Vasilios Fragoulakis

Economic evaluation of pharmacogenomic-guided warfarin treatment for elderly Croatian atrial fibrillation patients with ischemic stroke.

BACKGROUND & METHODS Economic evaluation in genomic medicine is an emerging discipline to assess the cost-effectiveness of genome-guided treatment. Here, we developed a pharmaco-economic model to assess whether pharmacogenomic (PGx)-guided warfarin treatment of elderly ischemic stroke patients with atrial fibrillation in Croatia is cost effective compared with non-PGx therapy. The time horizon of the model was set at 1 year. RESULTS Our primary analysis indicates that 97.07% (95% CI: 94.08-99.34%) of patients belonging to the PGx-guided group have not had any major complications, compared with the control group (89.12%; 95% CI: 84.00-93.87%, p < 0.05). The total cost per patient was estimated at €538.7 (95% CI: €526.3-551.2) for the PGx-guided group versus €219.7 (95% CI: €137.9-304.2) for the control group. In terms of quality-adjusted life-years (QALYs) gained, total QALYs was estimated at 0.954 (95% CI: 0.943-0.964) and 0.944 (95% CI: 0.931-0.956) for the PGx-guided and the control groups, respectively. The true difference in QALYs was estimated at 0.01 (95% CI: 0.005-0.015) in favor of the PGx-guided group. The incremental cost-effectiveness ratio of the PGx-guided versus the control groups was estimated at €31,225/QALY. CONCLUSION Overall, our data indicate that PGx-guided warfarin treatment may represent a cost-effective therapy option for the management of elderly patients with atrial fibrillation who developed ischemic stroke in Croatia.

Economic Evaluation and Genomic Medicine: What Can They Learn from Each Other?

Health economics uses various economic evaluation tools to evaluate medical interventions. The most commonly used types of analyses are cost-effectiveness analyses, cost–utility analyses, cost-minimization analyses, cost–benefit analyses, and cost-threshold analyses. All these approaches consider the cost of the medical intervention itself together with the accompanying costs, but they differ in how they measure the outcome or utility of an intervention. This chapter outlines the application of economic evaluation in genomic medicine, which is not so different from other aspects of medicine. However, there are still some important elements that should be taken into consideration during the various stages of economic evaluation in genomic medicine. Such elements are mostly the type of genomic data and the various ethical, legal, and social issues that pertain to these data. This chapter uses the example of warfarin pharmacogenomics to demonstrate how economic evaluation can be implemented in genomic medicine and projects the application of economic evaluation in the postgenomic era, where next-generation sequence analysis will become an integral part of genomic medicine applications.

Economic analysis of pharmacogenomic-guided clopidogrel treatment in Serbian patients with myocardial infarction undergoing primary percutaneous coronary intervention

INTRODUCTION Clopidogrel, which is activated by the CYP2C19 enzyme, is among the drugs for which all major regulatory agencies recommend genetic testing to be performed to identify a patients CYP2C19 genotype in order to determine the optimal antiplatelet therapeutic scheme. The CYP2C19*2 and CYP2C19*3 variants are loss-of-function alleles, leading to abolished CYP2C19 function and thus have the risk of thrombotic events for carriers of these alleles on standard dosages, while the CYP2C19*17 allele results in CYP2C19 hyperactivity. AIMS Here, we report our findings from a retrospective study to assess whether genotyping for the CYP2C19*2 allele was cost effective for myocardial infarction patients receiving clopidogrel treatment in the Serbian population compared with the nongenotype-guided treatment. RESULTS We found that 59.3% of the CYP2C19*1/*1 patients had a minor or major bleeding event versus 42.85% of the CYP2C19*1/*2 and *2/*2, while a reinfarction event occurred only in 2.3% of the CYP21C9*1/*1 patients, compared with 11.2% of the CYP2C19*1/*2 and CYP2C19*2/*2 patients. There were subtle differences between the two patient groups, as far as the duration of hospitalization and rehabilitation is concerned, in favor of the CYP2C19*1/*1 group. The mean cost for the CYP2C19*1/*1 patients was estimated at €2547 versus €2799 in the CYP2C19*1/*2 and CYP2C19*2/*2 patients. Furthermore, based on the overall CYP2C19*1/*2 genotype frequencies in the Serbian population, a break-even point analysis indicated that performing the genetic test prior to drug prescription represents a cost-saving option, saving €13 per person on average. CONCLUSION Overall, our data demonstrate that pharmacogenomics-guided clopidogrel treatment may represent a cost-saving approach for the management of myocardial infarction patients undergoing primary percutaneous coronary intervention in Serbia.

Chapter 5 – Advanced Methodological Aspects in the Economic Evaluation

The key methodological issues involved in the economic evaluation of health services are described in this chapter. These include the various model types using either patient data or models that are created to simulate the course of the disease with data from the literature or decision trees that constitute the most basic form of a model. Also, for economic evaluation, the effectiveness of each medical intervention should be accurately and reliably estimated, which relies on various sources, data collection, and calculations. In this case, the best known source is a clinical trial, whereas other data sources are meta-analyses, databases, and medical records. The study perspective is also a key factor when determining the cost categories that will ultimately be involved in the analysis. In this case, the approach differs depending on the purpose of the analysis and involves direct, indirect, and invisible intangible costs. A fundamental parameter in economic evaluation is sensitivity analysis, which estimates the effect that different parameters of an independent variable have on the analysis’ end results. Overall, these issues are readily applicable in genomic medicine interventions, particularly those that are readily applicable into clinical practice.

Economic Evaluation in the Genomic Era: Some Examples from the Field

This chapter presents examples of cost-effectiveness analyses for genomic medicine interventions. The examples are selected to illustrate the theoretical concepts presented in the prior chapters to demonstrate the importance of these concepts when applied to real-world scenarios. The importance of setting, the balance between safety and efficacy, indication for the intervention, perspective of the analysis, test performance characteristics, population differences, and the use of analyses in the developing world are presented. Genomic cost-effectiveness analysis has the potential to inform assessments about the value of current and emerging technologies, prioritize value-based decisions about adoption and investment, close evidence gaps, target areas of greatest need and potential health and cost impact, and provide information and guidance for decision-making and policy-making.

Introduction to the Technical Issues of Economic Evaluation

The idea of comparative evaluation of alternative therapeutic interventions is fundamental in economics and is related to the way in which economists assess the value of the relevant options. Economic evaluation is a standard approach to the problem of evaluating alternative interventions through their opportunity cost; cost-effectiveness analysis constitutes a major part of economic evaluation, allowing comparisons between different therapeutic interventions to be made. As such, based on this analysis, the health care systems can allocate the limited resources to be used effectively based on optimization behaviors grounded in the tenets of economics. This chapter gives a background for the application of economic evaluation in health technologies. We list the basic principles and tenets of this method to determine how health economists evaluate different options to maximize the population’s level of health using limited available resources.

Economic Evaluation in Health Care: Evidence-Based Medicine and Evidence-Based Health Economics

The field of economic evaluation of health services deals with the systematic evaluation of the costs and benefits arising from the comparison of different treatments and health technologies. Such evaluations are based on a thorough and accurate comparison of the alternative treatments and/or technologies to identify those that maximize the welfare of the society in general or of specific patient groups. Also, economic evaluation attempts to link evidence-based medicine to the wishes of the patients and society in general, and aims to achieve viability, societal fairness, and improved efficiency in the health care system. This approach is known as evidence-based health economics. Economic evaluation does not aim to restrict health care expenditures, particularly because in certain cases health care expenditures are increased when this is financially or socially acceptable, but rather aims to rationalize the distribution of the available resources such that the highest possible level of population health based on certain societal criteria is achieved. As such, it can be considered more of a guideline for a systematic way of thinking rather than a set of quantification methods to determine the various therapeutic options to which a health care system should direct its resources. Overall, economic evaluation of health services is useful not only to economists but also to clinical scientists and, most importantly, policymakers, to inform them about the available treatment options and the consequences of adopting them for the health and the health care expenditures of the country.

A New Methodological Approach for Cost-Effectiveness Analysis in Genomic Medicine

In this chapter, we introduce illustratively the decision-making process of the classical theory with a new model and a new methodological concept of cost-effectiveness analysis in genomic medicine. The proposed model combines the cost-effectiveness analysis, budget impact analysis, and social preferences while relaxing the assumption that willingness to pay (λ) is indifferent of the actual difference in effectiveness between interventions. This rational provides a practical guide by which policymakers could ensure the sustainability of funding given the restriction of budget.

Chapter 2 – Genomic Medicine Today: An Introduction for Health Economists

Genomic medicine aims to exploit an individual’s genomic make-up for a better prediction of response to medications and adverse drug reactions and to diagnose and prognose inherited pathogenic conditions. To be successfully implemented, genomic medicine must take full advantage of the various genetic, phenotypic, and environmental factors to provide the health care system with useful tools that can optimize the effectiveness of specific treatment. To date, although the anticipated impact of genomic medicine is potentially high and the pace of discoveries from genomics research is equally high, there are often difficulties in the translation of these findings into clinical practice. In this chapter, we summarize the most relevant applications of pharmacogenomics and genomic medicine in clinical practice and discuss the opportunities and shortcomings of the implementation of genetic information in personalized medicine and its full adoption in the clinic. In the latter case, we aim to provide readers with different expertise and an accessible key of interpretation to the barriers and opportunities regarding the use/adoption of genomic medicine in different clinical areas.

Special Requirements for Economic Evaluation and Health Technology Assessment in Genomic Medicine

Economic evaluations of genomic technologies present a particular challenge for health economists. This chapter summarizes the key methodological challenges and special requirements of economic evaluation and health technology assessment for genomic medicine. Special provisions should be made to accurately model the evaluation of the genomic analysis costs and resource use, the analysis method itself, the analysis outcomes, and the effectiveness of the analysis. To this end, new methods and economic models may be required to resolve these issues, which would still require enough evidence to justify such alternative approaches. This should be the focus of future work in this field that, if successful, could accelerate the pace of translating genomics research findings into genomic medical practice.