Background

Warfarin is commonly prescribed for prophylaxis and treatment of thromboembolism after orthopedic surgery. During warfarin initiation, out-of-range International Normalized Ratio (INR) values and adverse events are common.

Methods

In orthopedic patients beginning warfarin therapy, we developed and prospectively validated pharmacogenetic and clinical dose refinement algorithms to revise the estimated therapeutic dose after 4 days of therapy.

Results

The pharmacogenetic algorithm used the cytochrome P450 (CYP) 2C9 genotype, smoking status, perioperative blood loss, liver disease, INR values, and dose history to predict the therapeutic dose. The R2 was 82% in a derivation cohort (N = 86), and 70% when used prospectively (N = 146). The R2 of the clinical algorithm that used INR values and dose history to predict the therapeutic dose was 57% in a derivation cohort (N = 178), and 48% in a prospective validation cohort (N = 146). In one month of prospective follow-up, the percent time spent in the therapeutic range was 7% higher (95% CI: 2.7%–11.7%) in the pharmacogenetic cohort. The risk of laboratory or clinical adverse event was also significantly reduced in the pharmacogenetic cohort (Hazard Ratio 0.54; 95% CI: 0.29–0.97).

Conclusions

Warfarin dose adjustments that incorporate genotype and clinical variables available after four warfarin doses are accurate. In this non-randomized, prospective study, pharmacogenetic dose refinements were associated with more time spent in the therapeutic range and fewer laboratory or clinical adverse events. To facilitate gene-guided warfarin dosing we created a non-profit website, www.WarfarinDosing.org.

Summary

Introduction

By guiding initial warfarin dose, pharmacogenetic (PGx) algorithms may improve the safety of warfarin initiation. However, once INR response is known, the contribution of PGx to dose refinements is uncertain. This study sought to develop and validate clinical and PGx dosing algorithms for warfarin dose refinement on days 6–11 after therapy initiation.

Materials and Methods

An international sample of 2,022 patients at 13 medical centers on 3 continents provided clinical, INR, and genetic data at treatment days 6–11 to predict therapeutic warfarin dose. Independent derivation and retrospective validation samples were composed by randomly dividing the population (80%/20%). Prior warfarin doses were weighted by their expected effect on S-warfarin concentrations using an exponential-decay pharmacokinetic model. The INR divided by that “effective” dose constituted a treatment response index.

Results

Treatment response index, age, amiodarone, body surface area, warfarin indication, and target INR were associated with dose in the derivation sample. A clinical algorithm based on these factors was remarkably accurate: in the retrospective validation cohort its R2 was 61.2% and median absolute error (MAE) was 5.0 mg/week. Accuracy and safety was confirmed in a prospective cohort (N=43). CYP2C9 variants and VKORC1-1639 G→A were significant dose predictors in both the derivation and validation samples. In the retrospective validation cohort, the PGx algorithm had: R2= 69.1% (P<0.05 vs. clinical algorithm), MAE= 4.7 mg/week.

Conclusions

A pharmacogenetic warfarin dose-refinement algorithm based on clinical, INR, and genetic factors can explain at least 69.1% of therapeutic warfarin dose variability after about one week of therapy.