Evidence map›Paper›PMID 28727136›Full record

ArticleCancer2017

A multidimensional view of racial differences in access to prostate cancer care.

Craig Evan Pollack, Katrina A Armstrong, Nandita Mitra, Xinwei Chen, Katelyn R Ward, Archana Radhakrishnan, Michelle S Wong, Justin E Bekelman, Charles C Branas, Karin V Rhodes and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in Cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.0field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Developing a Patient Experience Questionnaire for the Man Van Mobile Clinical Unit.Health expectations : an international journal of public participation in health care and health policy · 2025
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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

11 authors at 5 institutions in 1 country.

Craig Evan PollackDivision of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland.
Katrina A ArmstrongDepartment of Medicine, Massachusetts General Hospital, Boston, Massachusetts.
Nandita MitraDepartment of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Xinwei ChenDivision of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Katelyn R WardDivision of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.ORCID http://orcid.org/0000-0002-1772-0368
Archana RadhakrishnanDivision of General Internal Medicine, University of Michigan, Ann Arbor, Michigan.ORCID http://orcid.org/0000-0001-7689-6390
Michelle S WongDepartment of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Justin E BekelmanDepartment of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Charles C BranasDepartment of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Karin V RhodesOffice of Population Health Management, Northwell Health/Hofstra Northwell School of Medicine, Manhasset, New York.
David T GrandeDivision of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
University of Pennsylvania · USJohns Hopkins University · USMassachusetts General Hospital · USNorthwell Health · USUniversity of Michigan · US

Funding

Research Traiing/Education CoreP60MD006900 · NIMHD · UNIVERSITY OF PENNSYLVANIA · PI ARMSTRONG, KATRINA · 2012 to 2016
$6.6M
A Network Analytic Approach to Modeling Variation in Prostate Cancer CareK07CA151910 · NCI · JOHNS HOPKINS UNIVERSITY · PI POLLACK, CRAIG EVAN · 2011 to 2015
$780k
NCI NIH HHS K07 CA151910NIMHD NIH HHS P60 MD006900
6 · The paper itself

Abstract

backgroundRacial disparities in prostate cancer treatment and outcomes are widespread and poorly understood. In the current study, the authors sought to determine whether access to care, measured across multiple dimensions, contributed to racial differences in prostate cancer.

methodsThe Philadelphia Area Prostate Cancer Access Study (P

resultsThere were 1907 non-Hispanic white and 394 black men in the study cohort. Overall, approximately 85% of the men received definitive treatment with no differences noted by race. Black men were less likely to report a high quality of care (69% vs 81%; P<.001) and good physician-patient communication (60% vs 71%; P<.001) compared with white men. In adjusted models, none of the 5 domains of access were found to be associated with definitive treatment overall or with radical prostatectomy. All access domains were associated with perceived quality of care and communication, although these domains did not mediate racial disparities.

conclusionsTo the authors' knowledge, the current study presents the first comprehensive assessment of prostate cancer care access, treatment, and patient experience, demonstrating that although access was related to overall perceived quality of care and better physician-patient communication, it did not appear to explain observed racial differences. Cancer 2017;123:4449-57. © 2017 American Cancer Society.

Indexed as

AdultAgedAged, 80 and overBlack or African AmericanCohort StudiesHealthcare DisparitiesHealth Services AccessibilityHumansMaleMiddle AgedPhiladelphiaProstatic NeoplasmsRacial GroupsRegistriesUnited StatesWhite Peopleaccess to caredefinitive treatmentprostate cancerprostate cancer treatmentracial disparities

Identifiers

PMID28727136
PMCPMC5673580
OpenAlexW2737392005

What OpenQuestion holds

Textmetadata
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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.