Challenges of Incorporating Life Cycle Drug Pricing in Cost-Effectiveness Models: A Review of Methods and Modeling Suggestions

OBJECTIVES

This study aimed to conduct a review of existing methods used to incorporate life cycle drug pricing (LCDP) in cost-effectiveness analyses (CEAs), identify common methodological challenges, and suggest modeling approaches for prospectively implementing LCDP in CEA.

METHODS

Two complementary searches were conducted in PubMed, combined with hand searching and reference mining, to identify English language full-text articles that explored (1) how drug prices change over time and (2) methods used to apply dynamic pricing in cost-effectiveness models (CEMs). Relevant articles were reviewed, and authors discussed the common methodological practices used in the literature and their associated challenges on prospectively implementing LCDP in CEMs. For each key challenge identified, we provide modeling suggestions to address the issue.

RESULTS

We screened 1200 studies based on title and abstract; 117 were reviewed for eligibility, and 47 individual studies were included across both searches. Variations in prices over a product's life cycle are complex and multifactorial, and models applying LCDP in CEA varied in their methodology. We identified 4 key challenges to modeling LCDP in CEA, including how to model price trends before and after loss of exclusivity, how to capture the effect of price changes on future patient cohorts, and how to report results.

CONCLUSION

Accurately quantifying the impact of LCDP requires careful consideration of multiple aspects pertaining to both the evolution of drug prices and how to reflect these in CEA. Although uncertainties remain, our findings can aid implementation and evaluation of LCDP in economic evaluations.

Surrogacy and the Valuation of ATMPs: Taking Our Place in the Evidence Generation/Assessment Continuum

Medical technology is advancing rapidly, but established methods for health technology assessment are struggling to keep up. This challenge is particularly stark for the assessment of advanced therapy medicinal products-therapies often launched on the basis of single-arm studies powered to a surrogate primary endpoint. The most robust surrogacy methods investigate trial-level correlations between the treatment effect on the surrogate and the outcome of ultimate interest. However, these methods are often impossible with the evidence usually available for advanced therapy medicinal products at the time of the launch (randomized controlled trials are necessary for these advanced methods). Additionally, these surrogacy relationships are usually considered to be technology specific, adding uncertainty for any approach that primarily relies on historic data to estimate the surrogacy relationship for novel interventions such as advanced therapy medicinal products. The literature has already highlighted the need for early dialogue, staged assessment processes, and pricing arrangements that responsibly share the risk between the manufacturer and payer. However, it is our view that in addition to these critical developments, the modeling methods employed could also improve. Currently, health technology assessment practitioners typically either ignore the surrogate and simply extrapolate the endpoint of greatest patient relevance irrespective of the degree of maturity or assume historic surrogate relationships apply to the novel technology. In this opinion piece, we outline an additional avenue. By drawing on the understanding of the mechanism of action and insights generated earlier in the evidence generation/assessment continuum, cost-effectiveness modelers can make better use of the wider data available. These efforts are expected to reduce uncertainty at the time of the initial launch of pharmaceutical products and increase the value of subsequent data collection efforts.

R and Shiny for Cost-Effectiveness Analyses: Why and When? A Hypothetical Case Study

INTRODUCTION

Health economics models are typically built in Microsoft Excel^® owing to its wide familiarity, accessibility and perceived transparency. However, given the increasingly rapid and analytically complex decision-making needs of both the pharmaceutical industry and the field of health economics and outcomes research (HEOR), the demands of cost-effectiveness analyses may be better met by the programming language R.

OBJECTIVE

This case study provides an explicit comparison between Excel and R for contemporary cost-effectiveness analysis.

METHODS

We constructed duplicate cost-effectiveness models using Excel and R (with a user interface built using the Shiny package) to address a hypothetical case study typical of contemporary health technology assessment.

RESULTS

We compared R and Excel versions of the same model design to determine the advantages and limitations of the modelling platforms in terms of (i) analytical capability, (ii) data safety, (iii) building considerations, (iv) usability for technical and non-technical users and (v) model adaptability.

CONCLUSIONS

The findings of this explicit comparison are used to produce recommendations for when R might be more suitable than Excel in contemporary cost-effectiveness analyses. We conclude that selection of appropriate modelling software needs to consider case-by-case modelling requirements, particularly (i) intended audience, (ii) complexity of analysis, (iii) nature and frequency of updates and (iv) anticipated model run time.

"Stick or Twist?" Negotiating Price and Data in an Era of Conditional Approval

BACKGROUND

Changes in the regulatory context enable faster approval of transformative medicines. They also lead to health technology assessment (HTA) agencies having to make decisions with less evidence. In response, HTA agencies have also initiated forms of conditional approval. When the evidence base for a new oncology treatment leaves substantial uncertainty, the new Cancer Drugs Fund allows the National Institute for Heath and Care Excellence to give the manufacturer two options: (1) offer a low price based on conservative assumptions and obtain immediate approval ("stick") or (2) wait until the evidence base has further matured before finalizing a potentially higher agreed price ("twist").

OBJECTIVES

The purpose of this article is to explain how, using the theoretical framework of the expected value of sample information, simulation methods can help inform a manufacturer's decisions when faced with the option to stick or twist.

METHODS

We first summarize a general model to help frame the manufacturer's negotiating strategy. We then use a motivating case study, based on a hypothetical immunotherapy, to illustrate how manufacturers can use simulation methods to robustly characterize the uncertainty inherent to further data collection and incorporate this uncertainty within their decision making.

RESULTS

Our approach allows us to estimate the commercial value of generating additional data (the difference between the estimated net present value of stick and twist). We test the sensitivity of the results to different assumptions via scenario analyses.

CONCLUSIONS

This article shows that simulation methods can be used to help pharmaceutical managers make informed strategic decisions in contexts of uncertainty.

Economic evaluation in chronic pain: a systematic review and de novo flexible economic model

There is unmet need in patients suffering from chronic pain, yet innovation may be impeded by the difficulty of justifying economic value in a field beset by data limitations and methodological variability. A systematic review was conducted to identify and summarise the key areas of variability and limitations in modelling approaches in the economic evaluation of treatments for chronic pain. The results of the literature review were then used to support the development of a fully flexible open-source economic model structure, designed to test structural and data assumptions and act as a reference for future modelling practice. The key model design themes identified from the systematic review included: time horizon; titration and stabilisation; number of treatment lines; choice/ordering of treatment; and the impact of parameter uncertainty (given reliance on expert opinion). Exploratory analyses using the model to compare a hypothetical novel therapy versus morphine as first-line treatments showed cost-effectiveness results to be sensitive to structural and data assumptions. Assumptions about the treatment pathway and choice of time horizon were key model drivers. Our results suggest structural model design and data assumptions may have driven previous cost-effectiveness results and ultimately decisions based on economic value. We therefore conclude that it is vital that future economic models in chronic pain are designed to be fully transparent and hope our open-source code is useful in order to aspire to a common approach to modelling pain that includes robust sensitivity analyses to test structural and parameter uncertainty.

Cost effectiveness of renal denervation therapy for the treatment of resistant hypertension in the UK

BACKGROUND

Patients with resistant hypertension are at a high risk for developing serious cardiovascular events and renal complications. Catheter-based renal denervation (RDN) is a procedure with the potential to normalize systolic blood pressure (SBP).

OBJECTIVE

The overall objective of the study was to estimate the cost effectiveness of RDN in the UK for patients with diagnosed resistant hypertension, expressed as a standard cost per quality-adjusted life-year (QALY) ratio.

METHODS

A patient lifetime, economic, Markov heath-state model was developed, linking expected changes in SBP to reductions in risks for cardiovascular events and renal complications, using the Framingham, PROCAM, and other published risk equations. The model was developed from the perspective of the healthcare payer in the UK using relevant cost data from 2012. Clinical effectiveness for RDN (a mean reduction of 32 mmHg in SBP) was taken from the phase III Symplicity HTN-2 trial, in patients with a mean baseline SBP of 178 mmHg. HTN-2 was the largest, multicenter randomized controlled trial on the effectiveness of RDN therapy at the time of the model development. A systematic review identified UK-specific sources for utility, mortality, and cost parameter values, and included recently published UK guidelines for the clinical management of hypertension.

RESULTS

RDN therapy resulted in an increase in health benefit over a patient's lifetime compared with anti-hypertensive pharmacological treatment alone (12.77 vs. 12.16 QALYs; discounted). Additional lifetime costs per patient were modeled at £2,961; equivalent to an incremental cost per additional QALY of £4,805. This result was robust to full probabilistic sensitivity and scenario analyses.

CONCLUSION

RDN is an effective clinical procedure that offers patients a meaningful and cost-effective alternative for achieving SBP control, where traditional combination, anti-hypertensive pharmacologic strategies have been proven to be ineffective.

A cost-utility analysis of degarelix in the treatment of advanced hormone-dependent prostate cancer in the United Kingdom

OBJECTIVE

To determine the cost-effectiveness of the treatment of advanced hormone-dependent prostate cancer with degarelix compared to luteinizing hormone-releasing hormone (LHRH) agonists in the UK using the latest available evidence and the model submitted to AWMSG.

METHODS

A cost-effectiveness model was developed from the perspective of the UK National Health Service evaluating monthly injection of degarelix against 3-monthly leuprorelin therapy plus anti-androgen flare cover for the first-line treatment of patients with advanced (locally advanced or metastatic) hormone-dependent prostate cancer. A Markov process model was constructed using the patient population characteristics and efficacy information from the CS21 Phase III clinical trial and associated extension study (CS21A). The intention-to-treat (ITT) population and a high-risk sub-group with a PSA level >20 ng/mL were modeled.

RESULTS

In the base-case analysis using the patient access scheme (PAS) price, degarelix was dominant compared to leuprorelin with cost savings of £3633 in the ITT population and £4310 in the PSA > 20 ng/mL sub-group. The chance of being cost-effective was 95% in the ITT population and 96% in the PSA > 20 ng/mL sub-group at a threshold of £20,000 per quality-adjusted life-year (QALY). In addition, degarelix remained dominant when PSA progression was assumed equal and only the benefits of preventing testosterone flare were taken into account. Treatment with degarelix also remained dominant in both populations when the list price was used. The additional investment required to treat patients with degarelix could be offset in 19 months for the ITT population and 13 months for the PSA > 20 ng/mL population. The model was most sensitive to the hazard ratio assumed for PSA progression between degarelix and leuprorelin and the quality-of-life (utility) of patients receiving palliative care.

CONCLUSION

Degarelix is likely to be cost-effective compared to leuprorelin plus anti-androgen flare cover in the first-line treatment of advanced hormone-dependent prostate cancer.

A comparison of the cost-effectiveness of treatment of prolonged acute convulsive epileptic seizures in children across Europe

In the majority of children and adolescents with epilepsy, optimal drug therapy adequately controls their condition. However, among the remaining patients who are still uncontrolled despite mono-, bi- or tri-therapy with chronic anti-epileptic treatment, a rescue medication is required. In Western Europe, the licensed medications available for first-line treatment of prolonged acute convulsive seizures (PACS) vary widely, and so comparators for clinical and economic evaluation are not consistent. No European guidelines currently exist for the treatment of PACS in children and adolescents and limited evidence is available for the effectiveness of treatments in the community setting. The authors present cost-effectiveness data for BUCCOLAM® (midazolam oromucosal solution) for the treatment of PACS in children and adolescents in the context of the treatment pathway in seven European countries in patients from 6 months to 18 years. For each country, the health economic model consisted of a decision tree, with decision nodes informed by clinical data and expert opinion obtained via a Delphi methodology. The events modelled are those associated with a patient experiencing a seizure in the community setting. The model assessed the likelihood of medication being administered successfully and of seizure cessation. The associated resource use was also modelled, and ambulance call-outs and hospitalisations were considered. The patient's quality of life was estimated by clinicians, who completed a five-level EuroQol five dimensions questionnaire from the perspective of a child or adolescent suffering a seizure. Despite differences in current therapy, treatment patterns and healthcare costs in all countries assessed, BUCCOLAM was shown to be cost saving and offered increased health-related benefits for patients in the treatment of PACS compared with the current local standard of care.

Estimating the critical and sensitive periods of investment in early childhood: a methodological note

The identification of critical periods in early human development requires statistical analyses beyond simple cross tabulation of correlations of observed variables. This paper provides an overview of different quantitative methods available for the statistical analysis of longitudinal data regarding child development, and in particular the identification of critical and sensitive periods for later abilities. It draws heavily on the work on human skill formation developed by the economist James Heckman, which treats ability as a latent variable and explains its formation through the simultaneous estimation of structural equations of investments and achieved abilities across time. We distinguish between two specifications of the ability formation function. One of them (the 'recursive') format explains current ability as a function of the ability and investment at the immediately preceding period. The other (the 'non-recursive') format explains current ability as a function of a series of past investments. In order to fully examine critical and sensitive periods of investments, the non-recursive formulation needs to be used. Furthermore, true abilities of an individual cannot be directly observed: what we observe are the test scores, for example, on reading and writing. We outline an approach, structural equation modelling, that treats actual test scores as measurements of the latent ability variable, and show how it can be used in the recursive and non-recursive formulation. In order to fully examine critical and sensitive periods of investments, we argue that the non-recursive formulation of this structural model is necessary. However, the non-recursive formulation requires more data than the recursive formulation, and to the best of our knowledge, has never been used in the identification of critical and sensitive periods in early childhood development.

The cost effectiveness of licensed oromucosal midazolam (Buccolam(®)) for the treatment of children experiencing acute epileptic seizures: an approach when trial evidence is limited

BACKGROUND

In the UK, two treatment options are used for acute epileptic seizures in the community-rectal diazepam and unlicensed buccal midazolam. In practice, the former is rarely used, with unlicensed buccal midazolam being widely recommended and prescribed by physicians. In September 2011, Buccolam(®) (licensed midazolam oromucosal solution) became the first medicine to receive a Paediatric-Use Marketing Authorization (PUMA) and it is indicated for the treatment of prolonged, acute, convulsive seizures by caregivers in the community for children (aged 6 months to <18 years) diagnosed with epilepsy. The approval process for a PUMA product differs from other marketing authorization processes and may be based upon small population subsets and may not, in some cases, require new safety or efficacy data to be generated; a similar situation to that seen for orphan drugs. This can lead to challenges when conducting economic evaluations.

OBJECTIVE

The aim of this study was to assess the cost effectiveness of Buccolam(®) for children with a diagnosis of epilepsy suffering prolonged, acute, convulsive seizures occurring in the UK community setting. DESIGN AND PERSPECTIVE: A hybrid model was developed according to a UK payer perspective. The model included a time-to-event simulation for the frequency and location of occurrence of seizures, along with a decision-tree model that assessed the treatment pathway when a seizure occured. The model compared treatment with Buccolam(®) with standard care in the community (95 % unlicensed buccal midazolam and 5 % rectal diazepam) or either treatment alone. The model was informed by data from a variety of sources, including clinical effectiveness estimates, and costs based on published UK data, using 2012-13 prices, where possible. To determine current practice and real-world effectiveness, a Delphi panel and a survey of parents of children with epilepsy were conducted.

RESULTS

Buccolam(®) showed a reduction in costs of £2,939 compared with standard care, £14,269 compared with rectal diazepam alone and £886 compared with unlicensed buccal midazolam alone. Increases of 0.025, 0.082 and 0.013 quality-adjusted life-years, respectively, were also seen. Buccolam(®) remained dominant across a range of scenario analyses.

CONCLUSION

This model demonstrates the possibility of constructing a thorough economic case when trial or real-world data are not available. The results of the model show Buccolam(®) to be cost saving compared with rectal diazepam due to a reduction in the need for ambulance callouts and hospital stays, and compared with unlicensed buccal midazolam, through reduced drug costs and wastage.