Loading and maintenance dose algorithms for phenprocoumon and acenocoumarol using patient characteristics and pharmacogenetic data

Aims Polymorphisms in CYP2C9 and VKORC1 influence patients' phenprocoumon (PHE) and acenocoumarol (ACE) dose requirements. To provide physicians with tools to estimate the patient's individual dose, we aimed to develop algorithms for PHE and ACE. Methods and results In two Dutch anticoagulation clinics, data on age, sex, height, weight, co-medication, coumarin derivative doses, and international normalized ratio values were obtained from 624 patients taking PHE and 471 taking ACE. Single nucleotide polymorphisms relevant to coumarin derivative dosing on the CYP2C9 and VKORC1 genes were determined. Using multiple linear regression, we developed genotype-guided and non-genotype-guided algorithms to predict the maintenance dose with patient characteristics and genetic information. In addition, loading doses were derived from the calculated maintenance doses. We performed external validation in an independent data set with 229 PHE and 168 ACE users. CYP2C9 and VKORC1 genotype, weight, height, sex, age, and amiodarone use contributed to the maintenance dose of PHE and ACE. The genotype-guided algorithms explained 55.9% (PHE) and 52.6% (ACE) of the variance of the maintenance dose, the non-genetic algorithms 17.3% (PHE) and 23.7% (ACE). Validation in an independent data set resulted in an explained variation of 59.4% (PHE) and 49.0% (ACE) for the genotype-guided algorithms and for 23.5% (PHE) and 17.8% (ACE) for the non-genotype-guided algorithms, without height and weight as parameters. Conclusion To our knowledge, these are the first genotype-guided loading and maintenance dose algorithms for PHE and ACE using large cohorts. The utility of these algorithms will be tested in randomized controlled trials.