Abstract

Time-to-event modeling is gaining importance in drug dosage determination, particularly using pharmacometrics approaches. To evaluate the various time-to-event models for estimating the time to achieve a stable warfarin dose in the Bahraini population. A cross-sectional study evaluating the non-genetic and genetic covariates (single nucleotide polymorphisms (SNPs) in CYP2C9, VKORC1 and CYP4F2 genotypes) was conducted in patients receiving warfarin for at least 6 months. Time to achieving a stable dose of warfarin was defined as the duration (in days) from the day of initiating warfarin until 2 consecutive prothrombin time-international normalized ratio (PT-INR) values were observed in the therapeutic range with a gap of at least 7 days. Exponential, Gompertz, log-logistics, and Weibull models were tested, and the model with the lowest objective function value (OFV) was chosen. The covariate selection was carried out using the Wald test and OFV. A hazard ratio (HR) with a 95% confidence interval (95% CI) was estimated. A total of 218 participants were included in the study. The Weibull model was observed to have the lowest OFV (1989.82). The expected time to reach a stable dose in the population was 21.35 days. The CYP2C9 genotypes were identified as the only significant covariate. The HR (95% CI) for achieving a stable warfarin dose within 6 months of initiation for individuals with CYP2C9 *1/*2 was 0.2 (0.09, 0.3), 0.2 (0.1, 0.5) for CYP2C9 *1/*3, 0.14 (0.04, 0.6) for CYP2C9 *2/*2, 0.2 (0.03, 0.9) for CYP2C9 *2/*3, and 0.8 (0.45, 0.9) for those with the C/T genotype for CYP4F2. We estimated the population time-to-event parameters for achieving a stable warfarin dose in our population and observed CYP2C9 genotypes to be the main predictor covariate followed by CYP4F2. The influence of these SNPs needs to be validated in a prospective study and an algorithm to predict a stable warfarin dose and the time to achieve it needs to be developed.

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