Verification of pharmacogenomics-based algorithms to predict warfarin maintenance dose using registered data of Japanese patients.

Large inter-individual differences in warfarin maintenance dose are mostly due to the effect of genetic polymorphisms in multiple genes, including vitamin K epoxide reductase complex 1 (VKORC1), cytochromes P450 2C9 (CYP2C9), and cytochrome P450 4F2 (CYP4F2). Thus, several algorithms for predicting the warfarin dose based on pharmacogenomics data with clinical characteristics have been proposed. Although these algorithms consider these genetic polymorphisms, the formulas have different coefficient values that are critical in this context. In this study, we assessed the mutual validity among these algorithms by specifically considering racial differences. Clinical data including actual warfarin dose (AWD) of 125 Japanese patients from our previous study (Eur J Clin Pharmacol 65(11):1097-1103, 2009) were used as registered data that provided patient characteristics, including age, sex, height, weight, and concomitant medications, as well as the genotypes of CYP2C9 and VKORC1. Genotyping for CYP4F2*3 was performed by the PCR method. Five algorithms that included these factors were selected from peer-reviewed articles. The selection covered four populations, Japanese, Chinese, Caucasian, and African-American, and the International Warfarin Pharmacogenetics Consortium (IWPC). For each algorithm, we calculated individual warfarin doses for 125 subjects and statistically evaluated its performance. The algorithm from the IWPC had the statistically highest correlation with the AWD. Importantly, the calculated warfarin dose (CWD) using the algorithm from African-Americans was less correlated with the AWD as compared to those using the other algorithms. The integration of CYP4F2 data into the algorithm did not improve the prediction accuracy. The racial difference is a critical factor for warfarin dose predictions based on pharmacogenomics.