ArticleClinical and translational science2021
Evaluation of population-level pharmacogenetic actionability in Alabama.
Article 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 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- The Frequency ofPharmaceutics · 2024Article
- Pharmacogenetic actionability and medication prescribing in people with cystic fibrosis.Clinical and translational science · 2023Article
- Evaluation of population-level pharmacogenetic actionability in Alabama.Clinical and translational science · 2021Article
- Translational Pharmacogenomics: Discovery, Evidence Synthesis and Delivery of Race-Conscious Medicine.Clinical pharmacology and therapeutics · 2021Review
- Revisiting Secondary Information Related to Pharmacogenetic Testing.Frontiers in genetics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The evolution of evidence and availability of Clinical Pharmacogenetic Implementation Consortium (CPIC) guidelines have enabled assessment of pharmacogenetic (PGx) actionability and clinical implementation. However, population-level actionability is not well-characterized. We leveraged the Alabama Genomic Health Initiative (AGHI) to evaluate population-level PGx actionability. Participants (>18 years), representing all 67 Alabama counties, were genotyped using the Illumina Global Screening array. Using CPIC guidelines, actionability was evaluated using (1) genotype data and genetic ancestry, (2) prescribing data, and (3) combined genotype and medication data. Of 6,331 participants, 4230 had genotype data and 3386 had genotype and prescription data (76% women; 76% White/18% Black [self-reported]). Genetic ancestry was concordant with self-reported race. For CPIC level A genes, 98.6% had an actionable genotype (99.4% Blacks/African; 98.5% White/European). With the exception of DPYD and CYP2C19, the prevalence of actionable genotypes by gene differed significantly by race. Based on prescribing, actionability was highest for CYP2D6 (70.9%), G6PD (54.1%), CYP2C19 (53.5%), and CYP2C9 (47.5%). Among participants prescribed atenolol, carvedilol, or metoprolol, ~ 50% had an actionable ADRB1 genotype, associated with decreased therapeutic response, with higher actionability among Blacks compared to Whites (62.5% vs. 47.4%; p < 0.0001). Based on both genotype and prescribing frequencies, no significant differences in actionability were observed between men and women. This statewide effort highlights PGx population-level impact to help optimize pharmacotherapy. Almost all Alabamians harbor an actionable genotype, and a significant proportion are prescribed affected medications. Statewide efforts, such as AGHI, lay the foundation for translational research and evaluate "real-world" outcomes of PGx.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.