Warfarin Dose Model for the Prediction of Stable Maintenance Dose in Indian Patients

Abstract

The main aim of this study was to screen various genetic and nongenetic factors that are known to alter warfarin response and to generate a model to predict stable warfarin maintenance dose for Indian patients. The study comprised of 300 warfarin-treated patients. Followed by extensive literature review, 10 single-nucleotide polymorphisms, that is, VKORC1-1639 G>A (rs9923231), CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), FVII R353Q (rs6046), GGCX 12970 C>G (rs11676382), CALU c.*4A>G (rs1043550), EPHX1 c.337T>C (rs1051740), GGCX: c.214+597G>A (rs12714145), GGCX: 8016G>A (rs699664), and CYP4F2 V433M (rs2108622), and 5 nongenetic factors, that is, age, gender, smoking, alcoholism, and diet, were selected to find their association with warfarin response. The univariate analysis was carried out for 15 variables (10 genetic and 5 nongenetic). Five variables, that is, VKORC1-1639 G>A, CYP2C9*2, CYP2C9*3, age, and diet, were found to be significantly associated with warfarin response in univariate analysis. These 5 variables were entered in stepwise and multiple regression analysis to generate a prediction model for stable warfarin maintenance dose. The generated model scored R of .67, which indicates that this model can explain 67% of warfarin dose variability. The generated model will help in prescribing more accurate warfarin maintenance dosing in Indian patients and will also help in minimizing warfarin-induced adverse drug reactions and a better quality of life in these patients.

Association between genetic polymorphisms of CYP2C9 and VKORC1 and safety and efficacy of warfarin: Results of a 5 years audit

“…This could be explained by the presence of confounders and the study design being a retrospective audit without any scope for follow-up. On the other hand, a controlled prospective study by Gaikwad et al 29 in western Indian patients on warfarin demonstrated that five variables ( VKORC1 –1639 G>A, CYP2C9 *2, CYP2C9 *3, age, and diet) were significantly associated with warfarin response in an univariate analysis. After stepwise multiple regression analysis with these five variables, the developed prediction model was found to be explaining approximately 67% of warfarin dose variability (R 2 = 0.67).…”

Height, VKORC1 1173, and CYP2C9 Genotypes Determine Warfarin Dose for Pediatric Patients with Kawasaki Disease in Southwest China

“…To evaluate the effects of food, we compared warfarin dosages between children partly receiving milk powder and those with normal diet, and found the former required lower doses than the latter (1.203 ± 0.439 mg vs. 1.957 ± 0.769 mg, P = 0.004); however, the former cases were all infants. A study of 300 adults showed vegetarian or accidentally nonvegetarian patients intake lower warfarin doses than non-vegetarians [ 17 ]. Besides, diverse warfarin indications require different daily doses.…”

Warfarin: The End or the End of One Size Fits All Therapy?

“…The algorithms also predict extreme doses less efficiently (i.e., low or high daily warfarin doses) [ 15 , 24 ]. Algorithms designed for African-American, Indian, and Chinese patients have been developed but have not been tested in clinical trials [ 25 , 26 , 27 ].…”