Page 161 - Genomic Medicine in Emerging Economies

150 CHAPTER 8: E c o n omic Evaluation and Cost-Effectiveness Analysis

may serve as a comparison tool. In a recent economic evaluation study involv-
ing elderly atrial fibrillation patients undergoing warfarin treatment, it was
shown that not only did 97% of elderly Croatian patients with atrial fibrilla-
tion belonging to the pharmacogenomics-guided group not have any major
complications, compared with 89% in the control group, but, most impor-
tantly, the ICER of the pharmacogenomics-guided versus the control groups
was calculated to be just €31,225/QALY (Mitropoulou et al., 2015). These data
suggest pharmacogenomics-guided warfarin treatment represents a cost-effec-
tive therapy option for the management of elderly patients with atrial fibril-
lation in Croatia, which may very well be the case for the same and other
anticoagulation treatment modalities in neighboring countries.
A review on the global differences among healthcare systems and costs regard-
ing CYP2C9 and VKORC1 genotyping-guided coumarin derivatives treatment
took a closer look at anticoagulant care management and its cost in the United
Kingdom, Sweden, the Netherlands, Greece, Germany, and Austria. As it was
reported, variations between countries were found in the setting of the inter-
national normalized ratio (INR) monitoring and coumarin dosing, the fre-
quency of INR monitoring, and in the prevalence of coumarin use. Differences
were also found in the quality of anticoagulation, in terms of the percentage
of time spent in the target INR range and the rate of complications. Efficacy
and cost-effectiveness of genotyping prior to treatment can be influenced by
the management and quality of anticoagulant care. In countries where anti-
coagulant care is less well organized, there is the highest probability for phar-
macogenomics to be cost-effective. Nevertheless, genotyping might still be a
cost-effective strategy in countries where anticoagulant care is well organized,
as less INR measurements would be required when patients reach a stable dose
early on with genotyping. Genotyping costs and effects should be taken into
full consideration on the basis of data impact, as reported by Meckley et al.
(2010), whose policy model suggested a small clinical benefit for warfarin
pharmacogenomics testing, yet with significant uncertainty in economic value
(Meckley et al., 2010). Because of significant uncertainties regarding important
assumptions in their Markov decision analytic model, Verhoef et al. (2013)
stated that it was too early to conclude whether or not Dutch patients with
atrial fibrillation starting phenprocoumon should be genotyped, even though
pharmacogenetic-guided dosing of phenprocoumon had the potential to
increase health slightly in a cost-effective way. The main factors for this uncer-
tainty were the effectiveness of a pharmacogenetic-guided dosing regimen as
well as the costs of the genetic test. A couple of years later, Verhoef et al. (2015)
investigated the cost-effectiveness of a pharmacogenetic dosing algorithm ver-
sus a clinical dosing algorithm for phenprocoumon and acenocoumarol versus
clinical dosing in the Netherlands. Pharmacogenetic dosing was reported to
increase costs by €33 and QALYs by 0.001, and, as such, improve health only