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This study evaluated the cost-effectiveness of first-line treatments of relapsing–remitting multiple sclerosis (RRMS) (dimethyl fumarate [DMF] 240 mg PO BID, teriflunomide 14 mg once daily, glatiramer acetate 20 mg SC once daily, interferon [IFN]-β1a 44 µg TIW, IFN-β1b 250 µg EOD, and IFN-β1a 30 µg IM QW) and best supportive care (BSC) in the health care payer setting in Finland.
Methods
The primary outcome was the modeled incremental cost-effectiveness ratio (ICER; €/quality-adjusted life-year [QALY] gained, 3%/y discounting). Markov cohort modeling with a 15-year time horizon was employed. During each 1-year modeling cycle, patients either maintained the Expanded Disability Status Scale (EDSS) score or experienced progression, developed secondary progressive MS (SPMS) or showed EDSS progression in SPMS, experienced relapse with/without hospitalization, experienced an adverse event (AE), or died. Patients׳ characteristics, RRMS progression probabilities, and standardized mortality ratios were derived from a registry of patients with MS in Finland. A mixed-treatment comparison (MTC) informed the treatment effects. Finnish EuroQol Five-Dimensional Questionnaire, Three-Level Version quality-of-life and direct-cost estimates associated with EDSS scores, relapses, and AEs were applied. Four approaches were used to assess the outcomes: cost-effectiveness plane and efficiency frontiers (relative value of efficient treatments); cost-effectiveness acceptability frontier, which demonstrated optimal treatment to maximize net benefit; Bayesian treatment ranking (BTR); and an impact investment assessment (IIA; a cost-benefit assessment), which increased the clinical interpretation and appeal of modeled outcomes in terms of absolute benefit gained with fixed drug-related budget. Robustness of results was tested extensively with sensitivity analyses.
Findings
Based on the modeled results, teriflunomide was less costly, with greater QALYs, versus glatiramer acetate and the IFNs. Teriflunomide had the lowest ICER (24,081) versus BSC. DMF brought marginally more QALYs (0.089) than did teriflunomide, with greater costs over the 15 years. The ICER for DMF versus teriflunomide was 75,431. Teriflunomide had >50% cost-effectiveness probabilities with a willingness-to-pay threshold of <€77,416/QALY gained. According to BTR, teriflunomide was first-best among the disease-modifying therapies, with potential willingness-to-pay thresholds of up to €68,000/QALY gained. In the IIA, teriflunomide was associated with the longest incremental quality-adjusted survival and time without cane use. Generally, primary outcomes results were robust, based on the sensitivity analyses. The results were sensitive only to large changes in analysis perspective or mixed-treatment comparison.
Implications
The results were sensitive only to large changes in analysis perspective or MTC. Based on the analyses, teriflunomide was cost-effective versus BSC or DMF with the common threshold values, was dominant versus other first-line RRMS treatments, and provided the greatest impact on investment. Teriflunomide is potentially the most cost-effective option among first-line treatments of RRMS in Finland.
Multiple sclerosis (MS)—a chronic progressive, autoimmune, inflammatory disease—affects >2 million people worldwide. Approximately 89% of cases are classified as relapsing–remitting MS (RRMS) at the time of diagnosis.
The risk for death among Finnish patients with MS is 2.8-fold compared with that in the general population, being 3.4-fold in women and 2.2-fold in men as early as 2 to 10 years after diagnosis.
Natalizumab (Tysabri) for the treatment of adults with highly active relapsing remitting multiple sclerosis: Single technology appraisal (STA) submission to the National Institute for Health and Clinical Excellence.2006; : 1-269
MS treatment with disease-modifying therapies (DMTs) is aimed at decreasing the inflammatory activity leading to relapses, stopping or slowing progression of residual disability, and, eventually, delaying the progression to the secondary progressive phase. However, long-term prognosis among treated patients is largely unknown. Based on Finnish drug reimbursement and sales data,
commonly used first-line DMTs include injectable DMTs, namely glatiramer acetate (GA), interferon (IFN)-β1a IM, IFN-β1a SC, and IFN-β1b SC.
Dimethyl fumarate (DMF) and teriflunomide are new oral DMTs reimbursed as the first-line treatment of RRMS in Finland. The efficacy and safety of DMF 240 mg BID for established MS have been studied in the Phase III CONFIRM (Comparator and an Oral Fumarate in Relapsing-Remitting Multiple Sclerosis)
trials (ClinicalTrials.gov identifiers: NCT00451451 and NCT00420212, respectively). The efficacy and safety of teriflunomide 14 mg once daily for established MS have been demonstrated in the Phase III TEMSO (Teriflunomide Multiple Sclerosis Oral Teriflunomide for Relapsing Multiple Sclerosis)
trials (NCT00134563 and NCT00751881, respectively), and in patients with a first clinical episode suggestive of MS in the TOPIC (Oral Teriflunomide for Patients with a First Clinical Episode Suggestive of Multiple Sclerosis)
Oral teriflunomide for patients with a first clinical episode suggestive of multiple sclerosis (TOPIC): a randomised, double-blind, placebo-controlled, phase 3 trial.
trial (NCT00622700). Effectiveness of teriflunomide compared with IFN-β1b SC has been demonstrated in the Phase III TENERE (Teriflunomide and Rebif® in Patients with Relapsing Multiple Sclerosis)
We evaluated the cost-utility of injectable and oral first-line DMTs in the Finnish population of patients with RRMS, based on a decision-analytical model. To our knowledge, there are no previously published journal articles on the cost-utility of first-line oral DMTs in a European setting or on oral and injectable DMTs for first-line treatment of RRMS. In addition, progression of RRMS in Finnish patients has not been assessed before, and the 4 different approaches elaborating the key results from MS cost-utility analysis have not been previously reported.
Materials and Methods
The cost-utility of the first-line DMTs in the Finnish RRMS population was assessed in a decision-analytical modeling framework
by implementing a Markov cohort model with mutually exclusive health states in Excel 2007, including Visual Basic for Applications (Microsoft Corporation, Redmond, Washington). The modeling approach followed the Finnish guidance for health economic analyses.
The primary outcome of analysis was the modeled incremental cost-effectiveness ratio (ICER), reported as Euros per quality-adjusted life-year (€/QALY) gained. The interpretation of ICER is challenging in Finland because the decision maker’s willingness-to-pay (WTP) threshold per QALY gained has not been publicly declared,
could be applicable in Finland, so that values of <~€25,000 or €25,000–37,000/QALY gained would indicate most plausible or plausible cost-effectiveness, respectively; and, on average, €55,000/QALY gained could be acceptable for end-of-life treatment based on the UK population-weighted decisions. This applicability of UK thresholds is based on the observation that many articles from Finland
Cost-utility analysis of vortioxetine versus agomelatine, bupropion SR, sertraline and venlafaxine XR after treatment switch in major depressive disorder in Finland.
Cost-effectiveness of insulin glargine compared to other long-acting basal insulins in the treatment of Finnish type 1 and type 2 diabetes patients based on individual studies.
was used in the modeling. This model includes direct health and social care costs, and excludes income transfers (taxes) and indirect costs (eg, time costs, disability payments, presenteeism, absenteeism, and informal care). A scenario analysis, including productivity losses,
was performed to assess the robustness of this direct-costing perspective. A summary of the modeled key research questions is given in Table I as an extended PICO framework, which is used to capture and clarify the essential parts of complicated cost-effectiveness assessment in a sensible order (namely, PICOSTEPS: P, patients; I, interventions; C, comparator; O, outcomes; S, setting; T, time horizon; E, effects; P, perspective; and S, sensitivity analyses).
Table IPICOSTEPS: Summary of the research questions.
PICOSTEPS
Description
P: Patients
Finnish adults with incident RRMS and EDSS scores 0.0–6.5 at baseline based on data from a Finnish MS registry
I: Interventions
DMTs: DMF 240 mg PO BID, teriflunomide 14 mg once daily, GA 20 mg SC once daily, IFN-β1a 44 µg SC TIW, IFN-β1b 250 µg SC EOD, IFN-β1a 30 µg IM QW
C: Comparator
Common comparator: BSC (trial placebo)
O: Outcomes
Primary: ICER given as the cost/QALY gained based on the direct cost
Secondary: disaggregated and total QALYs (based on EQ-5D-3L) and costs, life-years, years without impaired mobility (EDSS <6; ie, years without cane use), cost-effectiveness plane and efficiency frontiers, cost-effectiveness acceptability frontiers, Bayesian treatment ranking, and cost–benefit assessment. Discounting: 3%/y
S: Setting
Probabilistic decision analytical modeling (Markov cohort model), including 21 health states reflecting the disease progression (modified by treatment efficacy); and events reflecting relapses, AEs, and withdrawals
T: Time horizon
15 years, based on the follow-up data from the Finnish registry, time since diagnosis in a Finnish cost and EQ-5D-3L MS study,
Effectiveness and cost-effectiveness of interferon beta and glatiramer acetate in the UK Multiple Sclerosis Risk Sharing Scheme at 6 years: a clinical cohort study with natural history comparator.
Natalizumab (Tysabri) for the treatment of adults with highly active relapsing remitting multiple sclerosis: Single technology appraisal (STA) submission to the National Institute for Health and Clinical Excellence.2006; : 1-269
National Institute for Health and Care Excellence (NICE) Final Appraisal Determination—Teriflunomide for Treating Relapsing-Remitting Multiple Sclerosis.
Alemtuzumab versus interferon beta 1a as first-line treatment for patients with relapsing-remitting multiple sclerosis: a randomised controlled phase 3 trial.
Fingolimod reduces the number of severe relapses in patients with relapsing multiple sclerosis: results from phase III TRANSFORMS and FREEDOMS studies.
Presented at: European Neurological Society; 28-31 May,
Lisbon, Portugal2011: 28-31
Cost-utility of agomelatine, venlafaxine and placebo in the treatment of major depressive disorder (MDD) in Finland—economic modelling study using representative population data.
As a secondary complementary analysis, an impact investment assessment (IIA) was carried out to increase the clinical appeal and interpretation of the primary outcome results.
The IIA here covered a fixed drug-related budget based on the most affordable DMT and incremental quality-adjusted survival or time to cane use (EDSS score, 6) versus best supportive care (BSC; trial comparator). The outcome (impact on investment [II]) of the IIA was the duration of benefit obtained in comparison with BSC with the fixed budget. This IIA incorporated an explicit minimal willingness-to-invest (WTI) value for DMT based on the most affordable DMT and, thus, demonstrated the mean absolute cost–benefit in terms of a single unit:
(Equation 1)
where i indicates a particular drug treatment.
Consequently, the result of the IIA is a standardized benefit (II) obtained with the given WTI (in fact, the WTI can be greater than the minimum assumed here, and the benefit increases accordingly).
Patients
Finland’s MS research registry data were used to define the cohort characteristics in the model. Based on the MS research registry data (713 ambulatory patients from Finland, with MS diagnosed in 1991–2010 and an EDSS score of 0–6.5 observed at baseline; see Supplemental Material A in the online version at http://dx.doi.org/10.1016/j.clinthera.2017.01.028), the mean age of modeled patients was 35.64 years, and the female/male ratio was 2.57. The distribution of EDSS scores at baseline is shown in Figure 1.
Figure 1Expanded Disability Status Scale (EDSS) score distribution at the initiation of modeling.
Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis. Commentary: evaluating disease modifying treatments in multiple sclerosis.
Cost-effectiveness analyses of natalizumab (Tysabri) compared with other disease-modifying therapies for people with highly active relapsing-remitting multiple sclerosis in the UK.
as no direct comparison is currently available. Models are always hypothetical and contain an element of uncertainty, but when relying on conservative and fair structure and estimates—and keeping the modeling assumptions in mind—they can produce useful information for decision making.
Figure 2Simplified presentation of the Markov model and its key health states. Relapses and adverse events are not depicted. EDSS = Expanded Disability Status Scale; RRMS = relapsing–remitting multiple sclerosis; SPMS = secondary-progressive multiple sclerosis.
In the model shown in Figure 2, patients with RRMS either maintained the same EDSS or transited to another EDSS health state as the disease progressed, developed secondary progressive MS (SPMS), transited to another EDSS state in SPMS, or died (EDSS score, 10; absorbing state) within the 1-year model cycles. Within each cycle, patients experienced a relapse (with/without hospitalization) and/or an adverse event (AE). The relative effects of DMTs were implemented as modifiers of the modeled clinical course of MS. Midcycle estimates (life-table method of half-cycle correction
National Institute for Health and Care Excellence (NICE) Dimethyl fumarate for treating relapsing-remitting multiple sclerosis. NICE technology appraisal guidance 320.
) were used to avoid over- or underestimation of modeled outcomes.
Disease Progression
Disease progression and relapses were modeled independently. Disease progression in terms of the EDSS score development during RRMS was estimated from Finland’s MS research registry data, consisting of 2299 EDSS measurements. The probability of transiting from RRMS to SPMS was estimated, and EDSS development during SPMS was based on results from the London Ontario registry of MS (see Supplemental Material A in the online version at http://dx.doi.org/10.1016/j.clinthera.2017.01.028). For the origins of registry, see Weinshenker et al.
Natalizumab (Tysabri) for the treatment of adults with highly active relapsing remitting multiple sclerosis: Single technology appraisal (STA) submission to the National Institute for Health and Clinical Excellence.2006; : 1-269
The annual probability of death was modeled based on Finland’s general population mortality rates by applying the observed MS female/male ratio of 2.57 from Finland’s MS research registry data to Finland’s all-cause age- and sex-specific mortality rates from the year 2014,
multiplying the sex-weighted general population mortality rate by the EDSS-specific standardized mortality ratio, and converting the result to give the probability.
Treatment efficacy was assessed by common MS study outcomes: sustaining the same disability status for 12 weeks, annualized relapse rate (ARR), and relapses. Persistence was assessed by withdrawal rates, and tolerability, by AEs. Relative rates of hospitalization in the model were derived from the following clinical trials: IFN-β1a SC, CARE MS I (Comparison of Alemtuzumab and Rebif Efficacy in Multiple Sclerosis)
Alemtuzumab versus interferon beta 1a as first-line treatment for patients with relapsing-remitting multiple sclerosis: a randomised controlled phase 3 trial.
(assumed to apply to GA and IFN-β1b SC); IFN-β1a IM, TRANSFORMS (Trial Assessing Injectable Interferon versus FTY720 Oral in Relapsing–Remitting Multiple Sclerosis)
Fingolimod reduces the number of severe relapses in patients with relapsing multiple sclerosis: results from phase III TRANSFORMS and FREEDOMS studies.
Presented at: European Neurological Society; 28-31 May,
Lisbon, Portugal2011: 28-31
(assumed to apply to DMF). Withdrawals were assumed to happen at the initiation of a new model cycle (but not at the start of the first cycle), and patients were assumed to discontinue their current treatment when they progressed from RRMS to SPMS.
Disability progression, ARR, and withdrawal rates were modeled based on a mixed-treatment comparison assessed by the National Institute for Health and Care Excellence.
National Institute for Health and Care Excellence (NICE) Final Appraisal Determination—Teriflunomide for Treating Relapsing-Remitting Multiple Sclerosis.
To account for new MS diagnostics, earlier treatment, and evidence of decreased ARR over time, the base case analysis included trials that enrolled ≥80% of patients who had RRMS and had been recruiting patients since 2000. In addition, multiway sensitivity analyses (disability progression, ARR, withdrawal rates) of mixed-treatment comparison without year limit and with or without adjustment for placebo relapses were performed.
Treatment safety was modeled using reported AEs from clinical trials or earlier health technology assessments, their costs, and QoL effects (see Supplemental Material B in the online version at http://dx.doi.org/10.1016/j.clinthera.2017.01.028). AEs reported with similar terms were assumed to be treated similarly and to result in similar QoL loss.
Quality-adjusted Survival
The EuroQol Five-Dimensional Questionnaire, Three-Level Version (EQ-5D-3L) QoL for EDSS scores was modeled on the basis of data from DEFENSE (Burden of Illness in Multiple Sclerosis),
Cost-utility of agomelatine, venlafaxine and placebo in the treatment of major depressive disorder (MDD) in Finland—economic modelling study using representative population data.
which used an extensive 1-year recall period and did not make a distinction between hospitalized and nonhospitalized patients or number of relapses.
To approximate the QoL loss associated with hospitalizations, the Finnish QoL loss was weighted with the observed ratio between the QoL losses for hospitalized and nonhospitalized relapses in the US study
(ratio –0.302/–0.091 = 3.3187) to obtain disutility for hospitalized patients in Finland. The applied QoL losses in relapsed patients with and without hospitalization in the model were –0.212 and –0.064, respectively. The QoL effect of relapse was assumed to last for 3 months.
Annual DMT cost was calculated using the indicated mean dose of each drug and number of doses per year (365.25 d/y), determined for each treatment regimen based on the product labeling. For drugs with multiple package sizes, the drug costs were estimated by weighting of the package costs by their estimated market share (Table II). A 100% dose intensity and adherence were assumed.
Administration, monitoring (Table III), and AE costs (see Supplemental Material B in the online version at http://dx.doi.org/10.1016/j.clinthera.2017.01.028) were calculated on the basis of resource consumption multiplied by the associated unit costs. DMT-associated resources were based on the product labeling, recommendations in Finland,
Estimated costs of disease-modifying therapies (DMTs) were excluded based on the digitalization and estimation of DMT costs in Figure 4 in Ruutiainen et al.14
–
1108/1446
2890/3470
3909/5656
7919/12,185
15,718
Direct non–health care costs, €
–
49/834
1693/4526
5767/15,289
18,749/32,364
68,852
ALT = alanine aminotransferase; BC = blood count; BSC = best supportive care; DMF = dimethyl fumarate; EDSS = Expanded Disability Status Scale; FBC = full blood count; GA = glatiramer acetate; GGT = gamma-glutamyl transferase; MRI = magnetic resonance imaging; MxA = protein induced by interferon-alfa/β; TSH = thyroid-stimulating hormone; UT = urine test.
§ Phone call after laboratory tests if specialist visit not arranged.
‖ Estimated costs of disease-modifying therapies (DMTs) were excluded based on the digitalization and estimation of DMT costs in Figure 4 in Ruutiainen et al.
International normalized ratio (INR) monitoring and percent time in therapeutic INR range (TTR) have impact on patient’s quality of life? Application of beta regressions in a prospective 3 months setting.
Estimation of quality-adjusted survival with mild obstructive sleep apnoea and six quality of life (QoL) assessments: comparison between trapezoid rule, cross-sectional and mixed model estimates.
Presented at: 14th Biennial Society for Medical Decision Making (SMDM) European Meeting. June 10-12,
Oslo, Norway2012
and are reported in Table III. Because of limitations in the assessment of DEFENSE-derived relapse costs, the costs of relapses were estimated from other patients with RRMS in Finland (Tampere; N = 581; data included procedures, hospital visits, hospital stays, and unit cost
Based on this analysis, the additional costs per relapse with and without hospitalization were €5537.57 and €1297.41, respectively.
In a scenario analysis, the relationship between EDSS and annual direct care costs (excluding DMT costs) was estimated based on a nonlinear interpolation of findings reported in a study from Finland,
health care costs were valued at 2013–2014 real prices. The required inflation adjustments were performed using Finland’s official price index for communal health care expenditures or income index.
The modeled costs and health outcomes were discounted at 3%/y.
Sensitivity and Generalizability of Results
The robustness and generalizability of the base case results were assessed using various deterministic and probabilistic sensitivity analyses (DSA and PSA, respectively). The base case was based on most credible inputs. DSAs were based on 25 different scenarios, including major or noncredible changes in methods, health risks, treatment, costs, QoL, population, and settings. Means based on all 25 DSA scenarios were also calculated. The details of the DSAs are shown in Table IV.
Table IVDetails of deterministic sensitivity analyses.
Category
Scenario
Discounting
No discounting
Discounting with 5%/y
Health risks
British Columbia, Canada, RRMS EDSS development, based on patients more than 28 years old
Rate for relapses leading to hospitalization based on the 1:2.75 ratio from Tampere data (26.7% of annual relapses result in hospitalization when adjusting for covariates including also EDSS score; N = 581; mean age at relapse, 40 y)
Relapse time, 2 mo
Relapse time, 4 mo
Treatment
DMT discontinuation when EDSS 7 and over was reached, based on reimbursement criteria
Disability progression and ARR set to the lower 95% credibility interval threshold of MTC results
Disability progression and ARR set to the higher 95% credibility interval threshold of MTC results
Alternative source disability progression, ARR, and withdrawal rates from the MTC: no year limit and adjustment for placebo relapses
Alternative source disability progression, ARR, and withdrawal rates from the MTC: no year limit
Time with AEs doubled (same as doubling AE disutility for those AEs that last a shorter time than the model cycle)
Time with AEs halved (same as halving AE disutility)
For PSA, a second-order Monte Carlo simulation was used to take into account the joint variation in the economic and clinical outcomes due to sampling uncertainty related to model parameters. The following distributions were used: β for ARR and withdrawal rates, γ for EDSS-related and treatment costs, log-normal for EDSS transitions, disease progression hazard rates, treatment effect on ARR, treatment effect on hospitalization relapse percentage and QoL, and Dirichlet distribution for the percentage of relapses involving hospitalization (see Supplemental Material C in the online version at http://dx.doi.org/10.1016/j.clinthera.2017.01.028). Based on the PSA, cost-effectiveness acceptability frontiers demonstrated optimal treatment to maximize net benefit with different WTP thresholds, and Bayesian treatment ranking ranked the best treatments.
Results
The average modeled base case results are reported in Table V. The mean projected 15-year total payer’s direct costs differed considerably (by 17.2%) between the most affordable (teriflunomide) and the most costly (IFN-β1b SC) DMT. The respective relative QALY gain difference was 9.3%. The maximum relative QALY difference was 10.6% between the 2 DMTs (DMF and IFN-β1b SC).
The modeled key outcome (ICERs €/QALY gained in comparison with BSC alone) ranged considerably, from 24,081 (teriflunomide) to 248,652 (GA) per QALY gained, and BSC dominated IFN-β1b SC in the base case. Teriflunomide was estimated to be less costly and more effective (dominant) than injectable first-line DMTs, and DMF had a high ICER of 75,431 versus teriflunomide, resulting from the marginally more QALYs (0.089) with DMF and higher costs versus teriflunomide over 15 years. (Table V and Figure 3).
If the WTP threshold for additional QALY gained is set to the most plausible level (€25,000), only teriflunomide represents a cost-effective alternative to BSC alone, based on the modeling. If the WTP is between €37,000 (plausible) and €55,000 (end of life) per QALY gained, only teriflunomide and DMF represent cost-effective alternatives to BSC alone. However, with a modeled ICER of 75,414 for DMF versus teriflunomide, DMF is unlikely to be considered cost-effective in the Finnish setting given the unofficial assumed WTP thresholds detailed in Materials and Methods.
The cost–benefit analysis type IIA utilized the minimal mean expected DMT-related discounted budget per patient (minimum WTI) of €42,077 based on the drug-related costs of IFN-β1a SC. The consequent discounted IIs in terms of incremental quality-adjusted survivals versus BSC were: teriflunomide, 0.337 QALYs gained; DMF, 0.314; IFN-β1a SC, 0.264; GA, 0.120; IFN-β1a IM, 0.119; and IFN-β1b SC, –0.239, all with the assumed WTI. The respective incremental time to cane uses were 0.467, 0.428, 0.347, 0.126, 0.166, and –0.436 years, respectively. Consequently, teriflunomide was projected to result in the highest II with the assumed WTI.
The results of 1-way and multiway sensitivity and subgroup analyses (Table VI) show that the ranking of DMTs in terms of incremental cost-effectiveness appears to be generally robust for sensible changes in modeling assumptions or input variables. The results were sensitive to large changes in the modeled perspective or mixed treatment comparison. As the base case was performed on the basis of a representative population in Finland with characteristics well in line with the indication for teriflunomide, TEMSO trial results on patients’ characteristics and transition probabilities in the placebo group were used in the subgroup analysis. Based on the analysis, the results are also generalizable to an older and more disabled population. Among the 25 modeled DSA scenarios, teriflunomide versus BSC was cost-effective in 72%, 84%, 96%, and 96% of scenarios with WTPs of €25,000, €37,000, €55,000, and €68,000/QALY gained, respectively. DMF versus teriflunomide was cost-effective in 0%, 0%, 4%, and 28% of the 25 DSA scenarios at these respective WTPs.
For the results of the modeled PSA, see Supplemental Material C in the online version at http://dx.doi.org/10.1016/j.clinthera.2017.01.028. In summary, the PSA results were in line with the deterministic results—teriflunomide dominated injectable first-line DMTs, and DMF had a high mean ICER of 76,803 (2.5%–97.5% percentile, 52,105–139,595; 96% and 75% of ICERs exceeded 55,000 and 68,000, respectively) versus teriflunomide. Teriflunomide had >50% cost-effectiveness probabilities at WTPs of <€77,416/QALY gained versus other first-line DMTs. According to the Bayesian treatment ranking, teriflunomide was the first-best among the DMTs with all unofficial WTP thresholds from Finland mentioned earlier.
Discussion
The findings from this modeling study of first-line DMTs for RRMS over 15 years suggest that teriflunomide 14 mg saves costs in comparison with all other reimbursed first-line DMTs in Finland; is cost-effective in comparison with DMF 240 mg at the cited threshold values; dominates injectable first-line DMTs; and, as a complementary result, is associated with the most value gained versus BSC as per the limited DMT-related budget (WTI). In some earlier cost-utility analyses of first-line DMTs for RRMS,
Cost-effectiveness of four immunomodulatory therapies for relapsing-remitting multiple sclerosis: a Markov model based on data a Balkan country in socioeconomic transition.
DMTs in comparison with BSC have been found not to be cost-effective based on the commonly cited threshold values—the situation was similar with GA, IFN-β1a IM, and IFN-β1b SC. These outcomes were largely explained by drug prices and clinical parts of the analysis, that is, short-term efficacy and tolerability and long-term efficacy and persistence of treatments.
The findings from the cost–benefit analysis type IIA based on the WTI seemed to follow the primary outcomes, yet a clear distinction on modeled II for teriflunomide versus BSC in comparison with other DMTs versus BSC was demonstrated with the assumed minimal DMT-related WTI of €42,077/patient. The IIA developed recently is a clinical value-assessment method that could increase clinical interpretation and appeal of the results, and indicate best IIs. However, based on the findings from Soini et al,
IIA cannot fully substitute the primary cost-effectiveness analysis outcomes if it ignores everything other than drug costs, differences in QoL, differences in AEs, and discounts and mixes the time horizons (ie, costs and benefits are gained from different timelines). Thus, IIA can easily result in investment biases and partial optimization of limited budgets. IIA, as such, probably should not be used as a primary method without acknowledging its limitations—here, the objective of the IIA was only to elaborate and complement the primary outcome based on a clear DMT-related cost and DMT-related II approach. In this study, the IIA was based on a modeling approach capable of synthesizing all of the known evidence. Comprehensive methods and data were needed for a valid IIA.
In addition to modeling methods, data validity and generalizability can be an issue in decision-analytical modeling. For example, the DEFENSE survey
is the most comprehensive, recent, and up-to-date assessment of the MS burden in Finland. However, the results from DEFENSE, as such, should be interpreted with caution. There are various reasons for this: the DEFENSE setting was cross-sectional, with varying patient recall (ie, recall bias can be an issue and there was no link between the cost outcomes and varying recall time, eg, relapses and EDSS-related costs); the base population was limited to active Finnish Neuro Society members, with only 36.9% of invited members participating in the survey (ie, about 10% of the Finnish Neuro Society); EDSS was self-assessed (whereas typically EDSS is assessed by a clinician); the results in patients with RRMS and those with SPMS were not separately reported; the reporting of DMT-related costs in different EDSS classes was unclear; and the adjusted cost (and relapse disutility) results may not have been adequately captured owing to statistical limitations (eg, costs should be assessed with methods that account for both distribution skewness and smearing).
is potentially an inappropriate statistical approach. Instead, the use of, for example, multilevel/hurdle regression or simple semilog regression with relapses as a continuous variable would have produced more reliable results.
Based on the findings from the extensive sensitivity analyses, the modeled base case results were nonetheless generally robust and generalizable, even when based on the TEMSO trial setting or RRMS transitions from British Columbia, Canada. Because of the potential impact of inherent methodologic issues in the DEFENSE survey,
were used in a sensitivity analysis and demonstrated that the base case analysis was unlikely to overestimate cost differences. The ranking of DMTs in terms of primary outcome appeared to be robust to sensible changes in the input variables.
Based on the trial evidence, the modeled results of this study are valid. Teriflunomide 14 mg once daily was the only first-line DMT, injectable or oral, to show a significant reduction in both ARR and 3-month risk for disability progression compared with placebo in 2 pivotal clinical trials.
Compared with placebo, teriflunomide significantly reduced the rate of relapses with neurologic sequelae, relapses leading to hospitalization, and relapses requiring intravenous corticosteroids, and teriflunomide-treated patients spent fewer nights in hospital for relapse.
In addition, teriflunomide has a consistent tolerability profile, and AEs reported in patients receiving teriflunomide in clinical trials were largely mild to moderate (diarrhea, nausea, and hair thinning being most common) and infrequently led to treatment discontinuation. Patients reported improved treatment satisfaction with teriflunomide compared with IFN-β1a 44 μg.
Alanine aminotransferase and blood pressure should be monitored regularly, and complete blood cell counts should be performed based on signs and symptoms (eg, infections) during teriflunomide treatment (European Medicines Agency. Teriflunomide [summary of product characteristics] 2013).
Recently, Teri-PRO (Teriflunomide Patient-Reported Outcomes Study), an international Phase IV real-world study that measured patient-reported outcomes after the initiation of teriflunomide treatment, demonstrated a significant increase in treatment satisfaction in patients who were switched to teriflunomide from other DMTs.
which is consistent with the findings from the present modeling study, with those from teriflunomide clinical trials, and with those from other recent real-world studies.
Real Life Use of natalizumab, fingolimod, dimethylfumarate, teriflunomide and alemtuzumab in Austria: benefit-risk data from the Austrian Multiple Sclerosis Treatment Registry.
Presented at: 32nd Congress of the European Committee for Treatment and Research in Multiple SclerosisLondon, September 14-17,.2016; (Poster EP1510)
Efficacy and safety of first line oral therapies in relapsing-remitting multiple sclerosis: dimethylfumarate vs teriflunomide in the Chieti experience.
Presented at: 32nd Congress of the European Committee for Treatment and Research in Multiple SclerosisLondon, September 14-17,.2016; (Poster P1648)
In Teri-PRO, statistically significant improvements were also seen in QoL (as measured by the MS International QoL scale), particularly on the subscales of activities of daily living, psychological well-being, symptoms, and coping.
In addition, teriflunomide seems to have some benefit in patients who are switched from natalizumab due to a risk for progressive multifocal leukoencephalopathy.
However, it is important to note that the risk for progressive multifocal leukoencephalopathy, a severe AE that is included in the DMF labeling in Europe
On the other hand, injection-site or skin reactions, influenza-like symptoms, and neutralizing antibodies are common AEs associated with injectable DMTs and are among the most common reasons for discontinuing injectable DMTs.
Modelling the persistence of disease-modifying drug treatment (DMT) and its independent drivers in Finnish multiple sclerosis (MS) patients: parametric survival modelling.
Flushing, hot flushes, and upper gastrointestinal symptoms are the AEs most commonly reported with DMF therapy, according to an assessment by the National Institute for Health and Care Excellence.
National Institute for Health and Care Excellence (NICE) Dimethyl fumarate for treating relapsing-remitting multiple sclerosis. NICE technology appraisal guidance 320.
Real Life Use of natalizumab, fingolimod, dimethylfumarate, teriflunomide and alemtuzumab in Austria: benefit-risk data from the Austrian Multiple Sclerosis Treatment Registry.
Presented at: 32nd Congress of the European Committee for Treatment and Research in Multiple SclerosisLondon, September 14-17,.2016; (Poster EP1510)
—an observation not accounted for in the present study; in fact, the modeling assumed a lesser withdrawal rate in DMF users compared with teriflunomide users.
Among earlier cost-effectiveness studies of first-line MS DMTs,
Cost-effectiveness of four immunomodulatory therapies for relapsing-remitting multiple sclerosis: a Markov model based on data a Balkan country in socioeconomic transition.
Cost-effectiveness of different interferon beta products for relapsing-remitting and secondary progressive multiple sclerosis: decision analysis based on long-term clinical data and switchable treatments.
Daru: journal of Faculty of Pharmacy, Tehran University of Medical Sciences.2013; 21: 50
Cost-effectiveness analysis of disease modifying drugs (interferons and glatiramer acetate) as first line treatments in remitting-relapsing multiple sclerosis patients.
In the present modeling study, teriflunomide 14 mg and DMF 240 mg were cost-effective treatments versus BSC at the WTP threshold values of €37,000 or €55,000/QALY gained. However, at the most plausible WTP of €25,000/QALY gained versus BSC, only teriflunomide 14 mg was cost-effective. Furthermore, DMF 240 mg was not cost-effective versus teriflunomide 14 mg at Finland’s unofficial WTP threshold values.
Overall health care efficiency, low drug prices, and costly health care resources may be reasons behind the results from the present analysis. However, the health care setting in Finland can be regarded as a robust default setting and as a benchmark for health economic assessments for many reasons. Most important, the productivity and efficiency of the Nordic health care systems are high, as demonstrated in multiple studies of the health care system in Finland.
Social security code and national registries cover all citizens in Finland, and one of the most advanced biobank laws is in use for the willing. Furthermore, Finland has a low pharmacy purchase price for reimbursed drugs
which is likely to result in digitized service solutions for the primary (eg, benchmarking service producers) and secondary (eg, market access to new drugs and devices) uses of national, areal, local, and biobank health care and social welfare data in terms of effectiveness and cost-effectiveness.
Expert solutions in outcomes research. Legal Working Group Workshop, Secondary Use of Data: Information Management, Control and Monitoring [in Finnish].
Ministry of Social Affairs and Health,
Helsinki, Finland2016
Furthermore, the Finnish parliament recently received a proposal for a risk-sharing scheme centered around an agreement-based conditional reimbursement from the government of Finland. However, the official wholesale price in the application would still need to be affordable, and the risk-sharing scheme would be available only through the optional application process.
This development has the potential to further increase the efficiency of Finland’s health care system and the relevance of modeling-based health economic assessments. Finally, Finland’s guidance for health economic analyses
Baltic guideline for economic evaluation of pharmaceuticals (pharmacoeconomic analysis). Latvia, Estonia and Lithuania: 8 August 2002. International Society for Pharmacoeconomics and Outcomes Research; 2002:1--6.
Health economic modeling is needed to handle the multidimensional assessment challenge, to summarize the trial evidence and local input data, to enable extrapolations and discounting, and to produce results in terms of generalizable outcomes with standard interpretation. In the future, it will be necessary to assess the effects of the risk-sharing scheme with some treatments. Thus, by necessity, health economic models are simplifications of a very complicated reality. Here, these assumptions are discussed.
In the model, potential treatment sequences were excluded, and switching between different DMTs was not accounted for. However, dropping out of first-line DMT altogether was included. To analyze the cost-utility of first-line RRMS DMTs, a sequential approach was not needed. A sequential approach would be more viable in later treatment line assessment or in health technology assessment searching for the optimal treatment sequence. Furthermore, there was no gold standard treatment sequence based on Finnish data, and the treatment of patients with RRMS seemed to be guided by per-patient decisions (which are probably affected by disease severity, disease progression, patient/clinician preferences, and potential DMT-related AEs).
In the selected modeling approach, all DMTs compared were handled equally by assuming similar treatment after the first-line DMT, and the result was not jeopardized by inherent and potentially problematic assumptions related to second- and later-line DMT efficacy, tolerability, and washout. Furthermore, in a sequential model, the result may be confounded by potential population changes between the treatment lines. In the present analysis, the results were directly related to differences due to the first-line DMT. In the evaluation, the first-line DMTs were being compared against each other, which potentially was associated with less uncertainty and fewer assumptions, and also in reduced bias and confounding in comparison with a sequential approach relying on multiple additional assumptions due to lack of data. Furthermore, all of the DMTs in the comparison were pharmacy prescription drugs, which overcomes issues of comparing intravenously administered hospital drugs (eg, further-line or high-activity MS treatments) and pharmacy prescription drugs
and are currently subject to public reimbursement in Finland.
In earlier cost-effectiveness analyses of treatments for diseases other than MS, if the treatment sequence included treatment options that were not the most cost-effective, the incremental cost-effectiveness of the sequence deteriorated in comparison with base treatments.
Comprehensive health economic assessment of sequenced treatment with biologics in moderate-to-severe rheumatoid arthritis: analysis based on ACR50 and ACR70 responses.
First-line MS DMTs lacked published cost-utility evidence; thus, there are no supporting publications to benchmark or determine the optimal MS treatment sequence. Furthermore, in these situations, it was more important to know how DMTs perform in comparison with the minimum case (BSC). Based on the Finnish MS research registry data, only a percentage of patients with RRMS are currently actively treated. This may be for reasons connected with efficacy, tolerability, the patient, or the clinician.
Based on the Finnish MS research registry data, MS DMT-related AEs seem to accumulate in some patients. However, owing to the similarity of some AEs produced by frequently used first-line MS injectable DMTs, it is uncertain whether AEs occur in some patients after changing from one first-line DMT to another. Furthermore, no well-controlled research evidence exists demonstrating the clinical gains or benefits of switching the first-line DMT.
EDSS transitions in this modeled evaluation were based on data from Finland (RRMS) and London, Ontario, Canada (SPMS),
because these were most comprehensive for the setting and because they included survival data and were recorded and checked by clinical experts. Other examples of EDSS data include the British Columbia database,
Effectiveness and cost-effectiveness of interferon beta and glatiramer acetate in the UK Multiple Sclerosis Risk Sharing Scheme at 6 years: a clinical cohort study with natural history comparator.
The effects of RRMS EDSS transitions were tested in sensitivity analyses, and the relative results remained unchanged. In fact, the recently published RRMS transitions from British Columbia, Canada
Last, in addition to clinical real-world evidence, future real-world studies should collect real-world data to support modeled economic evaluations. They should, accordingly, include comprehensive assessments of the EDSS specified separately for RRMS; SPMS and primary progressive MS; relapses; AEs and withdrawals; comorbidities; patient income; and the impact of these outcomes on resource use, costs, QoL, and mortality. This real-world evidence may be obtainable using structural treatment-monitoring systems and long-term registry data with sufficient data coverage and could enable the use of event-based or microsimulation methods in the assessments. In addition, IIA type analysis should be used to increase the clinical appeal of complex analyses.
Conclusions
Data presented from the present modeling study highlight the cost-effectiveness of teriflunomide 14 mg once daily compared with DMF 240 mg BID when the commonly cited threshold values are taken into account. In the present modeling study, teriflunomide 14 mg also dominated all other commonly used first-line DMTs for RRMS in Finland and was associated with the highest II.
Conflicts of Interest
This research and editorial support was funded by Sanofi Genzyme, Helsinki, Finland. Sanofi Genzyme participated in the study design; collection, analysis, and interpretation of data; writing of the manuscript; and the decision to submit the article for publication.
E. Soini is a founding partner and employee of ESiOR Oy, Kuopio, Finland. ESiOR Oy carries out studies, statistical analysis, consultancy, education, reporting and health economic evaluations for several pharmaceutical, food industry, diagnostics and device companies; hospitals; consultancies; and academic institutions. J. Joutseno is employed by Genzyme, a Sanofi Company, Helsinki, Finland. M.-L. Sumelahti has been a consultant and member of advisory councils at Genzyme, Novartis, and Biogen, and has received a travel grant from Novartis.
Acknowledgments
E. Soini is grateful to Taru Hallinen, ESiOR Oy, for helpful comments on an early manuscript draft. Editorial support in the preparation of the manuscript was provided by Hannah Greenwood, Fishawack Communications.
Authorship criteria: study management, E. Soini and J. Joutseno; concept/design and study/analysis plan, E. Soini, M.-L. Sumelahti, and J. Joutseno; data assembly, E. Soini, M.-L. Sumelahti, and J. Joutseno; analysis, E. Soini; manuscript drafting, E. Soini; critical manuscript revision, E. Soini, M.-L. Sumelahti, and J. Joutseno; all authors gave final approval for the version to be published. All authorship decisions were made on the basis of scientific consideration.
Appendix A. Supplementary material
Supplement A. EDSS-based RRMS and SPMS transition matrices
is the key outcome in the assessment of MS disability progression. In the Finnish Pirkanmaa-Seinäjoki-Vaasa MS registry, there were 1359 patients with MS with EDSS assessment data available, with altogether 2458 measurements. These patients were identified from administrative registries. The data collection, case ascertainment procedure, and ethical permits have been described in detail elsewhere.
A total of 1242 patients had RRMS, and these patients with RRMS had altogether 2299 EDSS measurements between August 27, 1986, and December 31, 2010. Women accounted for 69.8% of the patients. In all, 62.2% of the EDSS assessments were carried out at the beginning of a DMT episode with an EDSS score of 0–7. In 2010, EDSS values were assessed for all patients alive (July 1, 2010, assumed, if no specific day shown in the data).
EDSS Transitions in RRMS
Figure A.1 shows all EDSS measurements over time for descriptive purposes. As can be seen, most EDSS measurements were performed for patients with RRMS (green colored dots). The figure also shows that there was censoring in the EDSS measurements in EDSS classes 6.5–9.5.
Figure A.1All EDSS measurements (jittered to prevent over-plotting) over time, by MS type (RRMS, green; PPMS, red; SPMS, blue). EDSS = Expanded Disability Status Scale; PPMS = primary progressive multiple sclerosis; RRMS = relapsing-remitting multiple sclerosis; SPMS = secondary progressive multiple sclerosis.
For descriptive purposes, combined Figure A.2 shows the development from one EDSS measurement to the next among patients with RRMS, conditional on particular EDSS scores.
Figure A.2EDSS development in RRMS population over time showing next EDSS scores. The blue line gives the average expected EDSS over time and the shaded area is the 95% CI obtained by unadjusted local polynomial smoothing of the raw data. CI = confidence interval; EDSS = Expanded Disability Status Scale; RRMS = relapsing-remitting multiple sclerosis.
EDSS development over time needs to be modeled in order to estimate the progression of MS. MS progression for the model was estimated using integer RRMS EDSS scores (halves rounded up; 9.5 assumed to be 9.0 because the patient is alive when EDSS is 9.5). The JAGS software V3.3.0,
which is a statistical program capable of analyzing Bayesian hierarchical models by Markov Chain Monte Carlo (MCMC) simulation methods, was used to estimate the EDSS transition probabilities.
When estimating the RRMS EDSS 0–9 transitions, uniform priors were assumed because no earlier Finnish transition probabilities data were available. Based on a prior knowledge of the data in question, 60% of the mortality was assumed to be MS-related.
The hazard rate (HR, λ) for conversion from RRMS EDSS 1 to SPMS was calculated assuming an exponential survival function (ie, a constant hazard of converting to SPMS over time):
λ for an exponential distribution could be estimated from the median time of conversion to SPMS, reported to be 15 years based on London Ontario data,
This gives an annual HR of 0.0462 for SPMS-conversion of patients in EDSS 1.
The Finnish dataset includes only a few observations of conversion to SPMS, and an EDSS-specific rate could not be estimated from these. Based on the London Ontario data, the Cox proportional hazards model was:
where H(t) is the HR of conversion for any EDSS state; H(t)EDDS1, the HR of conversion for EDDS 1; and β, the coefficient (0.25270) of the relationship between EDSS and the HR of progression between the base case EDSS 1 and all other EDSS states.
This was used to derive the HR of conversion from EDSS 1 through each successive stage to EDSS 8 (Table A.II). All estimated HRs were then subsequently converted into probabilities
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Supplement B. AEs: Incidence, Treatment Costs, and Disutilities
Risks of AEs
Adverse events (AEs) were included to the modeling based on a ≥4% difference between active treatment and placebo and/or clear inclusion in a previous NICE HTA submission (Table B.I). Nearly all AEs related to DMF, GA, interferons, and teriflunomide are mild to moderate and of short duration. The reason for not including the AEs with a <4% difference between placebo and active treatment and no NICE HTA reference was to simplify the analysis. Recently, the FDA added a progressive multifocal leukoencephalopathy (PML, a very severe AE) scenario to the DMF label. However, possible PML risk with DMF was ignored owing to uncertainty related to exact PML risk (usually PML risk accumulates over time).
Table B.IAnnualized risk of AEs associated with treatment.
Treatment
Adverse event (AE)
Annualized probability
Rate source
DMF 240 mg (Tecfidera®)
Flushing
19.0%
Aggregate weighted estimate based on the trials referred to in the HTA submission (NICE)
and the resulting annualized AE rates were then converted back to annualized probabilities/risks (Table B.I).
AEs were assumed to occur at most once per cycle. However, injection-site reaction, fever, and nausea tend to occur after every interferon dose, and chest pain, palpitation, and dyspnea may happen after every GA dose for subjects who have a particular AE. Consequently, the impact of those AEs may be underestimated for interferons and GA.
Treatment of AEs
In Finnish practice, the active treatment of severe AEs takes place in the neurology unit, and moderate AEs result in phone calls to the neurologic department. More severe AEs, including injection-site reactions, chest pain, palpitation, dyspnea, hot flush, and vomiting, require specialist consultation (Table B.II). Chest pain and flushing, palpitation, and dyspnea related to GA are usually transient.
Asthenia, chills, diarrhea, flush, hair thinning, and nausea alone do not usually need active treatment; thus, phone contact to the neurologic department was assumed for these. Conservatively, none of the AEs included were assumed to result in hospitalization.
Table B.IIResource use and costs (€) associated with AE management.
Adverse event (AE)
Cost (€)
Resources (original unit cost and source)
Asthenia, chills, diarrhea, flush, hair thinning, or nausea
Ibuprofen is used to treat fever, headache, influenza, muscle pain, and myalgia. Antihistamine is used to treat (at minimum) the hot flush associated with DMF. No other drugs were assumed to be used for the treatment of DMT-related AEs.
QoL Loss of AEs
Resource use and costs associated with AE management are given in Table B.II, and QoL losses and durations associated with AEs are given in Table B.III.
Table B.IIIQuality of life (QoL) loss and its duration associated with AEs.
Adverse event (AE)
QoL loss
Duration
Assumption
Disutility source
Flushing, hair thinning, neutralizing antibodies, or upper abdominal pain
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Supplement C. Probabilistic Sensitivity Analysis Results
Probabilistic Results
Table C.I reports the 15-year mean and 2.5%–97.5% percentile results based on 2000 simulations.
Figure C.1 shows the joint distributions of 15-year cost-and-effect differences (increments) for the nondominated teriflunomide (teriflunomide is in the origin of Figure C.1) vs other DMTs.
Figure C.1Probabilistic incremental cost and QALY results in a cost-effectiveness plane for teriflunomide vs other first-line treatments (2000 simulations). DMF = dimethyl fumarate; GA = glatiramer acetate; IFNβ-1a-SC = interferon beta-1a-subcutaneous; IFNβ-1a-IM = interferon beta-1a-intramuscular; IFNβ-1b-SC = interferon beta-1b-subcutaneous; QALY = quality-adjusted life-year.
Figure C.2 depicts the cost-effectiveness acceptability frontier (CEAF). Based on the CEAF, teriflunomide had more than 50% cost-effectiveness probabilities with ICERs less than 77,416 vs other first-line DMTs for RRMS (Figure C.2).
According to Bayesian treatment ranking, teriflunomide was the best option, with a willingness-to-pay threshold of €0 (99.9%), €25,000 (100.0%), €37,000 (100.0%), €55,000 (96.2%), and €68,000 (75.2%) per QALY gained.
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Drug costs are at January 2016 values.
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