Evidence map›Paper›PMID 25593898›Full record

ArticleClinical cancer investigation journal

New serum biomarkers for prostate cancer diagnosis.

Kailash C Chadha, Austin Miller, Bindukumar B Nair, Stanley A Schwartz, Donald L Trump, Willie Underwood

Abstract read
In one paragraph

Article in Clinical cancer investigation journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 17% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Analysis of Serum Markers with Regard to Treatment Procedures in Advanced Stage Prostate Cancer Patients.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  7. Article
  8. Review
  9. Article
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  12. 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

6 authors at 2 institutions in 1 country.

Kailash C ChadhaDepartment of Molecular and Cellular Biology, Roswell Park Cancer Institute, University at Buffalo, Buffalo, NY, USA.
Austin MillerDepartment of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, University at Buffalo, Buffalo, NY, USA.
Bindukumar B NairDepartment of Molecular and Cellular Biology, Roswell Park Cancer Institute, University at Buffalo, Buffalo, NY, USA ; Department of Medicine, Division of Allergy/Immunology and Rheumatology, University at Buffalo, Buffalo, NY, USA.
Stanley A SchwartzDepartment of Medicine, Division of Allergy/Immunology and Rheumatology, University at Buffalo, Buffalo, NY, USA.
Donald L TrumpDepartment of Medicine, Roswell Park Cancer Institute, University at Buffalo, Buffalo, NY, USA.
Willie UnderwoodDepartment of Urologic Oncology, Roswell Park Cancer Institute, University at Buffalo, Buffalo, NY, USA.
Roswell Park Comprehensive Cancer Center · USUniversity at Buffalo, State University of New York · US

Funding

CANCER AND LEUKEMIA GROUP B MINORITY SATELLITE SUPPLEMENU10CA031946 · NCI · UNIVERSITY OF CHICAGO · PI BERTAGNOLLI, MONICA M · 1985 to 2013
$158.4M
Two-Spirit Films in Indigenous Cancer HealthP30CA016056 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI Christine B. Ambrosone · 1985 to 2026
$116.6M
CANCER &LEUKEMIA GROUP B STATISTICAL CENTERU10CA033601 · NCI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI SARGENT, DANIEL J. · 1985 to 2013
$69.4M
Cancer and Leukemia Group B Human Specimen RepositoriesU24CA114725 · NCI · UNIVERSITY OF CHICAGO · PI BERTAGNOLLI, MONICA M · 2005 to 2014
$11.1M
BIOMARKERS FOR DIAGNOSIS & MANAGEMENT OF PROSTATE CANCERR21CA113950 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI CHADHA, KAILASH · 2006 to 2007
$276k
NCI NIH HHS P30 CA016056NCI NIH HHS R21 CA113950NCI NIH HHS U10 CA031946NCI NIH HHS U10 CA033601NCI NIH HHS U24 CA114725
6 · The paper itself

Abstract

backgroundProstate-specific antigen (PSA) is currently used as a biomarker for diagnosis and management of prostate cancer (CaP). However, PSA typically lacks the sensitivity and specificity desired of a diagnostic marker.

objectiveThe goal of this study was to identify an additional biomarker or a panel of biomarkers that is more sensitive and specific than PSA in differentiating benign versus malignant prostate disease and/or localized CaP versus metastatic CaP.

methodsConcurrent measurements of circulating interleukin-8 (IL-8), Tumor necrosis factor-α (TNF-α) and soluble tumor necrosis factor-α receptors 1 (sTNFR1) were obtained from four groups of men: (1) Controls (2) with elevated prostate-specific antigen with a negative prostate biopsy (elPSA_negBx) (3) with clinically localized CaP and (4) with castration resistant prostate cancer.

resultsTNF-α Area under the receiver operating characteristic curve (AUC = 0.93) and sTNFR1 (AUC = 0.97) were strong predictors of elPSA_negBx (vs. CaP). The best predictor of elPSA_negBx vs CaP was sTNFR1 and IL-8 combined (AUC = 0.997). The strongest single predictors of localized versus metastatic CaP were TNF-α (AUC = 0.992) and PSA (AUC = 0.963) levels.

conclusionsThe specificity and sensitivity of a PSA-based CaP diagnosis can be significantly enhanced by concurrent serum measurements of IL-8, TNF-α and sTNFR1. In view of the concerns about the ability of PSA to distinguish clinically relevant CaP from indolent disease, assessment of these biomarkers in the larger cohort is warranted.

Indexed as

Castration resistant prostate cancerinterleukin-8prostate cancerprostate specific antigenserum biomarkertumor necrosis factor-α

Identifiers

PMID25593898
PMCPMC4292911
OpenAlexW2042729833

What OpenQuestion holds

Textmetadata
LicenceTDM
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.