Evidence map›Paper›PMID 33026148›Full record

ReviewClinical and translational science2021

The Translational Approaches to Personalized Health Collaborative: Pharmacogenomics for African American Older Adults.

Lana J Sargent, Marissa Mackiewicz, Youssef Roman, Ana Diallo, Sally Russell, Katherine Falls, Kristin M Zimmerman, Dave L Dixon, Elizabeth Prom-Wormley, Sarah Hobgood and 3 more

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 23% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Observational
  3. 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

13 authors at 2 institutions in 1 country.

Lana J SargentSchool of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA.
Marissa MackiewiczGeriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.
Youssef RomanGeriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.
Ana DialloSchool of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA.
Sally RussellSchool of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA.
Katherine FallsSchool of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA.
Kristin M ZimmermanGeriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.
Dave L DixonDepartment of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.
Elizabeth Prom-WormleyInstitute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA.
Sarah HobgoodSchool of Medicine, Department of Geriatrics, Virginia Commonwealth University, Richmond, Virginia, USA.
Sarah K LagemanSchool of Medicine, Neuropsychology Program Director and Department of Neurology, Virginia Commonwealth University, Richmond, Virginia, USA.
Faika ZanjaniInstitute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA.
Elvin T PriceGeriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.
Virginia Commonwealth University · USCenter for Innovation · US

Funding

African American Cardiovascular pharmacogenetic CONsorTium (ACCOuNT): discovery and translationU54MD010723 · NIMHD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI MELTZER, DAVID O, PERERA, MINOLI A · 2016 to 2020
$9.5M
NIMHD NIH HHS U54 MD010723
6 · The paper itself

Abstract

Older adults (i.e., 60 years and older), are the leading consumers of medications, and consequently are suffering the most from medication-related adverse events. Not only are older adults the largest consumers of medications, they are more likely to experience an adverse drug event contributing to increased hospitalization, utilization of emergency medical services, and mortality. Translational Approaches to Personalized Health (TAPH) is a transdisciplinary team of researchers conducting community-engaged participatory research focused on the discovery and translation of pharmacogenomic (PGx) data to improve health outcomes. Underserved and ethnically diverse older adults living in urban settings are significantly under-represented in PGx studies. To address the issue of under-representation, our study enrolls older African American adults into a community-based PGx study. Therefore, we will characterize the frequency of actionable PGx genotypes and identify novel PGx response genes in our cohort of older community dwelling African Americans. The translational component of our work is to use the PGx findings to improve therapeutic outcomes for medication management in older adults. Such findings will serve as a foundation for translational PGx studies aimed at improving medication efficacy and safety for older adults. In this article, we describe the process for launching the TAPH collaborative group, which includes the transdisciplinary team, community-engaged participatory research model, study measures, and the evaluation of PGx genes.

Indexed as

Intersectoral CollaborationAgedAge FactorsBlack or African AmericanCommunity-Based Participatory ResearchDrug-Related Side Effects and Adverse ReactionsHumansPharmacogenomic TestingPharmacogenomic VariantsPrecision MedicineTranslational Research, Biomedical

Identifiers

PMID33026148
PMCPMC7993264
OpenAlexW3092137723

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.