Systematic review of pharmacoeconomic studies of pharmacogenomic tests

Precision medicine in pharmacy: assessing pharmacogenomics competence among pharmacists and pharmacy students

Background

Pharmacogenomics, a key component of precision medicine, aims to improve healthcare outcomes. As pharmacists play a pivotal role in this evolving field, an assessment of their preparedness to apply pharmacogenomics is imperative.

Methods

In this cross-sectional study, a validated questionnaire (Content Validity Ratio > 0.741, p < 0.05) that demonstrated reliability (Cronbach's alpha for all scales > 0.7) gathered data on demographics, knowledge, attitudes, barriers, and confidence in pharmacogenomics among pharmacists and pharmacy students in Jordan. Statistical analysis assessed associations and their strength within the collected data and variables.

Results

This study included 514 pharmacists and pharmacy students. Knowledge scores were moderate and correlated with academic level and pharmacy school attended. Most participants were open to providing pharmacogenomics testing and interpretation through pharmacy services, but the majority demonstrated concerns about potential misinterpretation of test results and the resulting patients' anxiety. Students cited limited accessibility, while pharmacists identified the lack of standardised guidelines as the main roadblock.

Conclusion

This study highlights the need for education to prepare pharmacists for their role in pharmacogenomics. Despite positive attitudes from pharmacists, addressing knowledge gaps, the low confidence in recommending pharmacogenomics tests, and concerns about implementation are essential.

The Net Benefit of Personalized Medicine: A Systematic Literature Review and Regression Analysis

OBJECTIVES

Amidst conflicting expectations about the benefits of personalized medicine (PM) and the potentially high implementation costs, we reviewed the available evidence on the cost-effectiveness of PM relative to non-PM.

METHODS

We conducted a systematic literature review of economic evaluations of PM and extracted data, including incremental quality-adjusted life-years (ΔQALYs) and incremental costs (Δcosts). ΔQALYs and Δcosts were combined with estimates of national cost-effectiveness thresholds to calculate incremental net monetary benefit (ΔNMB). Regression analyses were performed with these variables as dependent variables and PM intervention characteristics as independent variables. Random intercepts were used to cluster studies according to country.

RESULTS

Of 4774 studies reviewed, 128 were selected, providing cost-effectiveness data for 279 PM interventions. Most studies were set in the United States (48%) and the United Kingdom (16%) and adopted a healthcare perspective (82%). Cancer treatments (60%) and pharmaceutical interventions (72%) occurred frequently. Prognostic tests (19%) and tests to identify (non)responders (37%) were least and most common, respectively. Industry sponsorship occurred in 32%. Median ΔQALYs, Δcosts, and ΔNMB per individual were 0.03, Int$575, and Int$18, respectively. We found large heterogeneity in cost-effectiveness. Regression analysis showed that gene therapies were associated with higher ΔQALYs than other interventions. PM interventions for neoplasms brought higher ΔNMB than PM interventions for other conditions. Nonetheless, average ΔNMB in the 'neoplasm' group was found to be negative.

CONCLUSIONS

PM brings improvements in health but often at a high cost, resulting in 0 to negative ΔNMB on average. Pricing policies may be needed to reduce the costs of interventions with negative ΔNMB.

Guidance for the Harmonisation and Improvement of Economic Evaluations of Personalised Medicine

OBJECTIVE

The objective of this study was to develop guidance contributing to improved consistency and quality in economic evaluations of personalised medicine (PM), given current ambiguity about how to measure the value of PM as well as considerable variation in the methodology and reporting in economic evaluations of PM.

METHODS

A targeted literature review of methodological papers was performed for an overview of modelling challenges in PM. Expert interviews were held to discuss best modelling practice. A systematic literature review of economic evaluations of PM was conducted to gain insight into current modelling practice. The findings were synthesised and used to develop a set of draft recommendations. The draft recommendations were discussed at a stakeholder workshop and subsequently finalised.

RESULTS

Twenty-two methodological papers were identified. Some argued that the challenges in modelling PM can be addressed within existing methodological frameworks, others disagreed. Eighteen experts were interviewed. They believed large uncertainty to be a key concern. Out of 195 economic evaluations of PM identified, 56% addressed none of the identified modelling challenges. A set of 23 recommendations was developed. Eight recommendations focus on the modelling of test-treatment pathways. The use of non-randomised controlled trial data is discouraged but several recommendations are provided in case randomised controlled trial data are unavailable. The parameterisation of structural uncertainty is recommended. Other recommendations consider perspective and discounting; premature survival data; additional value elements; patient and clinician compliance; and managed entry agreements.

CONCLUSIONS

This study provides a comprehensive list of recommendations to modellers of PM and to evaluators and reviewers of PM models.

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.

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 clinical analysis laboratory: clinical practice, research, and drug development pipeline

Introduction: Over the last decade, the spread of next-generation sequencing technology along with the rising cost in health management in national health systems has led to widespread use/abuse of pharmacogenetic tests (PGx) in the practice of many clinical disciplines. However, given their clinical significance, it is important to standardize these tests for having an interaction with the clinical analysis laboratory (CAL), in which a PGx service can meet these requirements. Areas covered: A diagnostic test must meet the criteria of reproducibility and validity for its utility in the clinical routine. This present review mainly describes the utility of introducing PGx tests in the CAL routine to produce correct results useful for setting up personalized drug treatments. Expert opinion: With a PGx service, CALs can provide the right tool to help clinicians to make better choices about different categories of drugs and their dosage and to manage the economic impact both in hospital-based settings and in National Health Services, throughout electronic health records. Advances in PGx also allow a new approach for pharmaceutical companies in order to improve drug development and clinical trials. As a result, CALs can achieve a powerful source of epidemiological, clinical, and research findings from PGx tests.

Economic Value of Pharmacogenetic Testing for Cancer Drugs with Clinically Relevant Drug-Gene Associations: A Systematic Literature Review

BACKGROUND

Pharmacogenetic testing can provide predictive insights about the efficacy and safety of drugs used in cancer treatment. Although many drug-gene associations have been reported in the literature, the strength of evidence supporting each association can vary significantly. Even among the subgroup of drugs classified by the PharmGKB database to have a high or moderate level of evidence, there is limited information regarding the economic value of pharmacogenetic testing.

OBJECTIVES

To: (a) summarize the available pharmacoeconomic evidence assessing the value of pharmacogenetic testing for cancer drugs with clinically relevant drug-gene associations; (b) determine the quality of the studies that contain this evidence; and (c) discuss the quality of this evidence with respect to the level of evidence of the drug-gene associations.

METHODS

The PharmGKB database was used to identify cancer drugs with clinically relevant drug-gene associations graded high (1A, 1B) or moderate (2A, 2B). A systematic literature review was conducted using these drugs. Ovid MEDLINE and Embase databases were searched to identify cost-effectiveness, cost-utility, or cost-minimization studies comparing pharmacogenetic testing to an alternative. Cost and effect values from every relevant comparison within the studies were extracted, and the incremental cost-effectiveness ratio (ICER) was either extracted or calculated for each comparison. Quality assessment was conducted for each study using the Quality of Health Economic Studies (QHES) instrument. Qualitative synthesis was used to summarize the data.

RESULTS

The search yielded 2,191 citations, of which 35 studies met the inclusion criteria. Pharmacoeconomic studies were available for the following drugs from the PharmGKB database: fluoropyrimidine, 6-mercaptopurine, irinotecan, carboplatin, cisplatin, erlotinib, gefitinib, cetuximab, panitumumab, and trastuzumab. The studies were conducted in Asia, Europe, Canada, the United States, and Mexico and reported cost-utility, cost-effectiveness, and cost-minimization outcomes. The mean QHES score was 80 (SD = 22) for the studies of drug-gene pairs with high (1A, 1B) and moderate (2A, 2B) levels of evidence (1A = 82, 1B = 93, 2A = 71, and 2B = 74). There was variation across studies in terms of reporting. 109 relevant comparisons were identified within the studies. Of those that reported cost per life-year or cost per quality-adjusted life-year (n = 58 comparisons), pharmacogenetic testing was dominant in 21% overall and 42%, 21%, 17%, and 5% of the comparisons in Asia, Europe, Canada, and the United States, respectively. Variability was observed in the ICER values regardless of geographic region or drug. Pharmacogenetic testing was cost saving in 17 of 19 cost-minimization comparisons and was favored most frequently when compared with genetically indiscriminate strategies containing the drug of interest.

CONCLUSIONS

There was mixed evidence regarding the value of pharmacogenetic testing to guide cancer treatment. For future pharmacogenomic-related economic studies, we recommend prioritizing clinically relevant drug-gene associations and greater adherence to available best practice guidelines for conducting and reporting economic evaluation studies.

DISCLOSURES

No outside funding supported this review. Part of Hussain's research time was supported by a Merit Review Award (I01 BX000545), Medical Research Service, U.S. Department of Veterans Affairs. Hussain also reports personal fees from Bristol-Myers Squibb, AstraZeneca, Novartis, Bayer HealthCare Pharmaceuticals, and France Foundation, outside the submitted work. Onukwugha reports grants from Pfizer and Bayer HealthCare Pharmaceuticals, along with advisory board fees from Novo Nordisk, outside the submitted work. Faruque, Neuberger, and Noh have nothing to disclose.

Precision Medicine: From Science To Value

Precision medicine is making an impact on patients, health care delivery systems, and research participants in ways that were only imagined fifteen years ago when the human genome was first sequenced. Discovery of disease-causing and drug-response genetic variants has accelerated, while adoption into clinical medicine has lagged. We define precision medicine and the stakeholder community required to enable its integration into research and health care. We explore the intersection of data science, analytics, and precision medicine in the formation of health systems that carry out research in the context of clinical care and that optimize the tools and information used to deliver improved patient outcomes. We provide examples of real-world impact and conclude with a policy and economic agenda necessary for the adoption of this new paradigm of health care both in the United States and globally.

The economic case for precision medicine

Introduction: The advancement of precision medicine into routine clinical practice has been highlighted as an agenda for national and international health care policy. A principle barrier to this advancement is in meeting requirements of the payer or reimbursement agency for health care. This special report aims to explain the economic case for precision medicine, by accounting for the explicit objectives defined by decision-makers responsible for the allocation of limited health care resources. Areas covered: The framework of cost-effectiveness analysis, a method of economic evaluation, is used to describe how precision medicine can, in theory, exploit identifiable patient-level heterogeneity to improve population health outcomes and the relative cost-effectiveness of health care. Four case studies are used to illustrate potential challenges when demonstrating the economic case for a precision medicine in practice. Expert commentary: The economic case for a precision medicine should be considered at an early stage during its research and development phase. Clinical and economic evidence can be generated iteratively and should be in alignment with the objectives and requirements of decision-makers. Programmes of further research, to demonstrate the economic case of a precision medicine, can be prioritized by the extent that they reduce the uncertainty expressed by decision-makers.

Metabolomics Applications in Precision Medicine: An Oncological Perspective

Nowadays, cancer therapy remains limited by the conventional one-size-fits-all approach. In this context, treatment decisions are based on the clinical stage of disease but fail to ascertain the individual´s underlying biology and its role in driving malignancy. The identification of better therapies for cancer treatment is thus limited by the lack of sufficient data regarding the characterization of specific biochemical signatures associated with each particular cancer patient or group of patients. Metabolomics approaches promise a better understanding of cancer, a disease characterized by significant alterations in bioenergetic metabolism, by identifying changes in the pattern of metabolite expression in addition to changes in the concentration of individual metabolites as well as alterations in biochemical pathways. These approaches hold the potential of identifying novel biomarkers with different clinical applications, including the development of more specific diagnostic methods based on the characterization of metabolic subtypes, the monitoring of currently used cancer therapeutics to evaluate the response and the prognostic outcome with a given therapy, and the evaluation of the mechanisms involved in disease relapse and drug resistance. This review discusses metabolomics applications in different oncological processes underlining the potential of this omics approach to further advance the implementation of precision medicine in the oncology area.

A cost-effectiveness analysis of maternal CYP2D6 genetic testing to guide treatment for postpartum pain and avert infant adverse events

Mothers with a CYP2D6 ultrarapid metabolizer phenotype may expose their infants to risk of adverse events when taking codeine while breastfeeding, by producing more of the active metabolite, morphine. Pharmacogenetic testing may be a valuable tool to identify such mothers, but testing can be costly. The objective of the study was to determine the incremental costs of genotyping to avert neonatal adverse events during maternal pharmacotherapy. A cost-effectiveness analysis, using a decision model, was performed with a hypothetical cohort of prenatal subjects. Parameter estimates, costs and ranges for sensitivity analyses were ascertained from the literature and expert opinion. Sensitivity analyses were conducted to assess the robustness of the results. Probabilistic sensitivity analysis revealed an incremental cost-effectiveness (ICER) of $10 433 (Canadian dollars) for genotyping compared to no genotyping per adverse event averted. Results were sensitive to hospital admission costs. The ICER was lower when evaluating only subjects having caesarean deliveries or those from ethnic populations known to have a high prevalence of ultra-rapid metabolizers. Although genotyping to guide pharmacotherapy was not cost saving, the cost to avert an infant adverse event may represent good value for money in specific populations. With a growing demand for personalized medicine, these findings are relevant for decision makers, clinicians and patients.

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.

The experience of physicians in pharmacogenomic clinical decision support within eight German university hospitals

Aim: The aim of this study was to assess the physicians’ attitude, their knowledge and their experience in pharmacogenomic clinical decision support in German hospitals. Materials & methods: We conducted an online survey to address physicians of 13 different medical specialties across eight German university hospitals. In total, 564 returned questionnaires were analyzed. Results: The remaining knowledge gap, the uncertainty of test reimbursement and the physicians’ lack of awareness of existing pharmacogenomic clinical decision support systems (CDSS) are the major barriers for implementing pharmacogenomic CDSS into German hospitals. Furthermore, pharmacogenomic CDSS are most effective in the form of real-time decision support for internists. Conclusion: Physicians in German hospitals require additional education of both genetics and pharmacogenomics. They need to be provided with access to relevant pharmacogenomic CDSS.

Economic evaluation of procalcitonin-guided antibiotic therapy in acute respiratory infections: a Chinese hospital system perspective

Background:

Cost-impact models have indicated that in the USA, the use of antibiotic stewardship protocols based on procalcitonin (PCT) levels for patients with suspected acute respiratory tract infection results in cost savings. Our objective was to assess the cost impact of adopting PCT testing among patients with acute respiratory infections (ARI) from the perspective of a typical hospital system in urban China.

Methods:

To conduct an economic evaluation of PCT testing versus usual care we built a cost-impact model based on a previously published patient-level meta-analysis data of randomized trials including Chinese sites. The data were adapted to the China setting by applying the results to mean lengths of stay, costs, and practice patterns typically found in China. We estimated the annual ARI visit rate for the typical hospital system (assumed to be 1650 beds) and ARI diagnosis.

Results:

In the inpatient setting, the costs of PCT-guided care compared to usual care for a cohort of 16,405 confirmed ARI patients was almost 1.1 million Chinese yuan (CNY), compared to almost 1.8 million CNY for usual care, resulting in net savings of 721,563 CNY to a typical urban Chinese hospital system for 2015. In the ICU and outpatient settings, savings were 250,699 CNY and 2.4 million CNY, respectively. The overall annual net savings of PCT-guided care was nearly 3.4 million CNY.

Conclusions:

Substantial savings are associated with PCT protocols of ARI across common China hospital treatment settings mainly by direct reduction in unnecessary antibiotic utilization.

A systematic review and checklist presenting the main challenges for health economic modeling in personalized medicine: towards implementing patient-level models

INTRODUCTION

The ongoing development of genomic medicine and the use of molecular and imaging markers in personalized medicine (PM) has arguably challenged the field of health economic modeling (HEM). This study aims to provide detailed insights into the current status of HEM in PM, in order to identify if and how modeling methods are used to address the challenges described in literature. Areas covered: A review was performed on studies that simulate health economic outcomes for personalized clinical pathways. Decision tree modeling and Markov modeling were the most observed methods. Not all identified challenges were frequently found, challenges regarding companion diagnostics, diagnostic performance, and evidence gaps were most often found. However, the extent to which challenges were addressed varied considerably between studies. Expert commentary: Challenges for HEM in PM are not yet routinely addressed which may indicate that either (1) their impact is less severe than expected, (2) they are hard to address and therefore not managed appropriately, or (3) HEM in PM is still in an early stage. As evidence on the impact of these challenges is still lacking, we believe that more concrete examples are needed to illustrate the identified challenges and to demonstrate methods to handle them.

A model to assess the cost–effectiveness of pharmacogenomics tests in chronic heart failure: the case of ivabradine

Pharmacogenomics (PGx) tests have the potential of improving the effectiveness of expensive new drugs by predicting the likelihood, for a particular patient, to respond to a treatment. The objective of this study was to develop a pharmacoeconomic model to determine the characteristics and the cost–effectiveness of a hypothetical PGx test, which would identify patients who are most likely to respond to an expensive treatment for chronic heart failure. For this purpose, we chose the example of ivabradine. Our results suggest that the use of a PGx test that could select a subgroup of patients to be treated with an expensive drug has the potential to provide more efficient drug utilization.

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.

Economic evaluation of procalcitonin-guided antibiotic therapy in acute respiratory infections: a US health system perspective

BACKGROUND

Whether or not antibiotic stewardship protocols based on procalcitonin levels results in cost savings remains unclear. Herein, our objective was to assess the economic impact of adopting procalcitonin testing among patients with suspected acute respiratory tract infection (ARI) from the perspective of a typical US integrated delivery network (IDN) with a 1,000,000 member catchment area or enrollment.

METHODS

To conduct an economic evaluation of procalcitonin testing versus usual care we built a cost-impact model based on patient-level meta-analysis data of randomized trials. The meta-analytic data was adapted to the US setting by applying the meta-analytic results to US lengths of stay, costs, and practice patterns. We estimated the annual ARI visit rate for the one million member cohort, by setting (inpatient, ICU, outpatient) and ARI diagnosis.

RESULTS

In the inpatient setting, the costs of procalcitonin-guided compared to usual care for the one million member cohort was $2,083,545, compared to $2,780,322, resulting in net savings of nearly $700,000 to the IDN for 2014. In the ICU and outpatient settings, savings were $73,326 and $5,329,824, respectively, summing up to overall net savings of $6,099,927 for the cohort. RESULTS were robust for all ARI diagnoses. For the whole US insured population, procalcitonin-guided care would result in $1.6 billion in savings annually.

CONCLUSIONS

Our results show substantial savings associated with procalcitonin protocols of ARI across common US treatment settings mainly by direct reduction in unnecessary antibiotic utilization. These results are robust to changes in key parameters, and the savings can be achieved without any negative impact on treatment outcomes.

Evidence used in model-based economic evaluations for evaluating pharmacogenetic and pharmacogenomic tests: a systematic review protocol

INTRODUCTION

Decision models can be used to conduct economic evaluations of new pharmacogenetic and pharmacogenomic tests to ensure they offer value for money to healthcare systems. These models require a great deal of evidence, yet research suggests the evidence used is diverse and of uncertain quality. By conducting a systematic review, we aim to investigate the test-related evidence used to inform decision models developed for the economic evaluation of genetic tests.

METHODS AND ANALYSIS

We will search electronic databases including MEDLINE, EMBASE and NHS EEDs to identify model-based economic evaluations of pharmacogenetic and pharmacogenomic tests. The search will not be limited by language or date. Title and abstract screening will be conducted independently by 2 reviewers, with screening of full texts and data extraction conducted by 1 reviewer, and checked by another. Characteristics of the decision problem, the decision model and the test evidence used to inform the model will be extracted. Specifically, we will identify the reported evidence sources for the test-related evidence used, describe the study design and how the evidence was identified. A checklist developed specifically for decision analytic models will be used to critically appraise the models described in these studies. Variations in the test evidence used in the decision models will be explored across the included studies, and we will identify gaps in the evidence in terms of both quantity and quality.

DISSEMINATION

The findings of this work will be disseminated via a peer-reviewed journal publication and at national and international conferences.

Economics of stratified medicine in rheumatoid arthritis

Clinically relevant examples of stratified medicine are available for patients with rheumatoid arthritis (RA). The aim of this study was to understand the current economic evidence for stratified medicine in RA. Two systematic reviews were conducted to identify: (1) all economic evaluations of stratified treatments for rheumatoid arthritis, or those which have used a subgroup analysis, and (2) all stated preference studies of treatments for rheumatoid arthritis. Ten economic evaluations of stratified treatments for RA, 38 economic evaluations including with a subgroup analysis and eight stated preference studies were identified. There was some evidence to support that stratified approaches to treating a patient with RA may be cost-effective. However, there remain key gaps in the economic evidence base needed to support the introduction of stratified medicine in RA into healthcare systems and considerable uncertainty about how proposed stratified approaches will impact future patient preferences, outcomes and costs when used in routine practice.

Economic evaluations of personalized medicine: existing challenges and current developments

Personalized medicine, with the aim of safely, effectively, and cost-effectively targeting treatment to a prespecified patient population, has always been a long-time goal within health care. It is often argued that personalizing treatment will inevitably improve clinical outcomes for patients and help achieve more effective use of health care resources. Demand is increasing for demonstrable evidence of clinical and cost-effectiveness to support the use of personalized medicine in health care. This paper begins with an overview of the existing challenges in conducting economic evaluations of genetics- and genomics-targeted technologies, as an example of personalized medicine. Our paper illustrates the complexity of the challenges faced by these technologies by highlighting the variations in the issues faced by diagnostic tests for somatic variations, generally referring to genetic variation in a tumor, and germline variations, generally referring to inherited genetic variation in enzymes involved in drug metabolic pathways. These tests are typically aimed at stratifying patient populations into subgroups on the basis of clinical effectiveness (response) or safety (avoidance of adverse events). The paper summarizes the data requirements for economic evaluations of genetics and genomics-based technologies while outlining that the main challenges relating to data requirements revolve around the availability and quality of existing data. We conclude by discussing current developments aimed to address the challenges of assessing the cost-effectiveness of genetics and genomics-based technologies, which revolve around two central issues that are interlinked: the need to adapt available evaluation methods and identifying who is responsible for generating evidence for these technologies.

Health technology assessment and personalized medicine: are economic evaluation guidelines sufficient to support decision making?

BACKGROUND

Many jurisdictions delivering health care, including Canada, have developed guidance for conducting economic evaluation, often in the service of larger health technology assessment (HTA) and reimbursement processes. Like any health intervention, personalized medical (PM) interventions have costs and consequences that must be considered by reimbursement authorities with limited resources. However, current approaches to economic evaluation to support decision making have been largely developed from population-based approaches to therapy-that is, evaluating the costs and consequences of single interventions across single populations. This raises the issue as to whether these methods, as they are or more refined, are adequate to address more targeted approaches to therapy, or whether a new paradigm for assessing value in PM is required.

OBJECTIVES

We describe specific issues relevant to the economic evaluation of diagnostics-based PM and assess whether current guidance for economic evaluation is sufficient to support decision making for PM interventions.

METHODS

Issues were identified through literature review and informal interviews with national and international experts (n = 10) in these analyses. This article elaborates on findings and discussion at a workshop held in Ottawa, Canada, in January 2012.

RESULTS

Specific issues related to better guiding economic evaluation of personalized medicine interventions include: how study questions are developed, populations are characterized, comparators are defined, effectiveness is evaluated, outcomes are valued and how resources are measured. Diagnostics-based PM also highlights the need for analyses outside of economic evaluation to support decision making.

CONCLUSIONS

The consensus of this group of experts is that the economic evaluation of diagnostics-based PM may not require a new paradigm. However, greater complexity means that existing approaches and tools may require improvement to undertake these more analyses.

The economic value of personalized medicine tests: what we know and what we need to know

PURPOSE

There is uncertainty about when personalized medicine tests provide economic value. We assessed evidence on the economic value of personalized medicine tests and gaps in the evidence base.

METHODS

We created a unique evidence base by linking data on published cost-utility analyses from the Tufts Cost-Effectiveness Analysis Registry with data measuring test characteristics and reflecting where value analyses may be most needed: (i) tests currently available or in advanced development, (ii) tests for drugs with Food and Drug Administration labels with genetic information, (iii) tests with demonstrated or likely clinical utility, (iv) tests for conditions with high mortality, and (v) tests for conditions with high expenditures.

RESULTS

We identified 59 cost-utility analyses studies that examined personalized medicine tests (1998-2011). A majority (72%) of the cost/quality-adjusted life year ratios indicate that testing provides better health although at higher cost, with almost half of the ratios falling below $50,000 per quality-adjusted life year gained. One-fifth of the results indicate that tests may save money.

CONCLUSION

Many personalized medicine tests have been found to be relatively cost-effective, although fewer have been found to be cost saving, and many available or emerging medicine tests have not been evaluated. More evidence on value will be needed to inform decision making and assessment of genomic priorities.

Economic Evaluations of Pharmacogenetic Approaches in Infectious Diseases: A Review of Current Approaches and Evaluation of Critical Aspects Affecting their Quality

Pharmacogenetics holds great potential for improving the effectiveness of treatment modalities in infectious diseases by taking into account the genetic determinants of both the host and infectious agents' individuality. Better utilization of resources and improved therapeutic efficiency are the expected outcomes of personalized medicine using pharmacogenetic and pharmacogenomics information made available by technological advances. However, there has been growing concern in the clinical community regarding the evaluation of the true benefits of these approaches. This perception is partly due to the limited number and perceived poor quality of economic evaluations in this field, and initiatives aimed at harmonizing and communicating strategies improving the quality of these studies and their acceptance by the clinical community are greatly needed. This paper reviews current literature of economic evaluations of pharmacogenetics interventions guiding pharmacotherapy in infectious diseases. PubMed and the NHS Centre for Reviews and Dissemination databases were searched using a combination of five broad research terms related to pharmacogenetic approaches, and papers relative to economic evaluations of pharmacogenetic interventions in infectious diseases retained for further analysis. Using these criteria, a total of 14 papers were included in this review. The area of economic evaluation of pharmacogenetic interventions in infectious diseases remains understudied and would benefit from greater harmonization. The main weaknesses of evaluations reviewed in this paper seem to be represented by poor evidence of pharmacogenetic marker validation, inconsistencies in the selection of costs and utility included in the economic models and the choice of sensitivity analysis. All these factors limit the overall transparency of the studies, greater acceptance of their results and applicability to diverse and possibly resourcelimited environments where these approaches could be expected to have the greater impact.

Economic Perspectives on Personalized Health Care and Prevention

The objective of this paper is to provide an overview of economic evaluation of personalized medicine, focusing particularly on the use of cost-effectiveness analysis and other methods of valuation. We draw on insights from the literature and our work at the University of California, San Francisco Center for Translational and Policy Research on Personalized Medicine (TRANSPERS). We begin with a discussion of why personalized medicine is of interest and challenges to adoption, whether personalized medicine is different enough to require different evaluation approaches, and what is known about the economics of personalized medicine. We then discuss insights from TRANSPERS research and six areas for future research: Develop and Apply Multiple Methods of Assessing Value Identify Key Factors in Determining the Value of Personalized Medicine Use Real World Perspectives in Economic Analyses Consider Patient Heterogeneity and Diverse Populations in Economic Analyses Prepare for Upcoming Challenges of Assessing Value of Emerging Technologies Incorporate Behavioral Economics into Value Assessments.

Pharmacometabonomics and personalized medicine

BACKGROUND

Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics.

METHODS

A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmaco-metabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013.

RESULTS

Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals.

CONCLUSIONS

Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.

An evaluation of pharmacists’ expectations towards pharmacogenomics

Background: Given their expertise in pharmacotherapy, pharmacists are well positioned to play a leading role in the implementation of pharmacogenomics in clinical practice. However, little is known about the opinions of pharmacists towards pharmacogenomics or their willingness to integrate this new field in their practice. Methods: We conducted a survey of 284 pharmacists practicing in the province of Québec (Canada) to describe the opinions, expectations and concerns of pharmacists toward pharmacogenomics. Results: Pharmacists were very hopeful regarding the potential role of pharmacogenomics. Moreover, more than 95% of responders would be willing to recommend pharmacogenomic testing. Nevertheless, only 7.7% of pharmacists currently felt comfortable advising patients based on pharmacogenomic test results. Accordingly, the majority of responders (96.6%) indicated that they would like to undertake continuing education related to pharmacogenomics. Conclusion: Pharmacists are extremely hopeful towards pharmacogenomic testing. Furthermore, a vast majority is willing to integrate these tests as part of their clinical practice. Proper education will be required if the integration of pharmacogenomics in patient care is to be optimal.

Original submitted 21 September 2012; Revision submitted 16 November 2012

Biomarkers in drug development and regulation: a paradigm for clinical implementation of personalized medicine

The post-genomic era has been hallmarked by significant enthusiasm for therapeutic individualization through the use of pharmacogenomic and other biomarkers. This enthusiasm has been dampened by limited examples of widespread clinical adoption. The current clinical implementation paradigm may not be adequate to facilitate uptake of pharmacogenetics for a variety of reasons. This paper discusses certain limitations of the classical clinical implementation paradigm and describes the drug development paradigm as an additional, powerful mechanism to facilitate clinical implementation of individualized therapeutics.