Evidence map›Paper›PMID 31388184›Full record

Trial reportBritish journal of cancer2019

Diagnosis of epithelial ovarian cancer using a combined protein biomarker panel.

Matthew R Russell, Ciaren Graham, Alfonsina D'Amato, Aleksandra Gentry-Maharaj, Andy Ryan, Jatinderpal K Kalsi, Anthony D Whetton, Usha Menon, Ian Jacobs, Robert L J Graham

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in British journal of cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Molecular Management of High-Grade Serous Ovarian Carcinoma.International journal of molecular sciences · 2022
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Biomarkers and Strategies for Early Detection of Ovarian Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  19. Article
  20. 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

10 authors.

Matthew R RussellStoller Biomarker Discovery Centre and Manchester Molecular Pathology Innovation Centre, Division of Cancer Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.
Ciaren GrahamSchool of Biological Sciences, Queens University Belfast, Chlorine Gardens, Belfast, BT9 5DL, UK.
Alfonsina D'AmatoDepartment of Pharmaceutical Sciences, University of Milan, Milano, Lombardy, Italy.
Aleksandra Gentry-MaharajMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, Faculty of Population Health Sciences, University College London, London, UK.
Andy RyanMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, Faculty of Population Health Sciences, University College London, London, UK.
Jatinderpal K KalsiMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, Faculty of Population Health Sciences, University College London, London, UK.
Anthony D WhettonStoller Biomarker Discovery Centre and Manchester Molecular Pathology Innovation Centre, Division of Cancer Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.
Usha MenonMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, Faculty of Population Health Sciences, University College London, London, UK.
Ian JacobsStoller Biomarker Discovery Centre and Manchester Molecular Pathology Innovation Centre, Division of Cancer Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK. i.jacobs@unsw.edu.au.
Robert L J GrahamSchool of Biological Sciences, Queens University Belfast, Chlorine Gardens, Belfast, BT9 5DL, UK. r.graham@qub.ac.uk.

Funding

Cancer Research UK 12677Cancer Research UK C1005/A12677Department of HealthMedical Research Council G9901012Medical Research Council MR/M008959/1
6 · The paper itself

Abstract

backgroundAn early detection tool for EOC was constructed from analysis of biomarker expression data from serum collected during the UKCTOCS.

methodsThis study included 49 EOC cases (19 Type I and 30 Type II) and 31 controls, representing 482 serial samples spanning seven years pre-diagnosis. A logit model was trained by analysis of dysregulation of expression data of four putative biomarkers, (CA125, phosphatidylcholine-sterol acyltransferase, vitamin K-dependent protein Z and C-reactive protein); by scoring the specificity associated with dysregulation from the baseline expression for each individual.

resultsThe model is discriminatory, passes k-fold and leave-one-out cross-validations and was further validated in a Type I EOC set. Samples were analysed as a simulated annual screening programme, the algorithm diagnosed cases with >30% PPV 1-2 years pre-diagnosis. For Type II cases (~80% were HGS) the algorithm classified 64% at 1 year and 28% at 2 years tDx as severe.

conclusionsThe panel has the potential to diagnose EOC one-two years earlier than current diagnosis. This analysis provides a tangible worked example demonstrating the potential for development as a screening tool and scrutiny of its properties. Limits on interpretation imposed by the number of samples available are discussed.

Indexed as

AlgorithmsBiomarkers, TumorBlood ProteinsCA-125 AntigenCarcinoma, Ovarian EpithelialC-Reactive ProteinEarly Detection of CancerFemaleFollow-Up StudiesHumansPhosphatidylcholine-Sterol O-AcyltransferasePrognosisProspective StudiesRetrospective StudiesBiomarkers, TumorBlood ProteinsCA-125 AntigenC-Reactive ProteinLCAT protein, humanPhosphatidylcholine-Sterol O-Acyltransferaseplasma protein Z

Identifiers

PMID31388184
PMCPMC6738042

What OpenQuestion holds

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LicenceCC BY
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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.