Evidence map›Paper›PMID 23543886›Full record

ArticlePersonalized medicine2012

Why personalized medicine will fail if we stay the course.

Edward Ramos, Shawneequa L Callier, Charles N Rotimi

Abstract read
In one paragraph

Article in Personalized medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

18 citing papers in PubMed, 59 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Genetic ancestry in precision medicine is reshaping the race debate.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. The mathematical limits of genetic prediction for complex chronic disease.Journal of epidemiology and community health · 2015
    Article
  14. Pharmacogenetics of drug-metabolizing enzymes in US Hispanics.Drug metabolism and personalized therapy · 2015
    Review
  15. Article
  16. Article
  17. Article
  18. Article
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

3 authors at 2 institutions in 1 country.

Edward RamosCenter for Research on Genomics & Global Health, National Human Genome Research Institute, NIH, Bethesda, MD, 20892-5635, USA.
Shawneequa L Callier
Charles N Rotimi
National Human Genome Research Institute · USGeorge Washington University · US

Funding

Genetic epidemiology of complex diseasesZIAHG200362 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI ROTIMI, CHARLES · 2009 to 2025
$54.7M
Understanding Obesity In Relation to the Built EnvironmentP20MD006899 · NIMHD · JACKSON STATE UNIVERSITY · PI ANTOINE-LAVIGNE, DONNA A · 2012 to 2016
$5.3M
Genetic epidemiology of complex diseasesZ01HG200362 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI ROTIMI, CHARLES · 2008 to 2008
$1.7M
Intramural NIH HHS Z01 HG200362Intramural NIH HHS Z99 HG999999Intramural NIH HHS Z99 HL999999Intramural NIH HHS Z99 MH999999NIMHD NIH HHS P20 MD006899
6 · The paper itself

Abstract

Genomic science and associated technologies are providing scientists and clinicians with novel insights that are transforming the delivery of healthcare and the overall well-being of society. However, these insights inform us that historical population sampling approaches for investigating rare and common genetic variations are not representative of the complex ancestral backgrounds of today's patients. In order for personalized medicine to be meaningful and applicable to the global populations, we will need to know how common and rare genetic variants found in different parts of the world influence health and drug response. This article demonstrates the importance of increasing ethnic and racial diversity among participants in genomic research, highlights areas of opportunity for improving our understanding of genomic diversity among populations, and provides examples of successful models that help to resolve these concerns.

Indexed as

diversityethnicitygenomic medicineglobal populationspersonalized medicine

Identifiers

PMID23543886
PMCPMC3609663
OpenAlexW2142104861

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.