceuticals (Basel, Switzerland) · 2022
    Article
  2. Article
  3. Article
  4. Article
  5. Serum Biomarker Based Algorithms in Diagnosis of Ovarian Cancer: A Review.Indian journal of clinical biochemistry : IJCB · 2018
    Review
  6. 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

5 authors at 3 institutions in 1 country.

Julie L HentzeDepartment of Pathology, Herlev Hospital, Herlev, Copenhagen University Hospital, Denmark.
Claus HøgdallDepartment of Gynecology, The Juliane Marie Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Susanne K KjærDepartment of Gynecology, The Juliane Marie Centre, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Jan BlaakærDepartment of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark.
Estrid HøgdallDepartment of Pathology, Herlev Hospital, Herlev, Copenhagen University Hospital, Denmark.
Copenhagen University Hospital · DKHerlev Hospital · DKUniversity of Southern Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer is a silent killer and, due to late diagnosis, the primary cause of death amongst gynecological cancers, killing approximately 376 women annually in Denmark. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, but also treatment, by predicting which patients will benefit from specific treatment strategies. The Mermaid III project is consisting of 3 parts including "Early detection, screening and long-term survival," "Biomarkers and/or prognostic markers" and "The infection theory." The present paper gives an overview of the part regarding biomarkers and/or prognostic markers, with a focus on rationale and design. The study described has 3 major branches: microRNAs, epigenetics and Next Generation Sequencing. Tissue and blood from ovarian cancer patients, already enrolled in the prospective ongoing pelvic mass cohort, will be examined. Relevant microRNAs and DNA methylation patterns will be investigated using array technology. Patient exomes will be fully sequenced, and identified genetic variations will be validated with Next Generation Sequencing. In all cases, data will be correlated with clinical information on the patient, in order to identify possible biomarkers. A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.

Indexed as

CA125, Cancer Antigen 125CPH-I, Copenhagen IndexDGCD, Danish Gynecologic Cancer DatabaseDiagnostic/prognostic biomarkersEpigeneticsFFPE, Formalin fixed and paraffin embeddedFIGO, International Federation of Gynecology and ObstetricsHE4, Human Epididymis Protein 4MALOVA, MALignant OVArian cancer studyMicroRNAmiRNAs, MicroRNAsNext Generation SequencingNGS, Next Generation SequencingOC, Ovarian cancerO.C.T., Optimal cutting temperatureOS, Overall survivalOvarian cancerPARP, poly(adenosine diphosphate [ADP]-ribose) polymerasePFS, Progression free survivalRMI, Risk of Malignancy IndexROCA, Risk of Ovarian Cancer AlgorithmROMA, Risk of Ovarian Malignancy AlgorithmUKCTOCS, UK Collaborative Trial of OC Screening

Identifiers

PMID29696206
PMCPMC5898550
OpenAlexW2763709769

What OpenQuestion holds

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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.