Evidence map›Paper›PMID 24281100›Full record

ArticleCancers2010

Predictive and prognostic protein biomarkers in epithelial ovarian cancer: recommendation for future studies.

Cécile Le Page, David G Huntsman, Diane M Provencher, Anne-Marie Mes-Masson

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

17 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. High Expression ofFrontiers in oncology · 2022
    Article
  5. The Anterior GRadient (AGR) family proteins in epithelial ovarian cancer.Journal of experimental & clinical cancer research : CR · 2021
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Lesser-Known Molecules in Ovarian Carcinogenesis.BioMed research international · 2015
    Review
  12. Expression of the MT1 melatonin receptor in ovarian cancer cells.International journal of molecular sciences · 2014
    Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
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

4 authors at 2 institutions in 1 country.

Cécile Le PageCentre de recherche du Centre hospitalier de l'Université de Montréal (CR/CHUM), Institut du cancer de Montréal, 1560 Sherbrooke Est, Montreal, H2L4M1, QC, Canada. anne-marie.mes-masson@umontreal.ca.
David G Huntsman
Diane M Provencher
Anne-Marie Mes-Masson
Centre Hospitalier de l’Université de Montréal · CABC Cancer Agency · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ovarian cancer is the most lethal gynecological malignancy. Due to its lack of symptoms, this disease is diagnosed at an advanced stage when the cancer has already spread to secondary sites. While initial rates of response to first treatment is >80%, the overall survival rate of patients is extremely low, mainly due to development of drug resistance. To date, there are no reliable clinical factors that can properly stratify patients for suitable chemotherapy strategies. Clinical parameters such as disease stage, tumor grade and residual disease, although helpful in the management of patients after their initial surgery to establish the first line of treatment, are not efficient enough. Accordingly, reliable markers that are independent and complementary to clinical parameters are needed for a better management of these patients. For several years, efforts to identify prognostic factors have focused on molecular markers, with a large number having been investigated. This review aims to present a summary of the recent advances in the identification of molecular biomarkers in ovarian cancer patient tissues, as well as an overview of the need and importance of molecular markers for personalized medicine in ovarian cancer.

Identifiers

PMID24281100
PMCPMC3835111
OpenAlexW2056816232

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.