Evidence map›Paper›PMID 22190978›Full record

ArticlePersonalized medicine2011

Early developments in gene-expression profiling of breast tumors: potential for increasing black-white patient disparities in breast cancer outcomes?

Donna H Odierna, Aimee Afable-Munsuz, Ogechi Ikediobi, Mary Beattie, Sara Knight, Michelle Ko, Adrienne Wilson, Ninez A Ponce

Abstract read
In one paragraph

Article in Personalized medicine, 2011. 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

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

8 authors.

Donna H OdiernaDepartment of Community Health Sciences, SUNY Downstate School of Public Health, 450 Clarkson Avenue, Box #43, Brooklyn, NY 11203, USA.
Aimee Afable-Munsuz
Ogechi Ikediobi
Mary Beattie
Sara Knight
Michelle Ko
Adrienne Wilson
Ninez A Ponce

Funding

UCSF CLINICAL AND TRANSLATIONAL SCIENCE INSTITUTEUL1RR024131 · NCRR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOHNSTON, S. CLAIBORNE · 2006 to 2011
$111.2M
UTILIZATION OF PERSONALIZED MEDICINE USING GENOMICSP01CA130818 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PHILLIPS, KATHRYN A · 2008 to 2010
$5.1M
NCI NIH HHS P01 CA130818NCRR NIH HHS UL1 RR024131
6 · The paper itself

Abstract

New prognostic tests, such as gene-expression profiling (GEP) of breast tumors, are expected to prolong survival and improve the quality of life for many breast cancer patients. In this article, we argue that GEP has not been adequately validated in minority populations, and that both biological and social factors might affect the broad utility of these tests in diverse populations. We suggest that the widespread use of this technology could potentially lead to suboptimal treatment for black women, resulting in a further increase in black-white patient disparities in treatment response, morbidity and mortality rates. We argue for the need to build a large and diverse evidence base for GEP and other emerging technologies in personalized medicine.

Identifiers

PMID22190978
PMCPMC3242007

What OpenQuestion holds

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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.