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Journal article
Clinical Model for Predicting Warfarin Sensitivity
Scientific reports, v 9(1), 12856
06 Sep 2019
PMID: 31492893
Featured in Collection : UN Sustainable Development Goals @ Drexel
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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Details
- Title
- Clinical Model for Predicting Warfarin Sensitivity
- Creators
- Zhiyuan Ma - Easton Cardiovascular Associates, Easton, PA, USA.Gang Cheng - Easton HospitalPing Wang - Duke UniversityBahar Khalighi - Temple UniversityKoroush Khalighi - Easton Cardiovascular Associates, Easton, USA
- Publication Details
- Scientific reports, v 9(1), 12856
- Publisher
- Springer Nature
- Number of pages
- 9
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Medicine (Graduate)
- Web of Science ID
- WOS:000484656700044
- Scopus ID
- 2-s2.0-85071896868
- Other Identifier
- 991019168291704721
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Pharmacology & Pharmacy