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Pharmacodynamic Modeling of Warfarin Dosing Algorithm for Cardiovascular Patients in Indonesia: A Tailored Method to
Norisca Aliza Putriana1, Irma Rahayu Latarissa2, Taofik Rusdiana1
1Department of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia.
Purpose:
Warfarin is an anticoagulant drug widely used for treating thromboembolism-related conditions. The main challenge with this drug is the high variability in patients response, which is influenced by both clinical, non-clinical, and genetic factors, such as VKORC1, CYP2C9, and CYP4F2. Therefore, this research aimed to evaluate the impact of clinical and genetic factors on warfarin dose adjustment and to develop a dosing algorithm for patients with cardiovascular disease.
Patients And Methods:
A total of 77 research subjects were selected using consecutive sampling based on the inclusion criteria of cardiac outpatients on warfarin for ≥3 months with PT-INR data, complete medical records, and willingness to participate. Exclusion criteria included vitamin K use and inability to follow up. Patients demographic data and clinical characteristics were collected from medical records. Blood samples were obtained for genetic testing of CYP4F2 rs2108622 (sequencing). Statistical analyses included both bivariate and multivariate analyses (logistic regression) with a significance level set at <0.05.
Results:
Statistical analysis using the Kruskal-Wallis test showed that the CC, CT, and TT genotypes were significantly associated with warfarin dose (p = 0.02). Furthermore, the Mann-Whitney test results showed that gender did not have a significant relationship with warfarin dose (p = 0.16). The Spearman Rank correlation test showed that age (p = 0.02) and BMI (p = 0.03) had significant relationships with warfarin dose (p < 0.05). However, gender (p = 0.89) had no effect, while age (p = 0.01), BMI (p = 0.01), and genotype (p = 0.01) significantly influenced warfarin dose determination.
Conclusion:
In conclusion, the combined contribution of age (8.76%), BMI (7.95%), and CYP4F2 genotype (8.29%) to warfarin dose adjustment was 25%. The linear regression model for predicting warfarin dose was determined to be y = 12.736-0.16*age + 0.55*BMI + 3.55*genotype, where 1 = CC, 2 = CT, and 3 = TT.
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