Evidence map›Paper›PMID 25530379›Full record

ArticleUrology2015

Impact of prostate-specific antigen on a baseline prostate cancer risk assessment including genetic risk.

A Karim Kader, Michael A Liss, Greg Trottier, Seong-Tae Kim, Jielin Sun, S Lilly Zheng, Karen Chadwick, Gina Lockwood, Jianfeng Xu, Neil E Fleshner

Abstract read
In one paragraph

Article in Urology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

A Karim KaderDepartment of Urology, Moores Cancer Center, University of California San Diego, San Diego, CA. Electronic address: kkader@ucsd.edu.
Michael A LissDepartment of Urology, Moores Cancer Center, University of California San Diego, San Diego, CA.
Greg TrottierDivision of Urology, Department of Surgery, University Health Network, Toronto, Canada.
Seong-Tae KimDepartments of Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC.
Jielin SunDepartments of Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC.
S Lilly ZhengDepartments of Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC.
Karen ChadwickDivision of Urology, Department of Surgery, University Health Network, Toronto, Canada.
Gina LockwoodCanadian Partnership Against Cancer, Toronto, Canada.
Jianfeng XuDepartments of Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC.
Neil E FleshnerDivision of Urology, Department of Surgery, University Health Network, Toronto, Canada.

Funding

Clinical validity and utility of genomic targeted chemoprevention of PCaUC2CA148463 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI XU, JIANFENG · 2010 to 2010
$2.0M
Clinical validity and utility of genomic targeted chemoprevention of PCaRC2CA148463 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI XU, JIANFENG · 2009 to 2009
$2.0M
NCI NIH HHS CA148463NCI NIH HHS RC2 CA148463NCI NIH HHS UC2 CA148463
6 · The paper itself

Abstract

objectiveTo determine to what extent prostate cancer (PCa) risk prediction is improved by adding prostate-specific antigen (PSA) to a baseline model including genetic risk.

methodsPeripheral blood deoxyribonucleic acid was obtained from Caucasian men undergoing prostate biopsy at the University of Toronto (September 1, 2008 to January 31, 2010). Thirty-three PCa risk-associated single nucleotide polymorphisms were genotyped to generate the prostate cancer genetic score 33 (PGS-33). Primary outcome is PCa on study prostate biopsy. Logistic regression, area under the receiver-operating characteristic curves (AUC), and net reclassification improvement were used to compare models.

resultsAmong 670 patients, 323 (48.2%) were diagnosed with PCa. The PGS-33 was highly associated with biopsy-detectable PCa (odds ratio, 1.66; P = 5.86E-05; AUC, 0.59) compared with PSA (odds ratio, 1.33; P = .01; AUC, 0.55). PSA did not improve risk prediction when added to a baseline model (age, family history, digital rectal examination, and PGS-33) for overall risk (AUC, 0.66 vs 0.66; P = .86) or Gleason score ≥7 PCa (AUC, 0.71 vs 0.73; P = .15). Net reclassification improvement analyses demonstrated no appropriate reclassifications with the addition of PSA to the baseline model for overall PCa but did show some benefit for reclassification of men thought to be at higher baseline risk in the high-grade PCa analysis.

conclusionIn a baseline model of PCa risk including the PGS-33, PSA does not add to risk prediction for overall PCa for men presenting for "for-cause" biopsy. These findings suggest that PSA screening may be minimized in men at low baseline risk.

Indexed as

AdultAgedAged, 80 and overBiopsyGenetic Predisposition to DiseaseHumansMaleMiddle AgedProstate-Specific AntigenProstatic NeoplasmsRisk AssessmentRisk FactorsProstate-Specific Antigen

Identifiers

PMID25530379
PMCPMC5398897

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Registered trials

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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.