The Creating an Optimal Warfarin Nomogram (CROWN) Study

Abstract

A significant proportion of warfarin dose variability is explained by variation in the genotypes of the cytochrome P450 CYP2C9 and the vitamin K epoxide reductase complex, VKORC1, enzymes that influence warfarin metabolism and sensitivity, respectively. We sought to develop an optimal pharmacogenetic warfarin dosing algorithm that incorporated clinical and genetic information. We enroled patients initiating warfarin therapy. Genotyping was performed of the VKORC1, -1639G>A, the CYP2C9*2, 430C>T, and the CYP2C9*3, 1075C>A genotypes. The initial warfarin dosing algorithm (Algorithm A) was based upon established clinical practice and published warfarin pharmacogenetic information. Subsequent dosing algorithms (Algorithms B and Algorithm C) were derived from pharmacokinetic / pharmacodynamic (PK/PD) modelling of warfarin dose, international normalised ratio (INR), clinical and genetic factors from patients treated by the preceding algorithm(s). The primary outcome was the time in the therapeutic range, considered an INR of 1.8 to 3.2. A total of 344 subjects are included in the study analyses. The mean percentage time within the therapeutic range for each subject increased progressively from Algorithm A to Algorithm C from 58.9 (22.0), to 59.7 (23.0), to 65.8 (16.9) percent (p = 0.04). Improvement also occurred in most secondary endpoints, which included the per-patient percentage of INRs outside of the therapeutic range (p = 0.004), the time to the first therapeutic INR (p = 0.07), and the time to achieve stable therapeutic anticoagulation (p < 0.001). In conclusion, warfarin pharmacogenetic dosing can be optimised in real time utilising observed PK/PD information in an adaptive fashion.

Figure 1. CONSORT diagram

A total of 362 subjects enrolled, 4 of which unenrolled prior to any study activity, and 14 of which were excluded because no study drug was administered. Of the 344 remaining subjects, 118 began on algorithm A, 147 on algorithm B, and 79 on algorithm C. If a subject transitioned to a newer algorithm, he was censored at that time.

Figure 2. The number of genetic variants and warfarin stable maintenance dose requirement

The requirement for warfarin declined in a stepwise manner with increasing number of variant alleles, as would be expected.

Figure 3. Accuracy of pharmacogenetic dosing

Shown is the average absolute difference between the algorithm prescribed initial dose and the actual steady-state warfarin dose. In subjects with 0 genetic variants each algorithm had similar accuracy. In subjects with 1 or more genetic variants, the dosing accuracy improved with each algorithm iteration.

Figure 4. Accuracy of pharmacogenetic dosing

Shown is the mean difference between the algorithm-prescribed initial dose and the actual steady-state warfarin dose. Subjects with 0 genetic variants were tended to be under-dosed by the first 2 algorithms and over-dosed by the third. Subjects with 1 variant tended to be over-dosed by all 3 algorithms. Subjects with 2 variants tended to be over-dosed by the first 2 algorithms and appropriately dosed by the third.