Evidence map›Paper›PMID 19389550›Full record

ReviewClinics in laboratory medicine2009

Development and validation of a protein-based signature for the detection of ovarian cancer.

Kyongjin Kim, Irene Visintin, Ayesha B Alvero, Gil Mor

Abstract readReview
In one paragraph

Review in Clinics in laboratory medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Trial
  2. Review
  3. Review
  4. Review of biomarker systems as an alternative for early diagnosis of ovarian carcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2021
    Review
  5. Review
  6. Review
  7. Article
  8. Ovarian cancer: can proteomics give new insights for therapy and diagnosis?International journal of molecular sciences · 2013
    Review
  9. The duplicitous origin of ovarian cancer.Rambam Maimonides medical journal · 2013
    Article
  10. Article
  11. Review
  12. Review
  13. 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

4 authors.

Kyongjin KimDepartment of Obstetrics, Gynecology and Reproductive Sciences, Reproductive Immunology Unit, Yale University School of Medicine, 333 Cedar Street FMB 301, New Haven, CT 06520, USA.
Irene Visintin
Ayesha B Alvero
Gil Mor

Funding

Apoptotic regulators in ovarian cancerR01CA118678 · NCI · YALE UNIVERSITY · PI MOR, GIL G · 2007 to 2011
$1.7M
MyD88-bearing tumors in immune-regulation and chemo-resistanceR01CA127913 · NCI · YALE UNIVERSITY · PI MOR, GIL G · 2008 to 2012
$1.7M
NCI NIH HHS R01 CA118678NCI NIH HHS R01 CA127913
6 · The paper itself

Abstract

To overcome the significant mortality associated with ovarian cancer, a highly sensitive and specific screening test is urgently needed. CA-125 testing is used to monitor response to chemotherapy, detect recurrence, and detect late stage ovarian cancer. However, CA-125 testing, alone or in combination with ultrasonography, has not been adequate for early detection of ovarian cancer. This article discusses the authors' recent report of a novel multiplex assay that uses a panel of six serum biomarkers: leptin, prolactin, osteopontin, insulin-like growth factor II (IGF-II), macrophage inhibitory factor (MIF), and CA-125. The combination of these six proteins yielded 95.3% sensitivity and 99.4% specificity. The application of this test in the clinical context and the most appropriate population, which could benefit from the test, are discussed.

Indexed as

Biomarkers, TumorData Interpretation, StatisticalEnzyme-Linked Immunosorbent AssayFemaleHumansOvarian NeoplasmsProtein Array AnalysisProteomicsReproducibility of ResultsBiomarkers, Tumor

Identifiers

PMID19389550
PMCPMC2720626

What OpenQuestion holds

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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.