ArticleScientific reports2019
Clinical Model for Predicting Warfarin Sensitivity.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 18 citations in OpenAlex.
- Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method.Scientific reports · 2024Article
- Warfarin sensitivity is associated with increased hospital mortality in critically Ill patients.PloS one · 2022Article
- Personalized medicine in cardiovascular disease: review of literature.Journal of diabetes and metabolic disorders · 2021Review
- Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose.PloS one · 2018Article
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Warfarin is a widely used anticoagulant with a narrow therapeutic index and large interpatient variability in the therapeutic dose. Complications from inappropriate warfarin dosing are one of the most common reasons for emergency room visits. Approximately one third of warfarin dose variability results from common genetic variants. Therefore, it is very necessary to recognize warfarin sensitivity in individuals caused by genetic variants. Based on combined polymorphisms in CYP2C9 and VKORC1, we established a clinical classification for warfarin sensitivity. In the International Warfarin Pharmacogenetic Consortium (IWPC) with 5542 patients, we found that 95.1% of the Black in the IWPC cohort were normal warfarin responders, while 74.8% of the Asian were warfarin sensitive (P < 0.001). Moreover, we created a clinical algorithm to predict warfarin sensitivity in individual patients using logistic regression. Compared to a fixed-dose approach, the clinical algorithm provided significantly better performance. In addition, we validated the derived clinical algorithm using the external Easton cohort with 106 chronic warfarin users. The AUC was 0.836 vs. 0.867 for the Easton cohort and the IWPC cohort, respectively. With the use of this algorithm, it is very likely to facilitate patient care regarding warfarin therapy, thereby improving clinical outcomes.
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