ArticlePharmacogenomics and personalized medicine2025
The Prevalence of Potential Drug-Drug-Gene Interactions: A Descriptive Study Using Swiss Claims Data.
Article in Pharmacogenomics and personalized medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- From evidence to implementation: key priorities for pharmacogenomics-guided treatment and prevention from a European expert workshop.European journal of human genetics : EJHG · 2026Article
- Population-Based Assessment of Phenoconversion Potential in Switzerland: A Claims Data Study of Key Drug-Metabolizing Enzymes and Transporters.Pharmacogenomics and personalized medicine · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Purpose: We aimed to determine the prevalence of interactions between PGx drugs metabolized by CYP2C9, CYP2C19, and CYP2D6 and drugs that act as inhibitors or inducers of those enzymes in the Swiss population. Patients and Methods: We defined concomitant use of PGx drugs and inhibitors/inducers as instances where a claim of a PGx drug and a claim of an inducer or inhibitor concerning the same enzyme were made within a specified temporal window, either ± 5 days or ± 30 days. We assessed concomitant drug use between 2017 and 2021, using claims data from a Swiss insurance company (Helsana). Results: Out of 894,748 individuals continuously insured, between 17.4% (± 5-days window) and 24.8% (± 30-days window) were exposed to potentially interacting drug pairs, with 1.5% to 2.2% being exposed to potentially strong interacting drug pairs. Individuals exposed to potentially interacting drugs were more frequently female, older and took a greater number of drugs than the general population. The majority of potential interactions were associated with CYP2D6 or CYP2C19. Conclusion: In light of the high prevalence of the simultaneous use of PGx drugs with inhibitor and inducer drugs, it is imperative to consider non-genetic factors, such as drug-induced phenoconversions, when interpreting PGx test results.
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