ArticleClinical and translational science2023
Pharmacogenetic actionability and medication prescribing in people with cystic fibrosis.
Article in Clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 9 citations in OpenAlex.
- Precision percutaneous coronary intervention.NPJ cardiovascular health · 2026Review
- Current State of Pharmacogenomic Implementation Into Care for Persons With Cystic Fibrosis.Pediatric pulmonology · 2025Article
- Unveiling the heritability of selected unexplored pharmacogenetic markers in the Saudi population.Frontiers in pharmacology · 2025Article
- Pharmacogenetic actionability and medication prescribing in people with cystic fibrosis.Clinical and translational science · 2023Article
- Article
- Pharmacogenomics and rare diseases: optimizing drug development and personalized therapeutics.PharmacogenomicsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Although major advancements have been made in the therapeutics for people with cystic fibrosis (PwCF), many still require the use of multiple medications to manage acute exacerbations of disease and maintain health. Iterative trial and error processes of pharmacotherapeutic management can be optimized by assessing and incorporating pharmacogenetics. For 82 PwCF, we reviewed 2 years of medication use and response history and interrogated metabolizer status for common pharmacogenes, revealing 3336 medication exposure events (MEEs) to 286 unique medications. As expected, the more frequent MEEs were those commonly used to treat cystic fibrosis (CF), such as antibiotics and respiratory medications. Antibiotics also comprised 56.7% of the undesirable drug responses. The impact of gene variants on drug responses was assessed using Pharmacogenomics Knowledgebase (PharmGKB) and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Thirty-three (11.5%) medications have strong evidence of genetic influence on response as evidenced by gene-based dosing guidelines. 110 (38.5%) unique medications had at least one association with a very important pharmacogene, whereas 143 (50%) were associated with at least one clinical or variant annotation. Over 97% of participants had at least one actionable genotype. Eleven (13.4%) patients with an actionable genotype, taking the impacted medication, had an undesirable drug response described in the CPIC guidelines that could potentially have been mitigated with a priori knowledge of the genotype. PwCF take many medications for disease management, with frequent dose changes to elicit a desired clinical effect. As CF care evolves, implementing pharmacogenetics testing can improve efficiency and safety of prescribing practices using precision selection and dosing at medication initiation.
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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.