Convergence yet Continued Complexity: A Systematic Review and Critique of Health Economic Models of Relapsing-Remitting Multiple Sclerosis in the United Kingdom

An Innovative Approach to Modelling the Optimal Treatment Sequence for Patients with Relapsing-Remitting Multiple Sclerosis: Implementation, Validation, and Impact of the Decision-Making Approach

INTRODUCTION

An innovative computational model was developed to address challenges regarding the evaluation of treatment sequences in patients with relapsing-remitting multiple sclerosis (RRMS) through the concept of a 'virtual' physician who observes and assesses patients over time. We describe the implementation and validation of the model, then apply this framework as a case study to determine the impact of different decision-making approaches on the optimal sequence of disease-modifying therapies (DMTs) and associated outcomes.

METHODS

A patient-level discrete event simulation (DES) was used to model heterogeneity in disease trajectories and outcomes. The evaluation of DMT options was implemented through a Markov model representing the patient's disease; outcomes included lifetime costs and quality of life. The DES and Markov models underwent internal and external validation. Analyses of the optimal treatment sequence for each patient were based on several decision-making criteria. These treatment sequences were compared to current treatment guidelines.

RESULTS

Internal validation indicated that model outcomes for natural history were consistent with the input parameters used to inform the model. Costs and quality of life outcomes were successfully validated against published reference models. Whereas each decision-making criterion generated a different optimal treatment sequence, cladribine tablets were the only DMT common to all treatment sequences. By choosing treatments on the basis of minimising disease progression or number of relapses, it was possible to improve on current treatment guidelines; however, these treatment sequences were more costly. Maximising cost-effectiveness resulted in the lowest costs but was also associated with the worst outcomes.

CONCLUSIONS

The model was robust in generating outcomes consistent with published models and studies. It was also able to identify optimal treatment sequences based on different decision criteria. This innovative modelling framework has the potential to simulate individual patient trajectories in the current treatment landscape and may be useful for treatment switching and treatment positioning decisions in RRMS.

How have Economic Evaluations in Relapsing Multiple Sclerosis Evolved Over Time? A Systematic Literature Review

INTRODUCTION

The introduction of disease-modifying therapies (DMTs) for relapsing multiple sclerosis (RMS) over the last two decades has prompted the economic assessments of these treatments by reimbursement authorities. The aim of this systematic literature review was to evaluate the modeling approach and data sources used in economic evaluations of DMTs for RMS, identify differences and similarities, and explore how economic evaluation models have evolved over time.

METHODS

MEDLINE®, Embase®, and EBM Reviews databases were searched using Ovid® Platform from database inception on 25 December 2019 and subsequently updated on 17 February 2021. In addition, health technology assessment agency websites, key conference proceedings, and gray literature from relevant websites were screened. The quality of included studies was assessed using the Drummond and Philips checklists.

RESULTS

A total 155 publications and 30 Health Technology Assessment (HTA) reports were included. Most of these were cost-utility analysis (73 studies and 25 HTA reports) and funded by medicines manufacturers (n = 65). The top three countries where studies were conducted were the USA (n = 29), the UK (n = 16), and Spain (n = 10). Studies predominantly used Markov cohort models (94 studies; 25 HTAs) structured based on the Expanded Disability Status Scale (EDSS) with 21 health states (20 studies; 12 HTA reports). The London Ontario and British Columbia data sets were commonly used sources for natural history data (n = 33; n = 13). Twelve studies and ten HTAs from the UK assumed a waning of DMT effect over the long term, while this was uncommon in studies from other countries. Nineteen studies adjusted for multiple sclerosis (MS)-specific mortality estimates, while 18 studies used data from the national life table without adjustment. Studies prominently referred to mortality data that were about two decades old. The data on treatment effect was generally obtained from randomized controlled trials (43 studies; 7 HTAs) or from published evidence synthesis (23 studies; 24 HTAs). Utility estimates were derived from either published studies and/or supplemented with data from RCTs. Most of the models used the lifetime horizon (n = 37) with a 1-year cycle length (n = 63).

CONCLUSION

As expected, similarities as well as differences were observed across the different economic models. Available evidence suggests models should continue using the Markov cohort model with 21 EDSS-based states, however, allowing the transition to a lower EDSS state and assuming a sustained treatment effect. With reference to the data sources, models should consider using a contemporary MS-specific mortality data, recent natural history data, and country-specific utility data if available. In case of data unavailability, a sensitivity analysis using multiple sources of data should be conducted. In addition, future models should incorporate other clinically relevant outcomes, such as the cognition, vision, and psychological aspects of RMS, to be able to present the comprehensive value of DMTs.

Modeling the Cost-Utility of Treatment Sequences for Multiple Sclerosis

OBJECTIVES

Most patients with multiple sclerosis (MS) switch between disease-modifying therapies (DMTs) during their lifetime. Our aim was to develop an MS cost-utility model that takes treatment switching into account to provide a more realistic estimate of treatment benefit than previous models that assume lifetime use of 1 DMT.

METHODS

A treatment sequence model using a microsimulation framework with a lifetime time horizon and a societal perspective was developed in R. Clinical plausibility and decision rules for switching were defined in consultation with Dutch MS neurologists. The ability of DMTs to prevent relapses and delay disease progression was modeled by applying DMT-specific estimates derived from a network meta-analysis of randomized controlled trials to natural history data. A total of 2 treatment strategies were compared: a first-line DMT sequence (peginterferon-glatiramer-teriflunomide-interferon-beta-dimethyl fumarate) and an escalation DMT sequence (peginterferon-glatiramer-ocrelizumab-natalizumab-alemtuzumab). Scenario analyses explored impact of alternative sources of natural history data, societal versus healthcare perspective, and condition-specific versus generic utilities. Predicted short-term switches (<5 years) were externally validated with Dutch claims data on DMT use.

RESULTS

Short-term switches predicted by the model compared well with Dutch claims data. Transition from relapsing-remitting MS to secondary progressive MS was delayed by the escalation sequence (24.7 vs 20.3 years on first-line sequence). Model results were sensitive to utility values and medical resource consumption was a large driver of uncertainty.

CONCLUSIONS

This microsimulation model overcomes the limitation of previous models by modeling treatment sequences. Because it better reflects clinical reality, it facilitates incorporating cost-utility information in clinical guidelines.

Predictors of Health Utility in Relapsing-Remitting and Secondary-Progressive Multiple Sclerosis: Implications for Future Economic Models of Disease-Modifying Therapies

BACKGROUND

Decision-analytic models used in economic evaluations of disease-modifying therapies for relapsing-remitting multiple sclerosis (RRMS) have characterized disease progression and accrue quality-adjusted life-years from utility values based on the Expanded Disability Status Scale (EDSS), the occurrence of relapses, and progression to secondary-progressive multiple sclerosis (SPMS). The EDSS, used to characterize disability progression, has several limitations. If the EDSS is the only disability measure used in economic evaluations, the long-term clinical and economic implications of disease-modifying therapies may not be properly assessed.

OBJECTIVE

The objective of this study was to explore if supplementary disability measures including the Timed 25-Foot Walk (T25FW), 9-Hole Peg Test (9HPT), and Paced Auditory Serial Addition Test (PASAT) significantly contribute additional information on health utility in RRMS and SPMS otherwise not captured by the EDSS and relapses and, therefore, should be considered in future economic evaluations of disease-modifying therapies.

METHODS

Short-Form Six-Dimension utility scores were derived from the RAND 36-Item Health Survey 1.0 individual-level data available in the Multiple Sclerosis Outcome Assessment Consortium (MSOAC) Placebo Database. Repeated-measures mixed-effects models were conducted to estimate the effects of EDSS, T25FW, 9HPT (dominant and non-dominant hand), PASAT, and relapses on changes in utility over time, controlling for demographics.

RESULTS

A higher level of EDSS, longer time to complete the T25FW test, and a recent relapse were significant predictors of lower utility in people with RRMS and SPMS. 9HPT and PASAT were not significant predictors.

CONCLUSIONS

This study suggests that in addition to EDSS and recent relapses, T25FW significantly predicts utility in RRMS and SPMS. These findings support the use of T25FW to supplement the EDSS and the occurrence of relapses to characterize the course of disease progression and to more accurately accrue quality-adjusted life-years in future economic evaluations of disease-modifying therapies for the treatment of RRMS.

Quantitative Evidence Synthesis Methods for the Assessment of the Effectiveness of Treatment Sequences for Clinical and Economic Decision Making: A Review and Taxonomy of Simplifying Assumptions

Sequential use of alternative treatments for chronic conditions represents a complex intervention pathway; previous treatment and patient characteristics affect both the choice and effectiveness of subsequent treatments. This paper critically explores the methods for quantitative evidence synthesis of the effectiveness of sequential treatment options within a health technology assessment (HTA) or similar process. It covers methods for developing summary estimates of clinical effectiveness or the clinical inputs for the cost-effectiveness assessment and can encompass any disease condition. A comprehensive review of current approaches is presented, which considers meta-analytic methods for assessing the clinical effectiveness of treatment sequences and decision-analytic modelling approaches used to evaluate the effectiveness of treatment sequences. Estimating the effectiveness of a sequence of treatments is not straightforward or trivial and is severely hampered by the limitations of the evidence base. Randomised controlled trials (RCTs) of sequences were often absent or very limited. In the absence of sufficient RCTs of whole sequences, there is no single best way to evaluate treatment sequences; however, some approaches could be re-used or adapted, sharing ideas across different disease conditions. Each has advantages and disadvantages, and is influenced by the evidence available, extent of treatment sequences (number of treatment lines or permutations), and complexity of the decision problem. Due to the scarcity of data, modelling studies applied simplifying assumptions to data on discrete treatments. A taxonomy for all possible assumptions was developed, providing a unique resource to aid the critique of existing decision-analytic models.

Desirability and acceptability of a treatment-sequencing model in relapsing-remitting multiple sclerosis: A health technology assessment perspective

OBJECTIVE

Gather health technology assessment (HTA) experts' insights on the desirability and acceptability of treatment-sequencing models applied to relapsing-remitting multiple sclerosis (RRMS).

DATA SOURCE/STUDY SETTING

Primary data.

STUDY DESIGN

In-depth double-blind semi-structured telephone interviews.

DATA COLLECTION/EXTRACTION METHODS

General themes were extracted from qualitative interviews.

PRINCIPAL FINDINGS

Although experts confirmed the importance of evaluating the clinical and cost-effectiveness of treatments as part of a sequence, the current HTA decision making framework is not conducive to this. Developing an RRMS treatment-sequencing model that meets HTA requirements is difficult, in particular due to scarcity of effectiveness data in later treatment lines.

CONCLUSIONS

At present, a treatment-sequencing model for RRMS may be desirable yet not requested by HTA bodies for their decision making. However, there could be other areas where a treatment-sequencing model for RRMS is of use.

Modified Delphi study of decision-making around treatment sequencing in relapsing-remitting multiple sclerosis

BACKGROUND AND PURPOSE

Existing effectiveness models of disease-modifying drugs (DMDs) for relapsing-remitting multiple sclerosis (RRMS) evaluate a single line of treatment; however, RRMS patients often receive more than one lifetime DMD. To develop treatment sequencing models grounded in clinical reality, a detailed understanding of the decision-making process regarding DMD switching is required. Using a modified Delphi approach, this study attempted to reach consensus on modelling assumptions.

METHODS

A modified Delphi technique was conducted based on three rounds of discussion amongst an international group of 10 physicians with expertise in RRMS.

RESULTS

The panel agreed that the expected time from disease onset to Expanded Disability Status Scale 6.0 is a proxy for disease severity as well as suitable for classifying severity into three groups. A modelled clinical decision rule regarding the timing of switching should contain at least the time between relapses, magnetic resonance imaging outcomes and the occurrence/risk of adverse events. The experts agreed that the assessment of adverse event risk for a DMD is dependent on disease severity, with more risks accepted when the patient's disease is more severe. The effectiveness of DMDs conditional on their position in a sequence and/or disease duration was discussed: there was consensus on some statements regarding this topic but these were accompanied by a high degree of uncertainty due to considerable knowledge gaps.

CONCLUSION

Useful insights into the medical decision-making process regarding treatment sequencing in RRMS were obtained. The knowledge gained has been used to validate the main modelling concepts and to further generate clinically meaningful results.

Pharmacoeconomics of synthetic therapies for multiple sclerosis

Introduction: Recently, the economic impact of multiple sclerosis (MS), which includes both direct and indirect costs, has been increasing. While direct costs comprise health-care costs, such as the cost of pharmaceuticals, additional treatments such as physiotherapy, and medical aids, indirect costs are triggered by the productivity loss of patients and caregivers. Although new drugs for MS have changed the therapeutic scenario, they have increased the direct costs of health-care services. Areas covered: This review describes the pharmacoeconomic aspects of synthetic therapies for MS. Additionally, it discusses the economic impact of the various classes of licensed disease-modifying treatments (DMTs) for relapsing forms of MS. Expert opinion: The emerging and more expensive DMTs for MS represent a considerable challenge for health-care systems and resource consumption. Future research should focus on the long-term efficacy of DMTs and the cost of treating MS in a real-life setting. Future biological and radiological biomarkers could help stratify patients at early stages of MS, helping physicians design a personalized therapeutic approach that could have a positive impact in economic terms.

Modeling Approaches in Cost-Effectiveness Analysis of Disease-Modifying Therapies for Relapsing-Remitting Multiple Sclerosis: An Updated Systematic Review and Recommendations for Future Economic Evaluations

BACKGROUND

Numerous cost-effectiveness analyses (CEAs) of disease-modifying therapies (DMTs) for relapsing-remitting multiple sclerosis (RRMS) have been published in the last three decades. Literature reviews of the modeling methods and results from these CEAs have also been published. The last literature review that focused on modeling methods, without country or time horizon in the inclusion criteria, included studies published up to 2012. Since then, new DMTs have become available, and new models and data sources have been used to assess their cost effectiveness.

OBJECTIVE

The aim of this systematic review was to provide a detailed and comprehensive description of the relevant aspects of economic models used in CEAs of DMTs for RRMS, to understand how these models have progressed from recommendations provided in past reviews, what new approaches have been developed, what issues remain, and how they could be addressed.

METHODS

EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), the National Health System (NHS) Economic Evaluations Database, the Health Technology Assessment (HTA) Database, and EconLit were searched for cost-effectiveness studies of DMTs for RRMS that used decision-analytic models, published in English between 1 January 2012 and 24 December 2017. The inclusion criteria were as follows: being a full economic evaluation, a decision-analytic model was used, the target population concerned adult patients with RRMS, and being available in full-text format. Studies were not excluded based on the methodological quality. The background information of the included studies, as well as specific information on the components of the economic models related to the areas of recommendation from previous reviews were extracted.

RESULTS

Twenty-three studies from ten countries were included. The model structure of these studies has converged over time, characterizing the course of disease progression in terms of changes in disability and the occurrence of relapses over time. Variations were found in model approach; data sources for the natural course of the disease and comparative efficacy between DMTs; number of lines of treatment modeled; long-term efficacy waning and treatment discontinuation assumptions; type of withdrawal; and criteria for selecting adverse events. Main areas for improvement include using long-term time horizons and societal perspective; reporting relevant health outcomes; conducting scenario analyses using different sources of natural history and utility values; and reporting how the model was validated.

CONCLUSION

The structure of economic models used in CEAs of DMTs for RRMS has converged over time. However, variation remains in terms of model approach, inputs, and assumptions. Though some recommendations from previous reviews have been incorporated in later models, areas for improvement remain.

When does economic model type become a decisive factor in health technology appraisals? Learning from the expanding treatment options for relapsing-remitting multiple sclerosis

OBJECTIVES

Specific economic model types often become de facto standard for health technology appraisal over time. Markov and discrete event simulation (DES) models were compared to investigate the impact of innovative modeling on the cost-effectiveness of disease-modifying therapies (DMTs) in relapsing-remitting multiple sclerosis (RRMS). Fingolimod was compared to dimethyl fumarate (DMF; in highly active [HA] RRMS), alemtuzumab (in HA RRMS) and natalizumab (in rapidly evolving severe RRMS). Comparator DMTs were chosen to reflect different dosing regimens.

MATERIALS AND METHODS

Markov and DES models used have been published previously. Inputs were aligned in all relevant respects, with differences in the modeling of event-triggered attributes, such as relapse-related retreatment, which is inherently difficult with a memoryless Markov approach. Outcomes were compared, with and without different attributes.

RESULTS

All results used list prices. For fingolimod and DMF, incremental cost-effectiveness ratios (ICERs) were comparable (Markov: £4206/quality-adjusted life year [QALY] gained versus DES: £3910/QALY gained). Deviations were observed when long-term adverse events (AEs) were incorporated in the DES (Markov: £25,412 saved/QALY lost, versus DES: £34,209 saved/QALY lost, fingolimod versus natalizumab; higher ICERs indicate greater cost-effectiveness). For fingolimod versus alemtuzumab, when relapse-triggered retreatment was included in the DES, large cost differences were observed (difference between incremental cost is £35,410 and QALY is 0.10).

LIMITATIONS

UK payer perspective, therefore societal approach was not considered. Resource utilization and utilities for both models were not derived from the subpopulations; as the focus is on model type, input limitations that apply to both models are less relevant.

CONCLUSIONS

Whilst no model can fully represent a disease, a DES allows an opportunity to include features excluded in a Markov structure. A DES may be more suitable for modeling in RRMS for health technology assessment purposes given the complexity of some DMTs. This analysis highlights the capabilities of different model structures to model event-triggered attributes.

Clinical effectiveness and cost-effectiveness of beta-interferon and glatiramer acetate for treating multiple sclerosis: systematic review and economic evaluation

BACKGROUND

At the time of publication of the most recent National Institute for Health and Care Excellence (NICE) guidance [technology appraisal (TA) 32] in 2002 on beta-interferon (IFN-β) and glatiramer acetate (GA) for multiple sclerosis, there was insufficient evidence of their clinical effectiveness and cost-effectiveness.

OBJECTIVES

To undertake (1) systematic reviews of the clinical effectiveness and cost-effectiveness of IFN-β and GA in relapsing-remitting multiple sclerosis (RRMS), secondary progressive multiple sclerosis (SPMS) and clinically isolated syndrome (CIS) compared with best supportive care (BSC) and each other, investigating annualised relapse rate (ARR) and time to disability progression confirmed at 3 months and 6 months and (2) cost-effectiveness assessments of disease-modifying therapies (DMTs) for CIS and RRMS compared with BSC and each other.

REVIEW METHODS

Searches were undertaken in January and February 2016 in databases including The Cochrane Library, MEDLINE and the Science Citation Index. We limited some database searches to specific start dates based on previous, relevant systematic reviews. Two reviewers screened titles and abstracts with recourse to a third when needed. The Cochrane tool and the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) and Philips checklists were used for appraisal. Narrative synthesis and, when possible, random-effects meta-analysis and network meta-analysis (NMA) were performed. Cost-effectiveness analysis used published literature, findings from the Department of Health's risk-sharing scheme (RSS) and expert opinion. A de novo economic model was built for CIS. The base case used updated RSS data, a NHS and Personal Social Services perspective, a 50-year time horizon, 2014/15 prices and a discount rate of 3.5%. Outcomes are reported as incremental cost-effectiveness ratios (ICERs). We undertook probabilistic sensitivity analysis.

RESULTS

In total, 6420 publications were identified, of which 63 relating to 35 randomised controlled trials (RCTs) were included. In total, 86% had a high risk of bias. There was very little difference between drugs in reducing moderate or severe relapse rates in RRMS. All were beneficial compared with BSC, giving a pooled rate ratio of 0.65 [95% confidence interval (CI) 0.56 to 0.76] for ARR and a hazard ratio of 0.70 (95% CI, 0.55 to 0.87) for time to disability progression confirmed at 3 months. NMA suggested that 20 mg of GA given subcutaneously had the highest probability of being the best at reducing ARR. Three separate cost-effectiveness searches identified > 2500 publications, with 26 included studies informing the narrative synthesis and model inputs. In the base case using a modified RSS the mean incremental cost was £31,900 for pooled DMTs compared with BSC and the mean incremental quality-adjusted life-years (QALYs) were 0.943, giving an ICER of £33,800 per QALY gained for people with RRMS. In probabilistic sensitivity analysis the ICER was £34,000 per QALY gained. In sensitivity analysis, using the assessment group inputs gave an ICER of £12,800 per QALY gained for pooled DMTs compared with BSC. Pegylated IFN-β-1 (125 µg) was the most cost-effective option of the individual DMTs compared with BSC (ICER £7000 per QALY gained); GA (20 mg) was the most cost-effective treatment for CIS (ICER £16,500 per QALY gained).

LIMITATIONS

Although we built a de novo model for CIS that incorporated evidence from our systematic review of clinical effectiveness, our findings relied on a population diagnosed with CIS before implementation of the revised 2010 McDonald criteria.

CONCLUSIONS

DMTs were clinically effective for RRMS and CIS but cost-effective only for CIS. Both RCT evidence and RSS data are at high risk of bias. Research priorities include comparative studies with longer follow-up and systematic review and meta-synthesis of qualitative studies.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016043278.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Disease-Modifying Therapies for Multiple Sclerosis: A Systematic Literature Review of Cost-Effectiveness Studies

INTRODUCTION AND OBJECTIVE

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. MS is considered incurable; however, disease treatment has advanced significantly over the past several decades with the introduction of disease-modifying therapies (DMTs). The current study reviewed the cost-effectiveness analyses of DMTs in relapsing-remitting MS (RRMS) patients.

METHODS

A systematic literature search of bibliographic databases was conducted to identify economic evaluations published after 2007. The relevant population, intervention, comparators, outcomes, and study design (PICOS) were considered. The outcomes of interest were incremental cost-effectiveness ratios (ICERs), net monetary benefits, incremental benefits, and incremental costs. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement was used to assess the reporting quality of published studies.

RESULTS

A total of 1370 potentially relevant citations were identified, of which 33 published articles and four Health Technology Assessment (HTA) reports prepared for the UK were included in the final analysis. Almost all studies were based on a health economic model and considered RRMS as the phase of disease at study entry. The studies were conducted in 10 different countries, with approximately 50% based in the US. Study outcomes were rarely comparable due to the different settings, input data, and assumptions. Even within the same country, the discrepancy between study criteria was considerable. The compliance with reporting standards of the CHEERS statement was generally high.

CONCLUSIONS

Internationally, a large number of health economic assessments of DMTs in RRMS were available, yielding difficult to compare, and at times conflicting, results.

Replicating Health Economic Models: Firm Foundations or a House of Cards?

Health economic evaluation is a framework for the comparative analysis of the incremental health gains and costs associated with competing decision alternatives. The process of developing health economic models is usually complex, financially expensive and time-consuming. For these reasons, model development is sometimes based on previous model-based analyses; this endeavour is usually referred to as model replication. Such model replication activity may involve the comprehensive reproduction of an existing model or 'borrowing' all or part of a previously developed model structure. Generally speaking, the replication of an existing model may require substantially less effort than developing a new de novo model by bypassing, or undertaking in only a perfunctory manner, certain aspects of model development such as the development of a complete conceptual model and/or comprehensive literature searching for model parameters. A further motivation for model replication may be to draw on the credibility or prestige of previous analyses that have been published and/or used to inform decision making. The acceptability and appropriateness of replicating models depends on the decision-making context: there exists a trade-off between the 'savings' afforded by model replication and the potential 'costs' associated with reduced model credibility due to the omission of certain stages of model development. This paper provides an overview of the different levels of, and motivations for, replicating health economic models, and discusses the advantages, disadvantages and caveats associated with this type of modelling activity. Irrespective of whether replicated models should be considered appropriate or not, complete replicability is generally accepted as a desirable property of health economic models, as reflected in critical appraisal checklists and good practice guidelines. To this end, the feasibility of comprehensive model replication is explored empirically across a small number of recent case studies. Recommendations are put forward for improving reporting standards to enhance comprehensive model replicability.

Costs and effectiveness of fingolimod versus alemtuzumab in the treatment of highly active relapsing-remitting multiple sclerosis in the UK: re-treatment, discount, and disutility

OBJECTIVE

Patients with relapsing-remitting multiple sclerosis (RRMS) treated with disease modifying therapies (DMTs) who continue to experience disease activity may be considered for escalation therapies such as fingolimod, or may be considered for alemtuzumab. Previous economic modeling used Markov models; applying one alternative technique, discrete event simulation (DES) modeling, allows re-treatment and long-term adverse events (AEs) to be included in the analysis.

METHODS

A DES was adapted to model relapse-triggered re-treatment with alemtuzumab and the effect of including ongoing quality-adjusted life year (QALY) decrements for AEs that extend beyond previous 1-year Markov cycles. As the price to the NHS of fingolimod in the UK is unknown, due to a confidential patient access scheme (PAS), a variety of possible discounts were tested. The interaction of re-treatment assumptions for alemtuzumab with the possible discounts for fingolimod was tested to determine which DMT resulted in lower lifetime costs. The lifetime QALY results were derived from modeled treatment effect and short- and long-term AEs.

RESULTS

Most permutations of fingolimod PAS discount and alemtuzumab re-treatment rate resulted in fingolimod being less costly than alemtuzumab. As the percentage of patients who are re-treated with alemtuzumab due to experiencing a relapse approaches 100% of those who relapse whilst on treatment, the discount required for fingolimod to be less costly drops below 5%. Consideration of treatment effect alone found alemtuzumab generated 0.2 more QALYs/patient; the inclusion of AEs up to a duration of 1 year reduced this advantage to only 0.14 QALYs/patient. Modeling AEs with a lifetime QALY decrement found that both DMTs generated very similar QALYs with the difference only 0.04 QALYs/patient.

CONCLUSIONS

When the model captured alemtuzumab re-treatment and long-term AE decrements, it was found that fingolimod is cost-effective compared to alemtuzumab, assuming application of only a modest level of confidential PAS discount.

A discrete event simulation to model the cost-utility of fingolimod and natalizumab in rapidly evolving severe relapsing-remitting multiple sclerosis in the UK

OBJECTIVE

Two disease-modifying therapies are licensed in the EU for use in rapidly-evolving severe (RES) relapsing-remitting multiple sclerosis (RRMS), fingolimod and natalizumab. Here a discrete event simulation (DES) model to analyze the cost-effectiveness of natalizumab and fingolimod in the RES population, from the perspective of the National Health Service (NHS) in the UK, is reported.

METHODS

A DES model was developed to track individual RES patients, based on Expanded Disability Status Scale scores. Individual patient characteristics were taken from the RES sub-groups of the pivotal trials for fingolimod. Utility data were in line with previous models. Published costs were inflated to NHS cost year 2015. Owing to the confidential patient access scheme (PAS) discount applied to fingolimod in the UK, a range of discount levels were applied to the fingolimod list price, to capture the likelihood of natalizumab being cost-effective in a real-world setting.

RESULTS

At the lower National Institute of Health and Care Excellence (NICE) threshold of £20,000/quality-adjusted life year (QALY), fingolimod only required a discount greater than 0.8% of list price to be cost-effective. At the upper threshold of £30,000/QALY employed by the NICE, fingolimod was cost-effective if the confidential discount is greater than 2.5%. Sensitivity analyses conducted using fingolimod list-price showed the model to be most sensitive to changes in the cost of each drug, particularly fingolimod.

CONCLUSIONS

The DES model shows that only a modest discount to the UK fingolimod list-price is required to make fingolimod a more cost-effective option than natalizumab in RES RRMS.

Predictors of the 10-year direct costs for treating multiple sclerosis

OBJECTIVES

Disease-modifying treatments (DMTs) constitute the largest direct medical cost for multiple sclerosis (MS). This study aims at investigating predictors of the 10-year economic burden for DMT administration and management.

MATERIALS AND METHODS

This study included 537 newly diagnosed, drug naïve relapsing-remitting MS (RRMS) patients, followed up for 10.1±3.3 years. Costs for DMT administration and management were calculated, and referred to each year of observation (annual costs). Possible predictors of disease evolution were categorized into early predictors (age, gender, disease duration, baseline expanded disability status scale (EDSS), 1-point EDSS progression within 2 years, and annualized relapse rate -ARR- within 2 years), and long-term predictors (reaching of EDSS 4.0, conversion to secondary progressive -SP-, ARR, number of DMTs, follow-up duration). Association between predictors and study outcome was explored using mixed-effects log-linear regression models.

RESULTS

A 1-point higher EDSS at diagnosis was associated with 13.21% increase in the annual costs (95%CI=4.16-23.04%). Each additional year of age at diagnosis was associated with a 0.74% decrease in the annual costs (95%CI=-1.43 to-0.04%). Female gender was associated with a 12.43% decrease in the annual costs (95%CI=-22.61 to-0.93%). Converting to SP was associated with a 14.26% decrease in the annual costs (95%CI=-14.26 to-2.94%). Each additional year of follow-up was associated with a 3.05% decrease in the annual costs (95%CI=-4.51 to-1.57%).

CONCLUSIONS

An estimate of the 10-year costs associated with DMT administration and management can be calculated by analyzing different factors, and might be of particular interest for planning resources needed for treating people with MS.