Predicting the warfarin maintenance dose in elderly inpatients at treatment initiation: accuracy of dosing algorithms incorporating or not VKORC1/CYP2C9 genotypes

Background: Initiating warfarin is challenging in frail elderly patients because of low-dose requirements and interindividual variability.

Objectives: We investigated whether incorporating VKORC1 and CYP2C9 genotype information in different models helped to predict the warfarin maintenance dose when added to clinical data and INR values at baseline (Day 0), and during warfarin induction.

Patients: We prospectively enrolled 187 elderly inpatients (mean age, 85.6 years), all starting on warfarin using the same 'geriatric dosing-algorithm' based on the INR value measured on the day after three 4-mg warfarin doses (INR(3)) and on INR(6 ± 1).

Results: On Day 0, the clinical model failed to accurately predict the maintenance dose (R(2) < 0.10). Adding the VKORC1 and CYP2C9 genotypes to the model increased R(2) to 0.31. On Day 3, the INR(3) value was the strongest predictor, completely embedding the VKORC1 genotype, whereas the CYP2C9 genotype remained a significant predictor (model- R(2) 0.55). On Day 6 ± 1, none of the genotypes predicted the maintenance dose. Finally, the simple 'geriatric dosing-algorithm' was the most accurate algorithm on Day 3 (R(2) 0.77) and Day 6 (R(2) 0.81), under-estimating (≥ 1 mg) and over-estimating the dose (≥ 1 mg) in fewer than 10% and 2% of patients, respectively. Clinical models and the 'geriatric dosing-algorithm' were validated on an independent sample.

Conclusions: Before starting warfarin therapy, the VKORC1 genotype is the best predictor of the maintenance dose. Once treatment is started using induction doses tailored for elderly patients, the contribution of VKORC1 and CYP2C9 genotypes in dose refinement is negligible compared with two INR values measured during the first week of treatment.