Evidence map›Paper›PMID 21704359›Full record

ArticleGynecologic oncology2011

Comparison of candidate serologic markers for type I and type II ovarian cancer.

Dan Lu, Elisabetta Kuhn, Robert E Bristow, Robert L Giuntoli, Susanne Krüger Kjær, Ie-Ming Shih, Richard B S Roden

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Gynecologic oncology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 3 pooled it
7.6field-weighted citation impact, top 3% 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

30 citing papers in PubMed, 3 syntheses or guidelines pooled it, 56 citations in OpenAlex.

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  9. Prolactin and Risk of Epithelial Ovarian Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021
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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

7 authors at 3 institutions in 2 countries.

Dan LuDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
Elisabetta Kuhn
Robert E Bristow
Robert L Giuntoli
Susanne Krüger Kjær
Ie-Ming Shih
Richard B S Roden
Johns Hopkins University · USJohns Hopkins Medicine · USDanish Cancer Society · DK

Funding

Treatment of HIV- and HIV+ Patients with HPV16+ CIN2/3 Using pNGLV4a-hCRTE6E7L2 DNA vaccine administered intramuscularly via electroporationP50CA098252 · NCI · JOHNS HOPKINS UNIVERSITY · PI Richard Bruce Roden · 2003 to 2026
$53.5M
Tumor-Associated Antigens in Early Stage Serous CarcinomaR01CA122581 · NCI · JOHNS HOPKINS UNIVERSITY · PI RODEN, RICHARD BRUCE · 2006 to 2010
$1.5M
NCI NIH HHS P50 CA098252NCI NIH HHS R01 CA122581
6 · The paper itself

Abstract

objectiveTo examine the value of individual and combinations of ovarian cancer associated blood biomarkers for the discrimination between plasma of patients with type I or II ovarian cancer and disease-free volunteers.

methodsLevels of 14 currently promising ovarian cancer-related biomarkers, including CA125, macrophage inhibitory factor-1 (MIF-1), leptin, prolactin, osteopontin (OPN), insulin-like growth factor-II (IGF-II), autoantibodies (AAbs) to eight proteins: p53, NY-ESO-1, p16, ALPP, CTSD, B23, GRP78, and SSX, were measured in the plasma of 151 ovarian cancer patients, 23 with borderline ovarian tumors, 55 with benign tumors and 75 healthy controls.

resultsWhen examined individually, seven candidate biomarkers (MIF, Prolactin, CA-125, OPN, Leptin, IGF-II and p53 AAbs) had significantly different plasma levels between type II ovarian cancer patients and healthy controls. Based on the receiver operating characteristic (ROC) curves constructed and area under the curve (AUC) calculated, CA125 exhibited the greatest power to discriminate the plasma samples of type II cancer patients from normal volunteers (AUC 0.9310), followed by IGF-II (AUC 0.8514), OPN (AUC 0.7888), leptin (AUC 0.7571), prolactin (AUC 0.7247), p53 AAbs (AUC 0.7033), and MIF (AUC 0.6992). p53 AAbs levels exhibited the lowest correlation with CA125 levels among the six markers, suggesting the potential of p53 AAbs as a biomarker independent of CA125. Indeed, p53 AAbs increased the AUC of ROC curve to the greatest extent when combining CA125 with one of the other markers. At a fixed specificity of 100%, the addition of p53 AAbs to CA125 increased sensitivity from 73.8% to 85.7% to discriminate type II cancer patients from normal controls. Notably, seropositivity of p53 AAbs is comparable in type II ovarian cancer patients with negative and positive CA125, but has no value for type I ovarian cancer patients.

conclusionsp53 AAbs might be a useful blood-based biomarker for the detection of type II ovarian cancer, especially when combined with CA125 levels.

Indexed as

AdultAgedAged, 80 and overAntigens, NeoplasmAutoantibodiesBiomarkers, TumorCA-125 AntigenEndoplasmic Reticulum Chaperone BiPEnzyme-Linked Immunosorbent AssayFemaleHumansMembrane ProteinsMiddle AgedOvarian NeoplasmsTumor Suppressor Protein p53Antigens, NeoplasmAutoantibodiesBiomarkers, TumorCA-125 AntigenCTAG1B protein, humanEndoplasmic Reticulum Chaperone BiPHSPA5 protein, humanMembrane ProteinsMUC16 protein, humanTP53 protein, humanTumor Suppressor Protein p53

Identifiers

PMID21704359
PMCPMC3152615
OpenAlexW2031104566

What OpenQuestion holds

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Read underepoch 390

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.