Summary
Pharmacogenetic (PG) dosing algorithms have been confirmed to predict warfarin therapeutic
dose more accurately;however, most of them are based on standard intensity of warfarin
anticoagulation, and their utility outside this range is limited. This study was designed
to develop and validate a PG refinement algorithm in Chinese patients mainly under
low-intensity warfarin anticoagulation. Consented Chinese-Han patients (n=310) under
stable warfarin treatment were randomly divided into a derivation (n=207) and a validation
cohort (n=103), with 83% and 80% of the patients under low-intensity anticoagulation,
respectively. In the derivation cohort, a PG algorithm was constructed on the basis
of genotypes (CYP2C9*3 and VKORC1–1639A/G) and clinical data. After integrating additional covariates of
international normalised ratio (INR) values (INR on day 4 of therapy and target INR)
and genotype of CYP4F2 (rs2108622), a PG refinement algorithm was established and
explained 54% of warfarin dose variability. In the validation cohort, warfarin dose
prediction was more accurate (p <0.01) with the PG refinement algorithm than with
the PG algorithm and the fixed dose approach (3 mg/day). In the entire cohort, the
PG refinement algorithm could accurately identify larger proportions of patients with
lower dose requirement (≤2 mg/day) and higher dose requirement (≥4 mg/day) than did
the PG algorithm. In conclusion, PG refinement algorithm integrating early INR response
and three genotypes CYP2C9*3, VKORC1–1639A/G, CYP4F2 rs2108622) improves the accuracy of warfarin dose prediction
in Chinese patients mainly under low-intensity anticoagulation.
Keywords
Warfarin - pharmacogenetics - dosing algorithm - low-intensity anticoagulation