Evidence map›Paper›PMID 34268895›Full record

ReviewClinical and translational science2021

Applying an equity lens to pharmacogenetic research and translation to under-represented populations.

Tiana Luczak, David Stenehjem, Jacob Brown

Open access · goldAbstract readReview
In one paragraph

Review in Clinical and translational science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

16 citing papers in PubMed, 16 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Tiana LuczakDepartment of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, Minnesota, USA.
David StenehjemDepartment of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, Minnesota, USA.
Jacob BrownDepartment of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, Minnesota, USA.
University of Minnesota, Duluth · USEssentia Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the publication of the Human Genome Project, genetic information has been used as an accepted, evidence-based biomarker to optimize patient care through the delivery of precision health. Pharmacogenetics (PGx) uses information about genes that encode proteins involved in pharmacokinetics, pharmacodynamics, and hypersensitivity reactions to guide clinical decision making to optimize medication therapy selection. Clinical PGx implementation is growing from the dramatic increase in PGx studies over the last decade. However, an overwhelming lack of genetic diversity in current PGx studies is evident. This lack of diverse representation in PGx studies will impede equitable clinical implementation through potentially inappropriate application of gene-based dosing algorithms, whereas representing a missed opportunity for identification of population specific single nucleotide variants and alleles. In this review, we discuss the challenges of studying PGx in under-represented populations, highlight two successful PGx studies conducted in non-European populations, and propose a path forward through community-based participatory research for equitable PGx research and clinical translation.

Indexed as

Genetic VariationPharmacogeneticsResearchCytochrome P-450 CYP2D6Genome, HumanHumansCytochrome P-450 CYP2D6

Identifiers

PMID34268895
PMCPMC8604241
OpenAlexW3178352266

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.