Cost-effectiveness of pharmacogenetics-guided warfarin therapy vs. alternative anticoagulation in atrial fibrillation

Methods for Economic Evaluations of Novel Oral Anticoagulants in Patients with Atrial Fibrillation: A Systematic Review

BACKGROUND

Atrial fibrillation (AF) is a severe epidemiological and public health concern among the elderly population worldwide, with substantial economic and social burdens. Economic evaluations can play an essential role in optimizing the utilization of scarce resources. In recent years, the number of economic evaluation studies related to AF has increased due to the rising number of AF patients, the continuous updating of clinical data, and the emergence of real-world evidence. However, there are still deficiencies in model settings and parameter sources in relevant studies.

OBJECTIVE

This study aims to review the existing economic evaluations of novel oral anticoagulants (NOACs) in patients with AF and summarize the evidence and methods applied.

METHODS

A comprehensive and systematic search was conducted on electronic databases, including PubMed, Embase, Web of Science (WOS), and The Cochrane Library, from the date of database creation to November 2022. The reporting quality of included literature was assessed using the Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement.

RESULTS

A total of 102 studies were included in the review, with 200 comparisons between NOACs and vitamin K antagonists (VKAs), as well as 58 comparisons between different NOACs. The healthcare sector and payer perspectives were the most common, and accordingly, the majority of the evaluations considered only direct medical costs. Most studies used Markov cohort models with the number of health states ranging from 4 to 29. Of included studies, 80 (78%) considered event recurrence and complications, and 78 (76%) considered discontinuation and second-line therapy. All of the studies applied uncertainty analysis to explore the robustness of the results. Of all 200 NOACs-VKAs comparisons, 149 (75%) showed that NOACs were more cost-effective; this proportion was 84% (139 out of 165) in high-income countries but decreased to 29% (10 out of 35) in middle- and low-income countries. Most (82%) of the 28 items in the CHEERS 2022 checklist were elucidated in the majority of included studies. A minority (only 39%) of included studies demonstrated high reporting quality.

CONCLUSION

NOACs may be more cost-effective than VKAs in patients with AF, but this conclusion applies to high-income countries, whereas VKAs may be more cost-effective in middle- and low-income countries. The reporting quality of included studies was variable, and certain methodological issues were presented. This study highlights the economic evaluation methodology of NOACs in patients with AF and provides recommendations for modeling methods and future studies.

Assessing the utility of measurement methods applied in economic evaluations of pharmacogenomics applications

An increasing number of economic evaluations are published annually investigating the economic effectiveness of pharmacogenomic (PGx) testing. This work was designed to provide a comprehensive summary of the available utility methods used in cost-effectiveness/cost-utility analysis studies of PGx interventions. A comprehensive review was conducted to identify economic analysis studies using a utility valuation method for PGx testing. A total of 82 studies met the inclusion criteria. A majority of studies were from the USA and used the EuroQol-5D questionnaire, as the utility valuation method. Cardiovascular disorders was the most studied therapeutic area while discrete-choice studies mainly focused on patients' willingness to undergo PGx testing. Future research in applying other methodologies in PGx economic evaluation studies would improve the current research environment and provide better results.

Cost-Effectiveness of Direct Oral Anticoagulants in Patients With Nonvalvular Atrial Fibrillation in Hong Kong

OBJECTIVES

The emergence of direct oral anticoagulants (DOACs) has revolutionized the prevention of stroke related to nonvalvular atrial fibrillation (NVAF). Several DOACs are available on the market, while the cost-effectiveness comparison among DOACs and vitamin K antagonist (warfarin) in NVAF management in Hong Kong market remains scarce. The objective of this study was to assess the cost-effectiveness of DOACs and warfarin from a Hong Kong public institutional perspective to inform formulary listing decisions.

METHODS

A previously developed Markov model was adapted to simulate the lifetime disease progression of a hypothetical cohort of 1000 patients. Net monetary costs, quality-adjusted life-year (QALY), and incremental cost-effectiveness ratio were computed for the following competing alternatives: warfarin, apixaban (5 mg twice daily), dabigatran (110 mg or 150 mg twice daily), and rivaroxaban (20 mg once daily). Probabilistic sensitivity analyses were conducted to address study uncertainties.

RESULTS

In base-case results, all DOACs were associated with greater QALYs improvements and lower costs than warfarin. Rivaroxaban, apixaban, dabigatran 150 mg, dabigatran 110 mg, and warfarin resulted in net costs US dollar (USD) 8088, USD 8240, USD 8566, USD 8653, and USD 16 363 and net QALY 5.87, 6.017, 6.022, 5.98, and 5.829, respectively. In probabilistic sensitivity analysis, the probabilities of warfarin, rivaroxaban 20 mg, dabigatran 110 mg, dabigatran 150 mg, and apixaban 5 mg being cost-effective of 2000 iterations were 0%, 0%, 29.4%, 33.2%, and 37.4%, respectively.

CONCLUSION

Apixaban was the most cost-effective option compared with other DOACs and warfarin in the management of NVAF; this conclusion is consistent under all the tested uncertainty scenarios.

Pharmacogenetics of warfarin and healthcare costs - Real-world data analysis

PURPOSE

Variants in CYP2C9 and VKORC1 genes have been associated with individuals' sensitivity to warfarin. The aim of this study was to investigate the differences of healthcare costs of genetically normal and genetically sensitive warfarin responder groups.

METHODS

This was a retrospective study linking genotype data from three Finnish biobanks (THL Biobank, Auria Biobank, Helsinki Biobank) with healthcare encounter data of the Finnish Institute of Health and Welfare (THL), drug dispensation data from the Social Insurance Institution of Finland (Kela) and laboratory data from Finnish hospital districts and municipalities. We compared the normal and sensitive warfarin responder groups in terms of healthcare costs related to bleeding and thromboembolic events, INR tests and medication purchases.

RESULTS

We found a trend towards increased bleeding-related hospital costs in the sensitive warfarin responder group (881 patients) when compared with the normal responders (1627 patients) with a per patient difference of 150.9 €/year (95% CI: -55.1, 414.6 €/year, p = 0.087). INR test costs were higher in the sensitive responder group with a difference of 7.2 €/year (95% CI: -1.5, 16.4 €/year, p = 0.047). Medication costs were significantly lower in the sensitive responder group with a difference of -14.4 €/year (95% CI: -15.8, -12.9 €/year, p < 0.001).

CONCLUSIONS

The difference in the costs of bleeding-related hospitalization between genetically sensitive and normal warfarin responders may justify genotype-guided warfarin dosing. Further studies with larger sample sizes would be needed to verify the result.

Global distribution of functionally important CYP2C9 alleles and their inferred metabolic consequences

BACKGROUND

Genetic variability in the cytochrome P450 CYP2C9 constitutes an important predictor for efficacy and safety of various commonly prescribed drugs, including coumarin anticoagulants, phenytoin and multiple non-steroidal anti-inflammatory drugs (NSAIDs). A global map of CYP2C9 variability and its inferred functional consequences has been lacking.

RESULTS

Frequencies of eight functionally relevant CYP2C9 alleles (*2, *3, *5, *6, *8, *11, *13 and *14) were analyzed. In total, 108 original articles were identified that included genotype data from a total of 81,662 unrelated individuals across 70 countries and 40 unique ethnic groups. The results revealed that CYP2C9*2 was most abundant in Europe and the Middle East, whereas CYP2C9*3 was the main reason for reduced CYP2C9 activity across South Asia. Our data show extensive variation within superpopulations with up to tenfold differences between geographically adjacent populations in Malaysia, Thailand and Vietnam. Translation of genetic CYP2C9 variability into functional consequences indicates that up to 40% of patients in Southern Europe and the Middle East might benefit from warfarin and phenytoin dose reductions, while 3% of patients in Southern Europe and Israel are recommended to reduce starting doses of NSAIDs.

CONCLUSIONS

This study provides a comprehensive map of the genetic and functional variability of CYP2C9 with high ethnogeographic resolution. The presented data can serve as a useful resource for CYP2C9 allele and phenotype frequencies and might guide the optimization of genotyping strategies, particularly for indigenous and founder populations with distinct genetic profiles.

Automated warfarin dose prediction for Asian, American, and Caucasian populations using a deep neural network

Existing warfarin dose prediction algorithms based on pharmacogenetics and clinical parameters have not been used clinically due to the absence of external validation, lack of assessment for clinical utility, and high risk of bias. Moreover, given the high degree of heterogeneity across different datasets used to develop these algorithms, it is unsurprising that prediction errors remain high, and dosing accuracy is dependent on specific ethnic populations. To circumvent these challenges, deep neural models are increasingly used to improve the precision and accuracy of warfarin dose predictions. Hence, this study sought to develop a deep learning-based model using a well-established curated dataset of over 6000 patients from the International Warfarin Pharmacogenomics Consortium (IWPC). Clinically-relevant input data such as physical attributes, medical conditions, concomitant medications, genotype status of functional warfarin genetic polymorphisms, and therapeutic INR were entered followed by applying a unique and robust training and validation method. The deep model yielded a low average mean absolute error (MAE) of 7.6 mg/week and a relatively low mean percentage of error of 40.9% in Asians, 14.2 mg/week MAE and 36.9% in African Americans, and 12.7 mg/week MAE and 45.4% mean percentage of error in White Caucasians. This model also resulted in 36.4% of all patients with a predicted dose within 20% of the administered dose. Hence, our proposed deep model provides an alternative to predicting warfarin dose in the clinical setting upon validation in ethnically-similar datasets.

Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.

Cost Effectiveness of Pharmacogenetic Testing for Drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines: A Systematic Review

The objective of this study was to evaluate the evidence on cost-effectiveness of pharmacogenetic (PGx)-guided treatment for drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A systematic review was conducted using multiple biomedical literature databases from inception to June 2021. Full articles comparing PGx-guided with nonguided treatment were included for data extraction. Quality of Health Economic Studies (QHES) was used to assess robustness of each study (0-100). Data are reported using descriptive statistics. Of 108 studies evaluating 39 drugs, 77 (71%) showed PGx testing was cost-effective (CE) (N = 48) or cost-saving (CS) (N = 29); 21 (20%) were not CE; 10 (9%) were uncertain. Clopidogrel had the most articles (N = 23), of which 22 demonstrated CE or CS, followed by warfarin (N = 16), of which 7 demonstrated CE or CS. Of 26 studies evaluating human leukocyte antigen (HLA) testing for abacavir (N = 8), allopurinol (N = 10), or carbamazepine/phenytoin (N = 8), 15 demonstrated CE or CS. Nine of 11 antidepressant articles demonstrated CE or CS. The median QHES score reflected high-quality studies (91; range 48-100). Most studies evaluating cost-effectiveness favored PGx testing. Limited data exist on cost-effectiveness of preemptive and multigene testing across disease states.

Impact of comparative effectiveness research on Medicare coverage of direct oral anticoagulants

Aim: To evaluate the association of comparative effectiveness research with Medicare coverage of direct oral anticoagulants. Materials & methods: A literature review for direct oral anticoagulants was conducted from 2011 to 2017. Monthly prescription drug plan and formulary files (n = 28) were used to conduct change-point analysis and assess each outcome variable. Results: Up to 2013, studies showed that dabigatran was more effective than rivaroxaban. In 2015, apixaban was shown to be the safest and most effective drug in comparison with all direct oral anticoagulants. In 2016-2017, dabigatran and apixaban were shown to have similar efficacy. Approximately 75% of plans covered dabigatran under tier 3 until 2015. From 2011 to 2017, less than 30% of plans required prior authorizations, 50% imposed quantity limits and mean copayment was lowest for rivaroxaban. Conclusion: Consistent with comparative effectiveness research, Medicare plans covered apixaban more favorably and edoxaban less favorably. However, discrepancies in comparative effectiveness research translation were found for rivaroxaban and dabigatran.

Economic evaluation of direct oral anticoagulants (DOACs) versus vitamin K antagonists (VKAs) for stroke prevention in patients with atrial fibrillation: a systematic review and meta-analysis

OBJECTIVES

To assess cost-effectiveness of direct oral anticoagulants (DOACs) compared with vitamin K antagonists (VKAs) for stroke prevention in atrial fibrillation (AF) by pooling incremental net benefits (INBs).

DESIGN

Systematic review and meta-analysis.

SETTING

We searched PubMed, Scopus and Centre for Evaluation of Value and Risks in Health Registry from inception to December 2019.

PARTICIPANTS

Patients with AF.

MAIN OUTCOME MEASURES

The INB was defined as a difference of incremental effectiveness multiplied by willing to pay threshold minus the incremental cost; a positive INB indicated favour treatment. These INBs were pooled (stratified by level of country income, perspective, time-horizon, model types) with a random-effects model if heterogeneity existed, otherwise a fixed effects model was applied. Heterogeneity was assessed using Q test and I² statistic. Risk of bias was assessed using the economic evaluations bias (ECOBIAS) checklist.

RESULTS

A total of 100 eligible economic evaluation studies (224 comparisons) were included. For high-income countries (HICs) from a third-party payer (TPP) perspective, the pooled INBs for DOAC versus VKA pairs were significantly cost-effective with INBs (95% CI) of $6632 ($2961.67 to $10 303.72; I²=59.9%), $6353.24 ($4076.03 to $8630.45; I²=0%), $7664.58 ($2979.79 to $12 349.37; I²=0%) and $8573.07 ($1877.05 to $15 269.09; I²=0%) for dabigatran, apixaban, rivaroxaban and edoxaban relative to VKA, respectively but only dabigatran was significantly cost-effective from societal perspective (SP) with an INB of $11 746.96 ($2429.34 to $21 064.59; I²=52.4%). The pooled INBs of all comparisons for upper-middle income countries (UMICs) were not significantly cost-effective. The ECOBIAS checklist indicated that risk of bias was mostly low for most items with the exception of five items which should be less influenced on pooling INBs.

CONCLUSIONS

Our meta-analysis provides comprehensive economic evidence that allows policy makers to generalise cost-effectiveness data to their local context. All DOACs may be cost-effective compared with VKA in HICs with TPP perspective. The pooling results produced moderate to high heterogeneity particularly in UMICs. Further studies are required to inform UMICs with SP.

PROSPERO REGISTERATION NUMBER

CRD 42019146610.

Genetic-Guided Pharmacotherapy for Atrial Fibrillation: A Systematic and Critical Review of Economic Evaluations

OBJECTIVES

This study aimed to examine the extent and quality of evidence from economic evaluations (EEs) of genetic-guided pharmacotherapy (PGx) for atrial fibrillation (AF) and to identify variables influential in changing base-case conclusions.

METHODS

From systematic searches, we included EEs of existing PGx testing to guide pharmacotherapy for AF, without restrictions on population characteristics or language. Articles excluded were genetic tests used to guide device-based therapy or focused on animals.

RESULTS

We found 18 EEs (46 comparisons), all model-based cost-utility analysis with or without cost-effectiveness analysis mostly from health system's perspectives, of PGx testing to determine coumadin/direct-acting anticoagulant (DOAC) dosing (14 of 18), to stratify patients into coumadin/DOACs (3 of 18), or to increase patients' adherence to coumadin (1 of 18) versus non-PGx. Most PGx to determine coumadin dosing found PGx more costly and more effective than standard or clinical coumadin dosing (19 of 24 comparisons) but less costly and less effective than standard DOAC dosing (14 of 14 comparisons). The remaining comparisons were too few to observe any trend. Of 61 variables influential in changing base-case conclusions, effectiveness of PGx testing was the most common (37%), accounted for in the models using time-based or medication-based approaches or relative risk. The cost of PGx testing has decreased and plateaued over time.

CONCLUSIONS

EEs to date only partially inform decisions on selecting optimal PGx testing for AF, because most evidence focuses on PGx testing to determine coumadin dosing, but less on other purposes. Future EE may refer to the list of influential variables and the approaches used to account for the effect of PGx testing to inform data collection and study design.

Pharmacogenetic testing for adverse drug reaction prevention: systematic review of economic evaluations and the appraisal of quality matters for clinical practice and implementation

Background

Genetic testing has potential roles in identifying whether an individual would have risk of adverse drug reactions (ADRs) from a particular medicine. Robust cost-effectiveness results on genetic testing would be useful for clinical practice and policy decision-making on allocating resources effectively. This study aimed to update a systematic review on economic evaluations of pharmacogenetic testing to prevent ADRs and critically appraise the quality of reporting and sources of evidence for model input parameters.

Methods

We searched studies through Medline via PubMed, Scopus and CRD’s NHS Economic Evaluation up to October 2019. Studies investigating polymorphism-based pharmacogenetic testing, which guided drug therapies to prevent ADRs, using economic evaluation methods were included. Two reviewers independently performed data extraction and assessed the quality of reporting using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines and the quality of data sources using the hierarchy of evidence developed by Cooper et al.

Results

Fifty-nine economic evaluations of pharmacogenetic testing to avoid drug-induced ADRs were found between 2002 and 2018. Cost-utility and cost-effectiveness analyses were the most common methods of economic evaluation of pharmacogenetic testing. Most studies complied with the CHEERS checklist, except for single study-based economic evaluations which did not report uncertainty analysis (78%). There was a lack of high-quality evidence not only for estimating the clinical effectiveness of pharmacogenetic testing, but also baseline clinical data. About 14% of the studies obtained clinical effectiveness data of testing from a meta-analysis of case-control studies with direct comparison, which was not listed in the hierarchy of evidence used.

Conclusions

Our review suggested that future single study-based economic evaluations of pharmacogenetic testing should report uncertainty analysis, as this could significantly affect the robustness of economic evaluation results. A specific ranking system for the quality of evidence is needed for the economic evaluation of pharmacogenetic testing of ADRs. Differences in parameters, methods and outcomes across studies, as well as population-level and system-level differences, may lead to the difficulty of comparing cost-effectiveness results across countries.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07025-8.

Pharmacogenetic-guided glimepiride therapy in type-2 diabetes mellitus: a cost-effectiveness study

The demonstration of the link between certain genetic variations and drug response has allowed the emergence of pharmacogenetics, which offers many opportunities to improve patient care. Type-2 diabetes mellitus is a disease for which several gene polymorphisms have been reported to be associated with drug response. Sulfonylureas are commonly used for the management of this disease. Genetic polymorphisms of CYP2C9, the main enzyme involved in the metabolism of sulfonylureas, have been associated with the risk of severe hypoglycaemia, particularly in poor metabolizers carrying CYP2C9 *3/*3 genotype, and especially in the case of patients treated with glimepiride. The objectives of the present study were to evaluate the potential clinical and economic outcomes of using CYP2C9 genotype data to guide the management of SU regimen in patients initiating glimepiride therapy, and to identify factors affecting the cost-effectiveness of this treatment scheme. The analysis was conducted using a decision tree, considering a 1-year time horizon, and taking as perspective that of the French national health insurance system. With pharmacogenetic-guided therapy, the cost to avoid an episode of severe hypoglycaemia event per 100 000 patients treated was €421 834. Genotyping cost was the most influential factor on the incremental cost-effectiveness ratio. In conclusion, the potential cost of CYP2C9 genotype-guided dosing for glimepiride therapy is relatively high, and associated with modest improvements with respect to the number of hypoglycaemia avoided, as compared with standard dosing. Additional economic studies are required to better specify the usefulness of CYP2C9 genotyping prior to glimepiride regimen initiation.

Economic Impact of the Application of a Precision Medicine Model (5SPM) on Psychotic Patients

BACKGROUND

Schizophrenia is a severe mental disorder that often manifests within the first three decades of life. Its prognosis is uncertain and may result in a prolonged treatment that could extend throughout the entire lifespan of the patient. Antipsychotic drugs are characterized by a high interindividual variability when considering therapeutic effect and emergence of adverse effects. Such interindividual variability is thought to be associated primarily with pharmacokinetic matters.

OBJECTIVE

The objective of this study was to evaluate the economic impact of the application of the 5-Step Precision Medicine model (5SPM), an approach based on the pharmacogenetic analysis of the primary genes involved in the metabolism of the therapy for each patient, restructuring treatment as necessary.

PATIENTS AND METHODS

One hundred eighty-eight psychiatry patients were analysed for single nucleotide polymorphisms on genes CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5 and ABCB1. Information on patients' diagnosis, pharmacotherapy, and hospitalizations was collected.

RESULTS

We achieved a cost-benefit ratio of 3.31-3.59 with a reduction of direct cost (hospitalizations plus pharmacotherapy) with a reduction of total cost in 67% of the patients who underwent the clinical intervention.

CONCLUSION

A rational Precision Medicine-based approach to psychiatric patients could result in a reduction on number of drugs required to control exacerbations, and the underlying pathologies, reducing the risk of adverse effects and improving adherence to treatment, leading to a potential decrease in direct costs. This methodology has been shown to be cost-dominant and, being based on a pharmacogenetic analysis, it has a lifelong nature, as the data obtained can be applied to other medical disciplines.

Warfarin maintenance dose prediction for Chinese after heart valve replacement by a feedforward neural network with equal stratified sampling

Patients requiring low-dose warfarin are more likely to suffer bleeding due to overdose. The goal of this work is to improve the feedforward neural network model's precision in predicting the low maintenance dose for Chinese in the aspect of training data construction. We built the model from a resampled dataset created by equal stratified sampling (maintaining the same sample number in three dose-groups with a total of 3639) and performed internal and external validations. Comparing to the model trained from the raw dataset of 19,060 eligible cases, we improved the low-dose group's ideal prediction percentage from 0.7 to 9.6% and maintained the overall performance (76.4% vs. 75.6%) in external validation. We further built neural network models on single-dose subsets to invest whether the subsets samples were sufficient and whether the selected factors were appropriate. The training set sizes were 1340 and 1478 for the low and high dose subsets; the corresponding ideal prediction percentages were 70.2% and 75.1%. The training set size for the intermediate dose varied and was 1553, 6214, and 12,429; the corresponding ideal prediction percentages were 95.6, 95.1%, and 95.3%. Our conclusion is that equal stratified sampling can be a considerable alternative approach in training data construction to build drug dosing models in the clinic.

Linked Pharmacometric-Pharmacoeconomic Modeling and Simulation in Clinical Drug Development

Market access and pricing of pharmaceuticals are increasingly contingent on the ability to demonstrate comparative effectiveness and cost-effectiveness. As such, it is widely recognized that predictions of the economic potential of drug candidates in development could inform decisions across the product life cycle. This may be challenging when safety and efficacy profiles in terms of the relevant clinical outcomes are unknown or highly uncertain early in product development. Linking pharmacometrics and pharmacoeconomics, such that outputs from pharmacometric models serve as inputs to pharmacoeconomic models, may provide a framework for extrapolating from early-phase studies to predict economic outcomes and characterize decision uncertainty. This article reviews the published studies that have implemented this methodology and used simulation to inform drug development decisions and/or to optimize the use of drug treatments. Some of the key practical issues involved in linking pharmacometrics and pharmacoeconomics, including the choice of final outcome measures, methods of incorporating evidence on comparator treatments, approaches to handling multiple intermediate end points, approaches to quantifying uncertainty, and issues of model validation are also discussed. Finally, we have considered the potential barriers that may have limited the adoption of this methodology and suggest that closer alignment between the disciplines of clinical pharmacology, pharmacometrics, and pharmacoeconomics, may help to realize the potential benefits associated with linked pharmacometric-pharmacoeconomic modeling and simulation.

Incorporating Pharmacometrics into Pharmacoeconomic Models: Applications from Drug Development

Pharmacometrics is the science of quantifying the relationship between the pharmacokinetics and pharmacodynamics of drugs in combination with disease models and trial information to aid in drug development and dosing optimization for clinical practice. Considering the variability in the dose-concentration-effect relationship of drugs, an opportunity exists in linking pharmacokinetic and pharmacodynamic model-based estimates with pharmacoeconomic models. This link may provide early estimates of the cost effectiveness of drug therapies, thus informing late-stage drug development, pricing, and reimbursement decisions. Published case studies have demonstrated how integrated pharmacokinetic-pharmacodynamic-pharmacoeconomic models can complement traditional pharmacoeconomic analyses by identifying the impact of specific patient sub-groups, dose, dosing schedules, and adherence on the cost effectiveness of drugs, thus providing a mechanistic basis to predict the economic value of new drugs. Greater collaboration between the pharmacoeconomics and pharmacometrics community can enable methodological improvements in pharmacokinetic-pharmacodynamic-pharmacoeconomic models to support drug development.

Has the introduction of direct oral anticoagulants (DOACs) in England increased emergency admissions for bleeding conditions? A longitudinal ecological study

OBJECTIVE

There is concern about long-term safety of direct oral coagulants (DOACs) in clinical practice. Our aim was to investigate whether the introduction of DOACs compared with vitamin-K antagonists in England was associated with a change in admissions for bleeding or thromboembolic complications.

SETTING

5508 General practitioner (GP) practices in England between 2011 and 2016.

PARTICIPANTS

All GP practices in England with a registered population size of greater than 1000 that had data for all 6 years.

MAIN OUTCOME MEASURE

The rate of emergency admissions to hospital for bleeding or thromboembolism, per 100 000 population for each GP practice in England.

MAIN EXPOSURE MEASURE

The annual number of DOAC items prescribed for each GP practice population as a proportion of all anticoagulant items prescribed.

DESIGN

This longitudinal ecological study used panel regression models to investigate the association between trends in DOAC prescribing within GP practice populations and trends in emergency admission rates for bleeding and thromboembolic conditions, while controlling for confounders.

RESULTS

For each additional 10% of DOACs prescribed as a proportion of all anticoagulants, there was a 0.9% increase in bleeding complications (rate ratio 1.008 95% CI 1.003 to 1.013). The introduction of DOACs between 2011 and 2016 was associated with additional 4929 (95% CI 2489 to 7370) emergency admissions for bleeding complications. Increased DOAC prescribing was associated with a slight decline in admission for thromboembolic conditions.

CONCLUSION

Our data show that the rapid increase in prescribing of DOACs after changes in National Institute for Health and Care Excellence guidelines in 2014 may have been associated with a higher rate of emergency admissions for bleeding conditions. These consequences need to be considered in assessing the benefits and costs of the widespread use of DOACs.

Influence of metabolic profiles on the safety of drug therapy in routine care in Germany: protocol of the cohort study EMPAR

INTRODUCTION

Pre-emptive testing of pharmacogenetically relevant single-nucleotide polymorphisms can be an effective tool in the prevention of adverse drug reactions and therapy resistance. However, most of the tests are not used as standard in routine care in Germany because of lacking evidence for the clinical and economical benefit and their impact on the usage of healthcare services. We address this issue by investigating the influence of pharmacogenetic profiles on the use of healthcare services over an extended period of several years using routine care data from a statutory health insurance company. The goal is to provide clinical evidence whether pre-emptive pharmacogenetic testing of metabolic profiles in routine care in Germany is beneficial and cost-effective.

METHODS AND ANALYSIS

The EMPAR (Einfluss metabolischer Profile auf die Arzneimitteltherapiesicherheit in der Routineversorgung) study is a non-interventional cohort study conducted to analyse pharmacogenetic risk factors that are important for drug therapy by means of endpoints relevant for healthcare. The analysis is based on pharmacogenetic profiles and statutory health insurance data. We perform pharmacogenetic, pharmacoepidemiological and pharmacoeconomic analyses using health care utilisation scores and machine learning techniques. Therefore, we aim to include about 10 000 patients (≥18 years) insured by the health insurance provider Techniker Krankenkasse. The study focuses on patients with prescriptions of anticoagulants and prescriptions of cholesterol-lowering drugs. Also, a screening for special pharmacogenetic characteristics will be performed in patients with at least one Y57.9! diagnosis (Complication of medical and surgical care: drug or medicament, unspecified). Outcomes include the utilisation of health insurance services, the incidence of incapacity for work and costs for drugs and treatment.

ETHICS AND DISSEMINATION

The protocol was approved by the Ethics Committee of the Medical Faculty, University of Bonn (Lfd. Nr. 339/17). The results of this research project will be published in scientific open access journals and at conferences.

TRIAL REGISTRATION NUMBER

German Clinical Trials Register, DRKS00013909.

Cost-effectiveness of precision medicine: a scoping review

Objectives

Precision medicine (PM) aims to improve patient outcomes by stratifying or individualizing diagnosis and treatment decisions. Previous reviews found inconclusive evidence as to the cost-effectiveness of PM. The purpose of this scoping review was to describe current research findings on the cost-effectiveness of PM and to identify characteristics of cost-effective interventions.

Methods

We searched PubMed with a combination of terms related to PM and economic evaluations and included studies published between 2014 and 2017.

Results

A total of 83 articles were included, of which two-thirds were published in Europe and the USA. The majority of studies concluded that the PM intervention was at least cost-effective compared to usual care. However, the willingness-to-pay thresholds varied widely. Key factors influencing cost-effectiveness included the prevalence of the genetic condition in the target population, costs of genetic testing and companion treatment and the probability of complications or mortality.

Conclusions

This review may help inform decisions about reimbursement, research and development of PM interventions.

Electronic supplementary material

The online version of this article (10.1007/s00038-019-01298-x) contains supplementary material, which is available to authorized users.

Statistical Methods for Adjusting Estimates of Treatment Effectiveness for Patient Nonadherence in the Context of Time-to-Event Outcomes and Health Technology Assessment: A Systematic Review of Methodological Papers

Introduction. Medication nonadherence can have a significant negative impact on treatment effectiveness. Standard intention-to-treat analyses conducted alongside clinical trials do not make adjustments for nonadherence. Several methods have been developed that attempt to estimate what treatment effectiveness would have been in the absence of nonadherence. However, health technology assessment (HTA) needs to consider effectiveness under real-world conditions, where nonadherence levels typically differ from those observed in trials. With this analytical requirement in mind, we conducted a review to identify methods for adjusting estimates of treatment effectiveness in the presence of patient nonadherence to assess their suitability for use in HTA. Methods. A "Comprehensive Pearl Growing" technique, with citation searching and reference checking, was applied across 7 electronic databases to identify methodological papers for adjusting time-to-event outcomes for nonadherence using individual patient data. A narrative synthesis of identified methods was conducted. Methods were assessed in terms of their ability to reestimate effectiveness based on alternative, suboptimal adherence levels. Results. Twenty relevant methodological papers covering 12 methods and 8 extensions to those methods were identified. Methods are broadly classified into 4 groups: 1) simple methods, 2) principal stratification methods, 3) generalized methods (g-methods), and 4) pharmacometrics-based methods using pharmacokinetics and pharmacodynamics (PKPD) analysis. Each method makes specific assumptions and has associated limitations. Five of the 12 methods are capable of adjusting for real-world nonadherence, with only g-methods and PKPD considered appropriate for HTA. Conclusion. A range of statistical methods is available for adjusting estimates of treatment effectiveness for nonadherence, but most are not suitable for use in HTA. G-methods and PKPD appear to be more appropriate to estimate effectiveness in the presence of real-world adherence.

Systematic review of the evidence on the cost-effectiveness of pharmacogenomics-guided treatment for cardiovascular diseases

PURPOSE

To examine the evidence on the cost-effectiveness of implementing pharmacogenomics (PGx) in cardiovascular disease (CVD) care.

METHODS

We conducted a systematic review using multiple databases from inception to 2018. The titles and abstracts of cost-effectiveness studies on PGx-guided treatment in CVD care were screened, and full texts were extracted.

RESULTS

We screened 909 studies and included 46 to synthesize. Acute coronary syndrome and atrial fibrillation were the predominantly studied conditions (59%). Most studies (78%) examined warfarin-CYP2C9/VKORC1 or clopidogrel-CYP2C19. A payer's perspective was commonly used (39%) for cost calculations, and most studies (46%) were US-based. The majority (67%) of the studies found PGx testing to be cost-effective in CVD care, but cost-effectiveness varied across drugs and conditions. Two studies examined PGx panel testing, of which one examined pre-emptive testing strategies.

CONCLUSION

We found mixed evidence on the cost-effectiveness of PGx in CVD care. Supportive evidence exists for clopidogrel-CYP2C19 and warfarin-CYP2C9/VKORC1, but evidence is limited in other drug-gene combinations. Gaps persist, including unclear explanation of perspective and cost inputs, underreporting of study design elements critical to economic evaluations, and limited examination of PGx panel and pre-emptive testing for their cost-effectiveness. This review identifies the need for further research on economic evaluations of PGx implementation.

Pharmacogenetics in the Treatment of Cardiovascular Diseases and Its Current Progress Regarding Implementation in the Clinical Routine

There is a special interest in the implementation of pharmacogenetics in clinical practice, although there are some barriers that are preventing this integration. A large part of these pharmacogenetic tests are focused on drugs used in oncology and psychiatry fields and for antiviral drugs. However, the scientific evidence is also high for other drugs used in other medical areas, for example, in cardiology. In this article, we discuss the evidence and guidelines currently available on pharmacogenetics for clopidogrel, warfarin, acenocoumarol, and simvastatin and its implementation in daily clinical practice.

Impact of Non-Adherence and Flare Resolution on the Cost-Effectiveness of Treatments for Gout: Application of a Linked Pharmacometric/Pharmacoeconomic Model

BACKGROUND

Dual urate-lowering therapy (ULT) with lesinurad in combination with either allopurinol or febuxostat is an option for patients with gout unsuccessfully treated on either monotherapy. Treatment failure is often a result of poor medication adherence. Imperfect adherence in clinical trials may lead to biased estimates of treatment effect and confound the results of cost-effectiveness analyses.

OBJECTIVES

To estimate the impact of varying medication adherence on the cost effectiveness of lesinurad dual therapy and estimate the value-based price of lesinurad at which the incremental cost-effectiveness ratio is equal to £20,000 per quality-adjusted life-year (QALY).

METHODS

Treatment effect was simulated using published pharmacokinetic-pharmacodynamic models and scenarios representing adherence in clinical trials, routine practice, and perfect use. The subsequent cost and health impacts, over the lifetime of a patient cohort, were estimated using a bespoke pharmacoeconomic model.

RESULTS

The base-case incremental cost-effectiveness ratios comparing lesinurad dual ULT with monotherapy ranged from £39,184 to £78,350/QALY gained using allopurinol and £31,901 to £124,212/QALY gained using febuxostat, depending on the assumed medication adherence. Results assuming perfect medication adherence imply a per-quarter value-based price of lesinurad of £45.14 when used in dual ULT compared with allopurinol alone and £57.75 compared with febuxostat alone, falling to £25.41 and £3.49, respectively, in simulations of worsening medication adherence.

CONCLUSIONS

The estimated value-based prices of lesinurad only exceeded that which has been proposed in the United Kingdom when assuming both perfect drug adherence and the eradication of gout flares in sustained treatment responders.

Innovation at the Intersection of Clinical Trials and Real-World Data Science to Advance Patient Care

While efficacy and safety data collected from randomized clinical trials are the evidentiary standard for determining market authorization, this alone may no longer be sufficient to address the needs of key stakeholders (regulators, providers, and payers) and guarantee long-term success of pharmaceutical products. There is a heightened interest from stakeholders on understanding the use of real-world evidence (RWE) to substantiate benefit-risk assessment and support the value of a new drug. This review provides an overview of real-world data (RWD) and related advances in the regulatory framework, and discusses their impact on clinical research and development. A framework for linking drug development decisions with the value proposition of the drug, utilizing pharmacokinetic-pharmacodynamic-pharmacoeconomic models, is introduced. The summary presented here is based on the presentations and discussion at the symposium entitled Innovation at the Intersection of Clinical Trials and Real-World Data to Advance Patient Care at the American Society for Clinical Pharmacology and Therapeutics (ASCPT) 2017 Annual Meeting.

Personalized Anticoagulation: Optimizing Warfarin Management Using Genetics and Simulated Clinical Trials

BACKGROUND

Clinical trials testing pharmacogenomic-guided warfarin dosing for patients with atrial fibrillation have demonstrated conflicting results. Non-vitamin K antagonist oral anticoagulants are expensive and contraindicated for several conditions. A strategy optimizing anticoagulant selection remains an unmet clinical need.

METHODS AND RESULTS

Characteristics from 14 206 patients with atrial fibrillation were integrated into a validated warfarin clinical trial simulation framework using iterative Bayesian network modeling and a pharmacokinetic-pharmacodynamic model. Individual dose-response for patients was simulated for 5 warfarin protocols-a fixed-dose protocol, a clinically guided protocol, and 3 increasingly complex pharmacogenomic-guided protocols. For each protocol, a complexity score was calculated using the variables predicting warfarin dose and the number of predefined international normalized ratio (INR) thresholds for each adjusted dose. Study outcomes included optimal time in therapeutic range ≥65% and clinical events. A combination of age and genotype identified different optimal protocols for various subpopulations. A fixed-dose protocol provided well-controlled INR only in normal responders ≥65, whereas for normal responders <65 years old, a clinically guided protocol was necessary to achieve well-controlled INR. Sensitive responders ≥65 and <65 and highly sensitive responders ≥65 years old required pharmacogenomic-guided protocols to achieve well-controlled INR. However, highly sensitive responders <65 years old did not achieve well-controlled INR and had higher associated clinical events rates than other subpopulations.

CONCLUSIONS

Under the assumptions of this simulation, patients with atrial fibrillation can be triaged to an optimal warfarin therapy protocol by age and genotype. Clinicians should consider alternative anticoagulation therapy for patients with suboptimal outcomes under any warfarin protocol.

Genotype-guided warfarin therapy: current status

Warfarin pharmacogenomics has been an extensively studied field in the last decades as it is focused on personalized therapy to overcome the wide interpatient warfarin response variability and decrease the risk of side effects. In this expert review, besides briefly summarizing the current knowledge about warfarin pharmacogenetics, we also present an overview of recent studies that aimed to assess the efficacy, safety and economic issues related to genotype-based dosing algorithms used to guide warfarin therapy, including randomized and controlled clinical trials, meta-analyses and cost-effectiveness studies. To date, the findings still present disparities, mostly because of standard limitations. Thus, further studies should be encouraged to try to demonstrate the benefits of the application of warfarin pharmacogenomic dosing algorithms in clinical practice.

Cost-utility of empagliflozin in patients with type 2 diabetes at high cardiovascular risk

AIMS

In the Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes (EMPA-REG) trial, empagliflozin reduced cardiovascular and all-cause mortality in type 2 diabetes (T2D) patients at high cardiovascular risk. We sought to estimate the cost-effectiveness of empagliflozin versus standard treatment for the prevention of cardiovascular morbidity and mortality in patients with T2D.

METHODS

A Markov model was developed to assess the cost-effectiveness of empagliflozin (versus standard treatment) for the prevention of cardiovascular morbidity and mortality in patients with T2D using a 3-month cycle length and a lifetime horizon. Data sources included the EMPA-REG randomized clinical trial and other published epidemiological studies. Outcomes included treatment costs (in 2016 US$), quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs). Probabilistic sensitivity analysis (PSA) was performed to test the robustness of conclusions.

RESULTS

Empagliflozin use resulted in higher total lifetime treatment costs ($371,450 versus $272,966) but yielded greater QALYs (10.712 vs. 9.419) compared to standard treatment. This corresponded to an ICER of $76,167 per QALY gained. PSA suggested empagliflozin would be cost-effective in 96% of 10,000 iterations assuming a willingness-to-pay threshold of $100,000 per QALY gained.

CONCLUSION

Empagliflozin may be cost-effective compared to standard treatment in T2D patients at high cardiovascular risk.

The challenges of implementing pharmacogenomic testing in the clinic

INTRODUCTION

Pharmacogenomic testing has the potential to greatly benefit patients by enabling personalization of medication management, ensuring better efficacy and decreasing the risk of side effects. However, to fully realize the potential of pharmacogenomic testing, there are several important issues that must be addressed. Areas covered: In this expert review we discuss current challenges impacting the implementation of pharmacogenomic testing in the clinical practice. We emphasize issues related to testing methods, reporting of the results, test selection, clinical interpretation of the results, cost-effectiveness, and the long-term use of pharmacogenomic results in clinical practice. We identify opportunities and future directions to facilitate clinical implementation. Expert commentary: Several key elements are necessary to optimally integrate pharmacogenomic testing into clinical practice. Collaborative efforts among laboratories are needed to improve standardization of testing and reporting of the results. Clinicians need educational opportunities to improve understanding of which test to order and how to interpret the results. The electronic health records and other clinical systems need to improve their storage of the pharmacogenomics test results and interoperability to facilitate the use of clinically actionable results to improve patient care.

Warfarin Pharmacogenomics in Diverse Populations

Genotype-guided warfarin dosing algorithms are a rational approach to optimize warfarin dosing and potentially reduce adverse drug events. Diverse populations, such as African Americans and Latinos, have greater variability in warfarin dose requirements and are at greater risk for experiencing warfarin-related adverse events compared with individuals of European ancestry. Although these data suggest that patients of diverse populations may benefit from improved warfarin dose estimation, the vast majority of literature on genotype-guided warfarin dosing, including data from prospective randomized trials, is in populations of European ancestry. Despite differing frequencies of variants by race/ethnicity, most evidence in diverse populations evaluates variants that are most common in populations of European ancestry. Algorithms that do not include variants important across race/ethnic groups are unlikely to benefit diverse populations. In some race/ethnic groups, development of race-specific or admixture-based algorithms may facilitate improved genotype-guided warfarin dosing algorithms above and beyond that seen in individuals of European ancestry. These observations should be considered in the interpretation of literature evaluating the clinical utility of genotype-guided warfarin dosing. Careful consideration of race/ethnicity and additional evidence focused on improving warfarin dosing algorithms across race/ethnic groups will be necessary for successful clinical implementation of warfarin pharmacogenomics. The evidence for warfarin pharmacogenomics has a broad significance for pharmacogenomic testing, emphasizing the consideration of race/ethnicity in discovery of gene-drug pairs and development of clinical recommendations for pharmacogenetic testing.

Integrating genotypes in the SAMe-TT2R2 score for the prediction of anticoagulation control in Chinese patients with atrial fibrillation on warfarin

INTRODUCTION

The SAMe-TT₂R₂ score has been proposed to predict whether patients with atrial fibrillation (AF) would be well anti-coagulated with warfarin or not. However, it might over-estimate the number of patients under suboptimal warfarin treatment in non-Caucasians. This study was designed to modify the SAMe-TT₂R₂ score with genotypes and validate it in Chinese AF patients treated with warfarin.

MATERIAL AND METHODS

Consented Chinese-Han patients (n=510) with AF under the treatment of warfarin for at least 3months were randomly divided into a derivation (n=310) and a validation cohort (n=200). For each patient, CYP2C9*3 and VKORC1 -1639 A/G genotyping was performed, and the time in therapeutic range (TTR) was calculated over this period.

RESULTS

The modified SAMe-TT₂R₂ score was established by adding "warfarin genotype bins" to replace "the non-white race" variable. In the validation cohort, the discrimination performance of the modified score for good anticoagulation control (TTR≥70%) was significantly improved (c- index increased from 0.60 to 0.67). Significantly increased risks of major bleedings (HR: 4.91; 95% CI: 1.03-23.37; adjusted p=0.04) and all bleedings (HR: 1.93; 95% CI: 1.14-3.25; adjusted p=0.01) were found in patients with modified scores ≥2, as compared with patients with modified scores of 0-1.

CONCLUSIONS

The modified SAMe-TT₂R₂ score could improve the ability for the identification of good anticoagulation control, and the prediction of major bleeding events in Chinese patients with AF treated by warfarin.

Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine

The traditional paradigm of cardiovascular disease research derives insight from large-scale, broadly inclusive clinical studies of well-characterized pathologies. These insights are then put into practice according to standardized clinical guidelines. However, stagnation in the development of new cardiovascular therapies and variability in therapeutic response implies that this paradigm is insufficient for reducing the cardiovascular disease burden. In this state-of-the-art review, we examine 3 interconnected ideas we put forth as key concepts for enabling a transition to precision cardiology: 1) precision characterization of cardiovascular disease with machine learning methods; 2) the application of network models of disease to embrace disease complexity; and 3) using insights from the previous 2 ideas to enable pharmacology and polypharmacology systems for more precise drug-to-patient matching and patient-disease stratification. We conclude by exploring the challenges of applying a precision approach to cardiology, which arise from a deficit of the required resources and infrastructure, and emerging evidence for the clinical effectiveness of this nascent approach.

Cost-effectiveness of pharmacogenetic-guided treatment: are we there yet?

Pharmacogenetics (PGx) has the potential to personalize pharmaceutical treatments. Many relevant gene-drug associations have been discovered, but PGx-guided treatment needs to be cost-effective as well as clinically beneficial to be incorporated into standard health-care. We reviewed economic evaluations for PGx associations listed in the US Food and Drug Administration (FDA) Table of Pharmacogenomic Biomarkers in Drug Labeling. We determined the proportion of evaluations that found PGx-guided treatment to be cost-effective or dominant over the alternative strategies, and estimated the impact on this proportion of removing the cost of genetic testing. Of the 137 PGx associations in the FDA table, 44 economic evaluations, relating to 10 drugs, were identified. Of these evaluations, 57% drew conclusions in favour of PGx testing, of which 30% were cost-effective and 27% were dominant (cost-saving). If genetic information was freely available, 75% of economic evaluations would support PGx-guided treatment, of which 25% would be cost-effective and 50% would be dominant. Thus, PGx-guided treatment can be a cost-effective and even a cost-saving strategy. Having genetic information readily available in the clinical health record is a realistic future prospect, and would make more genetic tests economically worthwhile.

Translating Pharmacometrics to a Pharmacoeconomic Model of COPD

BACKGROUND

A model-based meta-analysis (MBMA) is a type of meta-regression that uses nonlinear mixed-effects models estimated on trial-level data to relate patient and trial characteristics, dosing, biomarkers, and outcomes of treatment.

OBJECTIVES

To use a pharmacometric MBMA within a pharmacoeconomic model of chronic obstructive pulmonary disease (COPD).

METHODS

A Markov microsimulation model was developed to estimate monthly changes in the key disease severity metrics of COPD (forced expiratory volume in 1 second [FEV₁] and exacerbations) to compare a hypothetical drug that increases FEV₁ to usual care. The MBMA was used to predict a baseline exacerbation rate in a group of actual trial patients, given their known baseline FEV₁. The hypothetical drug increased FEV₁, thereby decreasing individuals' predicted exacerbation rates. Individual patient simulations allowed stochastic changes in monthly FEV₁ decline.

RESULTS

In a sample of 1097 trial patients with a mean FEV₁ of 50%, the MBMA predicted 0.93 exacerbations per year on average. The exacerbation rate ranged from 0.52 to 1.3 per year across moderate and severe patient subgroups. A hypothetical anti-inflammatory drug that increased FEV₁ by 50 ml decreased exacerbations by 26%. Given a simplified estimation of costs and quality-adjusted life-years (QALYs) associated with COPD, a drug with a 50-ml increase priced at €35/mo had an incremental cost-effectiveness ratio ranging from €13,000/QALY to approximately €207,000/QALY across patient severity subgroups.

CONCLUSIONS

The synergistic aspects of MBMA and pharmacoeconomic modeling are highlighted in this hypothetical example. Markov microsimulation modeling allows the finer predictions of MBMA to inform parameters. Such an approach has utility in both early-phase cost-effectiveness estimations and trial design.

Can pharmacogenetics help patients under chronic treatment with coumarin anticoagulants?

Vitamin K antagonists are highly effective antithrombotic drugs. However, appropriate dosing is difficult to establish owing to its narrow therapeutic window as well as widespread inter- and intra-individual variability in dosage. Compared with dosing solely based on clinical information, pharmacogenetics can help improve the therapy with coumarins by decreasing the time to reach a stable dose and reducing the risk of bleeding. Most of the studies about genotyping of patients using vitamin K antagonists have focused on predicting the stable dose. Two genes have been shown to have the most influence on dosing: VKORC1 and CYP2C9. Furthermore, genotyping of more genes, such as CYP4F2 and APOE, is also being included in some dosing algorithms. The role of genotype beyond the initial dose-titration phase is less clear. Thus, a proven genetically determined risk of unstable dose or bleeding could help with the selection of patients who require more frequent monitoring of dose. On the other hand, patients who have a genetically determined stable dose could self-monitor their international normalized ratio (INR), making the therapy less expensive and more convenient.

A Systematic Literature Review on the Cost-Effectiveness of Apixaban for Stroke Prevention in Non-valvular Atrial Fibrillation

INTRODUCTION

Economic evaluations are becoming increasingly important due to limitations in economic resources, the expense of many new treatments, the need to allocate health spending as effectively as possible, and the need to inform decision makers. Based on the data from the apixaban studies (ARISTOTLE and AVERROES), several economic evaluations have been performed in various countries to demonstrate the efficacy of apixaban versus warfarin and aspirin or other new oral anticoagulants (NOACs) for preventing stroke in patients with non-valvular atrial fibrillation (NVAF).The aim of this study was to perform a systematic literature review of published economic evaluations with apixaban in the indication of stroke prevention in patients with NVAF.

METHODS

A search in PubMed, Cochrane Library, Google Scholar, and Index Medicus Español was conducted in June 2015. Inclusion and exclusion criteria were established. The main characteristics were recorded for all relevant articles after being reviewed. In addition, a weighted version of the Drummond's checklist was used to further assess the quality of the selected studies.

RESULTS

After review, 26 cost-effectiveness analyses through Markov models were included; the identified economic evaluations represent different willingness-to-pay (WTP) thresholds, discount rates, medical costs, and healthcare systems. Apixaban was compared with warfarin/acenocoumarol in 7 of them (27%), with warfarin/NOACs in 14 (54%), with aspirin in 2 (8%), and with warfarin/aspirin in 3 (11%). Models were conducted from Europe (69%), USA (23%), Australia (4%), and Latin America (4%). All models reported cost/quality-adjusted life years (QALYs) gained, 92% reported using a payer perspective, and 8% using a societal perspective; the median quality score of the selected studies was 89 (out of 119), with a range of 55-103. In models performed in Europe, incremental cost-effectiveness ratios (ICERs) of apixaban versus warfarin ranged from €5607/QALY to €57,245/QALY, while ICERs versus aspirin ranged from being dominant to €7334/QALY. In models carried out in the USA, ICERs of apixaban versus warfarin ranged from being dominant to $93,063/QALY.

CONCLUSION

Different cost-effectiveness analyses suggest that apixaban is a cost-effective therapeutic option according to the WTP thresholds used in countries where cost-effectiveness analyses, were performed.

FUNDING

BMS and Pfizer.

A Systematic Review of Economic Evaluations of Pharmacogenetic Testing for Prevention of Adverse Drug Reactions

BACKGROUND

Pharmacogenetics offers the potential to improve health outcomes by identifying individuals who are at greater risk of harm from certain medicines. Routine adoption of pharmacogenetic tests requires evidence of their cost effectiveness.

OBJECTIVE

The present review aims to systematically review published economic evaluations of pharmacogenetic tests that aim to prevent or reduce the incidence of ADRs.

METHODS

We conducted a systematic literature review of economic evaluations of pharmacogenetic tests aimed to reduce the incidence of adverse drug reactions. Literature was searched using Embase, MEDLINE and the NHS Economic Evaluation Database with search terms relating to pharmacogenetic testing, adverse drug reactions, economic evaluations and pharmaceuticals. Titles were screened independently by two reviewers. Articles deemed to meet the inclusion criteria were screened independently on abstract, and full texts reviewed.

RESULTS

We identified 852 articles, of which 47 met the inclusion criteria. There was evidence supporting the cost effectiveness of testing for HLA-B*57:01 (prior to abacavir), HLA-B*15:02 and HLA-A*31:01 (prior to carbamazepine), HLA-B*58:01 (prior to allopurinol) and CYP2C19 (prior to clopidogrel treatment). Economic evidence was inconclusive with respect to TPMT (prior to 6-mercaptoputine, azathioprine and cisplatin therapy), CYP2C9 and VKORC1 (to inform genotype-guided dosing of coumarin derivatives), MTHFR (prior to methotrexate treatment) and factor V Leiden testing (prior to oral contraception). Testing for A1555G is not cost effective before prescribing aminoglycosides.

CONCLUSIONS

Our systematic review identified robust evidence of the cost effectiveness of genotyping prior to treatment with a number of common drugs. However, further analyses and (or) availability of robust clinical evidence is necessary to make recommendations for others.

Economic Evaluations of Pharmacogenetic and Pharmacogenomic Screening Tests: A Systematic Review. Second Update of the Literature

Objective

Due to extended application of pharmacogenetic and pharmacogenomic screening (PGx) tests it is important to assess whether they provide good value for money. This review provides an update of the literature.

Methods

A literature search was performed in PubMed and papers published between August 2010 and September 2014, investigating the cost-effectiveness of PGx screening tests, were included. Papers from 2000 until July 2010 were included via two previous systematic reviews. Studies’ overall quality was assessed with the Quality of Health Economic Studies (QHES) instrument.

Results

We found 38 studies, which combined with the previous 42 studies resulted in a total of 80 included studies. An average QHES score of 76 was found. Since 2010, more studies were funded by pharmaceutical companies. Most recent studies performed cost-utility analysis, univariate and probabilistic sensitivity analyses, and discussed limitations of their economic evaluations. Most studies indicated favorable cost-effectiveness. Majority of evaluations did not provide information regarding the intrinsic value of the PGx test. There were considerable differences in the costs for PGx testing. Reporting of the direction and magnitude of bias on the cost-effectiveness estimates as well as motivation for the chosen economic model and perspective were frequently missing.

Conclusions

Application of PGx tests was mostly found to be a cost-effective or cost-saving strategy. We found that only the minority of recent pharmacoeconomic evaluations assessed the intrinsic value of the PGx tests. There was an increase in the number of studies and in the reporting of quality associated characteristics. To improve future evaluations, scenario analysis including a broad range of PGx tests costs and equal costs of comparator drugs to assess the intrinsic value of the PGx tests, are recommended. In addition, robust clinical evidence regarding PGx tests’ efficacy remains of utmost importance.

The value of routine pharmacogenomic screening-Are we there yet? A perspective on the costs and benefits of routine screening-shouldn't everyone have this done?

Although there are several examples in which pharmacogenomic testing seems to provide clinical and economic value, use of pharmacogenomics as a tool to improve drug therapy through routine screening of unselected patients is currently tentative. An informal evaluation of the clinical benefits and economic costs of pharmacogenomic screening suggests that improving the evidence base, addressing uncertainty, and facilitating implementation can lead to practical and cost-effective pharmacogenomic screening programs.

Universal versus genotype-guided use of direct oral anticoagulants in atrial fibrillation patients: a decision analysis

AIM

This study aims to compare clinical and economic outcomes of CYP2C9 and VKORC1 genotype-guided (PG-DOAC) versus universal use of direct oral anticoagulant (DOAC) for stroke prevention in patients with atrial fibrillation (AF).

METHODS

Outcomes of oral anticoagulation therapy were simulated using life-long Markov modeling. In PG-DOAC, patients with genotype of high or low warfarin sensitivity were treated with DOAC, and patients with normal warfarin sensitivity genotype received warfarin.

RESULTS

Expected quality-adjusted life-years (QALYs) and cost of DOAC were higher than PG-DOAC. Incremental cost per QALY (ICER) of DOAC versus PG-DOAC was 314,129 USD/QALY, exceeding willingness-to-pay threshold (50,000 USD/QALY).

CONCLUSION

Using individual genotype to guide the use of DOAC versus warfarin appears to be the preferred strategy.

Stroke prevention with rivaroxaban in higher-risk populations with atrial fibrillation

BACKGROUND

Atrial fibrillation (AF), the most common cardiac arrhythmia, is a major risk factor for stroke. Rivaroxaban, an oral factor Xa inhibitor, is approved for the prevention of stroke in patients with non-valvular AF. In the pivotal phase III trial ROCKET AF, rivaroxaban demonstrated non-inferiority compared with warfarin for reducing the risk of stroke or systemic embolism (SE) in patients with AF (intention-to-treat analysis), without an increased risk of major bleeding. Superior efficacy vs. warfarin was achieved while patients were on study medication. Other direct oral factor Xa inhibitors have completed phase III clinical trials in this indication. Compared with warfarin, apixaban (in the ARISTOTLE trial) and edoxaban (in the ENGAGE-AF trial) were shown to be superior or non-inferior, respectively, for reduction in stroke or SE risk in patients with AF. Baseline stroke risk, as indicated by CHADS2 scores, was lower in patients in the ARISTOTLE and ENGAGE-AF trials than in ROCKET AF.

OBJECTIVES

This review discusses the main findings from ROCKET AF, specifically examining recent subgroup analyses investigating rivaroxaban use across various patient types at high risk for adverse outcomes, including those with prior stroke or transient ischaemic attack, reduced renal function, prior myocardial infarction, peripheral artery disease, heart failure or patients aged ≥ 75 years and those resident in East Asia.

CONCLUSIONS

These subgroup analyses demonstrate that the treatment effect for rivaroxaban vs. warfarin is broadly consistent across a wide range of patient groups, with respect to both efficacy and safety.

Clinical implications of neuropharmacogenetics

INTRODUCTION

Pharmacogenetics aims to identify the underlying genetic factors participating in the variability of drug response. Indeed, genetic variability at the DNA or RNA levels can directly or indirectly modify the pharmacokinetic or the pharmacodynamic parameters of a drug. The ultimate aim of pharmacogenetics is to move towards a personalised medicine by predicting responders and non-responders, adjusting the dose of the treatment, and identifying individuals at risk of adverse drug effects.

METHODS

A literature research was performed in which we reviewed all pharmacogenetic studies in neurological disorders including neurodegenerative diseases, multiple sclerosis, stroke and epilepsy.

RESULTS

Several pharmacogenetic studies have been performed in neurology, bringing insights into the inter-individual drug response variability and in the pathophysiology of neurological diseases. The principal implications of these studies for the management of patients in clinical practice are discussed.

CONCLUSION/DISCUSSION

Although several genetic factors have been identified in the modification of drug response in neurological disorders, most of them have a marginal predictive effect at the single gene level, suggesting mutagenic interactions as well as other factors related to drug interaction and disease subtypes. Most pharmacogenetic studies deserve further replication in independent populations and, ideally, in pharmacogenetic clinical trials to demonstrate their relevance in clinical practice.