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Modeling Benefits, Costs, and Affordability of a Novel Gene Therapy in Hemophilia A

ten Ham, Renske M.T.1,2,3; Walker, Simon M.2; Soares, Marta O.2; Frederix, Geert W.J.1,3; Leebeek, Frank W.G.4; Fischer, Kathelijn5; Coppens, Michiel6; Palmer, Stephen J.2

Author Information
doi: 10.1097/HS9.0000000000000679

Abstract

Erratum

Since the publication of the article entitled “Modeling Benefits, Costs, and Affordability of a Novel Gene Therapy in Hemophilia A” (HemaSphere. 2022;6(2):e679), the authors have requested a spelling correction for a co-author’s name. The first/given name of Simon M. Walker was erroneously listed as Sikon in the manuscript’s original publication. This has now been adjusted.

The changes have been made online: https://journals.lww.com/hemasphere/Fulltext/2022/02000/Modeling_Benefits,_Costs,_and_Affordability_of_a.5.aspx

HemaSphere. 6(3):e698, March 2022.

INTRODUCTION

Hemophilia A (HA) is a rare hereditary X-linked bleeding disorder caused by a mutation in the FVIII-gene coding for coagulation factor (F)VIII.1 This mutation results in activity impaired hemostasis causing bleeding tendency.2 Treatment of severe HA focuses predominantly on bleed prevention, especially prevention of joint bleeds.3 In The Netherlands, guidelines recommend prophylactic treatment of severe HA patients with intravenous (recombinant) FVIII every 1–3 days.4 Recently, several FVIII products with extended half-life have been added to the treatment formularies, as well as the first monoclonal antibody emicizumab (Hemlibra; Roche HQ, Bazel, Switzerland). Emicizumab, a nonfactor replacement therapy, is administered subcutaneously every 1–4 weeks and is expected to have rapid global uptake. Longer-acting FVIII substitutes and nonfactor replacement therapies allow less frequent (intravenous) administrations increasing patient mobility and quality-of-life.5 The latest innovation in HA-treatment is the emergence of gene therapies.6 The promise of one-time treatments inducing prolonged or sustained near-normal FVIII is considered a potential transformative innovation and creates high expectations among patients and physicians.7

The first gene therapy indicated for severe HA is in advanced clinical trials: valoctocogene roxaparvovec (valrox; Roctavian by BioMarin, San Rafael, CA).8,9 Valrox’ developer applied for centralized market authorization in the late 2019.10,11 However, in November of 2020, the application was withdrawn after the European regulator—following the US Food and Drug Administration—requested additional data from an ongoing phase III trial. The full results are not expected until November 2024.12,13 In addition to clinical uncertainties, high upfront and irrecoverable costs are expected to create additional market access challenges.14 Specifically, uncertainties around the extent and persistence of the potential benefits raise both practical and affordability concerns among health technology assessment (HTA)-bodies and payers (eg, will the intervention result in a net population health gain and over what time horizon?).15–18

To inform HTA, cost-effectiveness analyses (CEAs) are used to quantify benefits, costs, as well as uncertainties and the net impacts on population health (ie, whether the health gained by the patient exceeds the health forgone elsewhere by the same resources not being available for other purposes). Few published CEAs have assessed gene therapies for hemophilia. Machin et al19 was the first to assess the cost-effectiveness of a hypothetical gene therapy intended for HA in a US setting and found the gene therapy to dominate (being cost saving and more effective) compared to FVIII prophylaxis. More recently, Cook et al20 explored the cost-effectiveness of valrox and incorporated individual patient FVIII. This allowed for incorporation of an initial treatment effect (max FVIII) and treatment waning over time, which are used more widely to determine gene treatment durability.20–22 Cook et al20 also estimated a cost-saving but with high variance (ie, large 95% confidence intervals [CIs]), but did not provide insight on affordability. Last, the US-based Institute for Clinical and Economic Review (US ICER institute) conducted assessments of emicizumab compared to FVIII prophylaxis and more recently of valrox versus emicizumab.23,24 Awaiting availability of more clinical data, early cost-effectiveness analyses can be performed to quantify key areas of uncertainty. This is helpful both for the developers as well as policy makers, for example, to anticipate on upcoming dossiers, possible challenges, or inform access schemes such as Coverage with Evidence Development programs.25,26 So far, no (early) assessments of the benefits, costs, and affordability of valrox have been conducted for the Dutch situation.

The objective of this study is to undertake an early cost-effectiveness assessment of valoctocogene roxaparvovec (Roctavian; valrox) compared to prophylactic FVIII or emicizumab (Hemlibra; Roche HQ) in patients with severe HA without detectable FVIII-antibodies in The Netherlands. We also explore the use of novel measures to aid product development and direct research efforts, such as treatment durability, maximum value-based price (MVBP), and break-even time (time for benefits to offset high upfront payment to improve population health).

MATERIALS AND METHODS

Study design

To model the expected benefits and cost of valrox in patients with severe HA in The Netherlands, a Markov state transition model was constructed in Microsoft Excel (Microsoft, Redmond, WA). We compared a hypothetical cohort of patients who received valrox to a cohort receiving FVIII prophylaxis and to a cohort receiving emicizumab. The model takes a societal perspective and adheres to the Dutch guidelines on economic evaluations in health care.27 Costs were assessed from a Dutch societal perspective. The primary health outcome was quality-adjusted life years (QALYs). Cost-effectiveness was expressed in terms of incremental cost-effectiveness ratios (ICERs) and net benefits where appropriate.

As no list price is available for valrox we used a price of €2,125,000 in the base case based on previous research but also examined the MVBP of valrox,28 the MVBP analysis also accounted for uncertainty in the confidential price discounts of FVIII and emicizumab with different discounts to list prices considered. In the emicizumab MVBP analysis, a dose reduction scenario was also included.29 In both scenario’s, the MVBP reflects where the intervention would still be considered as cost-effective condition on different prices of FVIII and emizumab.30 Furthermore, we examined the point at which the intervention would break-even compared to the standards of care in terms of net health (eg, where the upfront cost, and resulting forgone health, is exceeded by the health benefits to the patient).

Model overview

A Markov model was constructed, based on a previously published model: The University of Washington Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute Hemophilia A Cost-Effectiveness Model, which assessed prophylactic emicizumab versus FVIII in patients with inhibitors.23 This model was adapted to the Dutch situation and to include an additional gene therapy arm. The gene therapy arm incorporated mean patient FVIII and treatment waning (Figure 1). This was done by translation of FVIII of patients treated with valrox from the literature to annual bleed rates (ABRs) based on work from den Uijl et al.31–33

F1
Figure 1.:
Structure of Markov model. Submodels have the same structure. Joint with arthropathy was defined as Petterson Score ≥28. Sub model i: No target joints. Sub model ii: 1 target joint. Sub model iii: 2+ target joints. FVIII = Factor VIII clotting factor; TJ = target joint.

The adapted model included 5 health states and 3 submodels. The model distinguished 5 health states reflecting different types of bleeds with more severe bleeds incurring higher costs and utility decrements: No bleed, untreated bleed, treated bleed not into target joint, treated target joint bleed and death (any cause). A target joint was defined as a single joint with ≥3 spontaneous bleeds within a consecutive 6-month period.34 The cycle length of the model was 1 week with patients returning to the no-bleed health state at the end of each cycle. A time horizon of 10 years was considered based on reported sustained benefits and the absence of retreatment data.10

Within the model three sub-models were defined to incorporate joint damage: (1) no target joint; (2) 1 target joint; and (3) 2+ target joints (Figure 1).23 The transitions between submodels was driven by the mean number of joint bleeds linked to Pettersson score (PS) increase.35 PS ≥28 was assumed to indicate a target joint whereafter a patient transitioned to subsequent submodel after acquiring cost increase and utility decrement for a total joint replacement therapy (assumed 50% knee/50% hip).36

All input parameters and assumptions, including ranges for sensitivity analyses are reported in Table 1.

Table 1. - Input Variables and Ranges Used in Deterministic and Probabilistic Sensitivity Analyses.
Input variables Base Case Low Estimate High Estimate Distribution Source
Characteristics and disease progression
 Age 31 23 42 Normal 9
 Weight 85 68 102 Normal 37
 Sex (%male) 100% Fixed 9
 Prevalence existing target joint (%) 70% 56% 84% Beta 32
 Prevalence existing > 1 target joint (%) 70% 56% 84% Beta 32
Pettersson score (baseline submodel ii/iii) 24.1 20.0 30.0 Lognormal 35
Number of joint bleeds per Pettersson Score increase 12.6 11.1 14.7 Lognormal 35
Valrox intervention
 Initial FVIII level (week 26) 67.00 20 84 Lognormal 9
 FVIII waning (annual) −5.72% −1.56% −10% Lognormal 10
 Limited responders (%) 15% 0.4% 45.9% Lognormal 8,9
 FVIII ≥15%: all bleeds (ABR) 1.0 0 2.0 Lognormal Expert elicitation
 FVIII ≥5% and <15%: joint bleeds (%) 60% 48% 72% Lognormal 20
 FVIII% >5% and <15%: joint bleeds into target joint (%) 40% 32% 48% Lognormal 20
 FVIII% ≥1% and <5%: patients receiving FVIII prophylaxis 25% 5% 40% Lognormal Expert elicitation
FVIII prophylaxis
 All bleeds (ABR) 4.80 3.20 7.10 Lognormal 32,38
 Treated bleeds (ABR) 4.33 3.46 5.20 Lognormal 32,38
 Treated joint bleeds (ABR) 2.90 2.32 3.48 Lognormal 32,38
 Treated target joint bleeds (ABR) 2.50 2.00 3.00 Lognormal 32,38
 Adherence during trial (0–24 wks) 100% 80% 100% Beta 39
 Adherence posttrial (>24 wks) 89% 71% 100% Beta 40
Emicizumab
 All bleeds (ABR) 2.60 1.60 1.92 Lognormal 32,38
 Treated bleeds (ABR) 1.30 0.80 1.70 Lognormal 32,38
 Treated joint bleeds (ABR) 0.90 0.40 0.96 Lognormal 32,38
 Treated target joint bleeds (ABR) 0.70 0.30 0.84 Lognormal 32,38
 Adherence during trial (0–24 wks) 100% 80% 100% Beta 41
 Adherence post trial (>24 wks) 86% 69% 100% Beta 41
Quality of life
 Utility, no bleed submodel i 0.88 0.66 0.98 Beta 42
 Utility, bleed submodel i 0.66 0.53 0.79 Beta 42
 Disutility target joint bleed submodel i −0.12 −0.10 −0.14 Beta 42
 Duration disutility bleed 2 d Fixed 24
 Utility PS 4–12, submodel ii/iii 0.82 0.78 0.86 Beta 43
 Utility PS 13–21, submodel ii/iii 0.79 0.75 0.83 Beta 43
 Utility PS 22–39, submodel ii/iii 0.73 0.69 0.77 Beta 43
 Utility PS 40–78, submodel ii/iii 0.72 0.68 0.76 Beta 43
 Disutility orthopc surgery −0.39 −0.31 −0.46 Beta 44
 Duration disutility orthopedic surgery 1 mo Fixed 24
Cost (2019 Euro)
 Healthcare cost: pharmaceutical
 Cost/unit valrox 2,125,000 1,700,000 2,550,000 Gamma 24
 Cost/unit FVIII prophylaxis (per IE) 0.89 0.20 1.10 Gamma 30
 Cost/unit emicizumab (30 mg/mL vial) 2476 1980 2971 Gamma 45,46
 Cost/bleed FVIII on demand (IE) 119.7/kg 95.78 143.67 Gamma 45,46
Healthcare cost: nonpharmaceutical
 Bleed-related, 19–44 y 904.55 723.64 1085.46 Gamma 47,48
 Bleed-related, >44 y 3735.80 2988.64 4482.95 Gamma 47,48
 Not bleed-related, no TJ (weekly) 112.38 Gamma 48,49
 Not bleed-related, >1 TJ (weekly) 176.21 Gamma 48,49
 Arthropathy surgery cost (50%TKR/50%THR) 11,850 9480 14,221 Gamma 48,50
 Surgery related on demand FVIII (valrox and emicizumab arm) 8278 6622 9934 Gamma 4
 Surgery related on demand FVIII (prophylactic FVIII arm) 66,225 52,980 79,470 Gamma 4
 Surgical follow-up 20 y Fixed 24
 Adverse events valrox (week 1) 401.29 321.03 481.55 Gamma 8, 9, 48
 Adverse events, FVIII prophylaxis (weekly) 2.01 1.61 2.41 Gamma 32, 38, 48
 Adverse events, emicizumab prophylaxis (weekly) 2.06 1.65 2.47 Gamma 32, 38, 48
Nonhealthcare cost
 Lost productivity after bleed 1 d Fixed 24
 Lost days of productivity after hospitalization Duration of stay + 2 d Fixed 24
 Hourly wage 2019 (adjusted for sex) 40.46 32.27 48.55 Gamma 27
Low and high estimates are extracted from literature (ie, confidence intervals) and used to explore impact on outcomes in sensitivity analyses.
ABR = annual bleed rate; FVIII = factor VIII; QALY = quality-adjusted life year.

Population

The model simulated a hypothetical cohort of patients with severe uncomplicated HA (defined as adults with congenital FVIII deficiency, FVIII < 1%, and without detectable FVIII antibodies or adeno-associated virus serotype 5). The patient characteristics matched the phase I/II study by Pasi et al9 (cohort 3), and are similar to the Dutch population.31

It was assumed that our cohort had the same life-expectancy as the general Dutch population.37 Consequently, Dutch lifetables for background mortality were applied.37 A mean age of 31 years (23–42) and mean weight 85 kg (68–102) were applied in line with cohort 3 from the phase I/II study by Pasi et al9 (see Table 1). Weight was varied by age and was sex-adjusted using 2019 Dutch population statistics.9,37 The prevalence of existing target joints was assumed to be 70%, of which 70% had >1 target joint. The baseline PS in submodels ii and iii was 24.1.35

Interventions

The primary intervention of interest was valrox (dosed 6 × 1013 vg/kg in one intravenous admission).9 Mean FVIII and adverse events were derived from a phase I/II study and extrapolated beyond study duration.9,51 In the first 2 months after valrox-treatment, patients received additional FVIII prophylaxis (including costs and adverse events) reflecting the trial protocol.9 Patients also received prophylactic glucocorticosteroids (40 mg/d), which were tapered from week 3 onward.8 In addition, the phase I/II study showed 1 of 7 patients (15%) in cohort 3 demonstrated limited response (FVIII < 5% after 2 y).9 This is in line with more recent unpublished preliminary data from an ongoing phase III trial.13,52 Therefore, 15% of patients in the base case were characterized as limited-responders and, in line with treatment protocol, switched back to FVIII prophylaxis.

The first comparator is standard (recombinant) FVIII concentrate prophylaxis (dosed 30I E/kg 3 times a week intravenously) and current main standard of care for patients with severe uncomplicated HA in The Netherlands.38,45 The model also included an emicizumab arm. This nonreplacement therapy was approved for reimbursement in The Netherlands in July 2020 and is expected to have rapid uptake.33 Following guidelines, emicizumab was dosed at 3 mg/kg/wk subcutaneous in the first month followed by maintenance dose of 3 mg/kg biweekly.45

Efficacy

Differences in treatment effects in the FVIII prophylaxis and emicizumab arm were driven by treatment specific ABRs (see Table 1). ABRs and adverse events were derived from the clinical trial to evaluate prophylactic emicizumab versus no prophylaxis in the HA without inhibitors (HAVEN-3) trial and the technology assessment of emicizumab conducted by The Dutch Health Care Institute (Zorginstituut Nederland, ZIN) and transformed to weekly rates.32,38

In the valrox arm, ABRs were deduced from FVIII reported by Pasi et al and translated to bleed rates using a relation described in the Dutch population by den Uijl et al.31 This study found an S-curved association between the FVIII level and annual joint bleeds. A sigmoid-curve was fitted on the S-curve published by den Uijl et al31 to simulate weekly joint bleed rates, which were translated to all bleed rates assuming 70% of all bleeds were joint bleeds.20,24 After initial treatment with valrox, it was assumed after week 26 that maximum FVIII% were achieved (ie, initial treatment effect) based on trial data.9 Treatment waning was incorporated by incorporating a mean linear decline of −5.7% FVIII/year based on public available developer materials.9,10 Assumptions around the initial treatment effect and treatment waning were discussed in expert elicitation and found appropriate. FVIII was measured with one-stage assay, both by Pasi et al and den Uijl et al.

To best reflect the bleed rates, bleed types, and translation to clinical presentation of different HA severity and disease stages over time in the valrox arm, several additional decision rules were applied to the modeled sigmoid curve based on the previous work and expert opinion.20 When FVIII >15% a base case spontaneous ABR of 1.0 (joint bleeds) was modeled.20 Bleeds were modeled to be treated the same across treatment arms with demand FVIII dosed according to Dutch treatment formulary: 25 units/kg bolus followed by twice daily 15 units/kg for 3.5 d).4,33,45 If FVIII >5% but ≤15% (corresponding to mild HA), 60% of bleeds were assumed joint bleeds of which 40% target joint bleeds.20 When FVIII >1% but ≤5% (corresponding to moderate-to-severe HA), 25% of patients returned to prophylactic FVIII and when FVIII ≤1%, it was assumed 100% returned to chronic prophylactic FVIII therapy.

Expect elicitation was conducted to inform decision rules to translate FVIII to bleeds rates. Elicitation was conducted via semi-structured 60-minute interviews with clinicians (n = 3).53 Additionally expert advisors were included to assess validity of modeled disease progression, treatment assumptions, clinical validity, and generalization to Dutch population.

Outcomes

Health outcomes were expressed in life years (LYs), QALYs, PS, and (joint) bleeds. A QALY is a generic measure capturing both survival and quality of life, which allows for meaningful comparison of health across different diseases.54

Baseline utility (eg, a standardized quality of life score with 0 reflecting death and 1 perfect health) was set at 0.82 for patients in the no-bleed health state in submodel i (no target joints) (see also Table 1).42,55 In the 1 and 2+ target joint submodels, baseline utilities were related to PS derived from a study by Fischer et al43 based on the SF-6D (utility derived from the Short Form-36) questionnaire with higher PS reflecting lower quality of life.56 Patients experiencing a bleed were assigned an utility of 0.66 for 2 days across submodels.42 A target joint bleed was assigned an additional disutility of −0.12.55 Patients undergoing orthopedic surgery were assigned a 1-month disutility of −0.39.44

Resource use and costs

Drug costs were expressed in 2019 euros (€). At time of analysis, no price of valrox had been disclosed in The Netherlands by the developer; therefore, our base case scenario used the US price converted to 2019 Euros (Table 1).24 As previously described, FVIII costs are considerably lower than public available list prices as discounts are negotiated between hospitals and manufacturers.30,57 This notion was supported by our expert advisors. Based on a procurement survey, a mean FVIII unit price of €0.89 per unit corresponding with 11% discount was applied (€0.56 per unit adjusted to 2019 Euros).30,37 Impact of different discounts informed by the procurement survey and expert opinion was further explored in a scenario analysis. For emicizumab, the Dutch list price was used in the base case analysis (€2476 per 30 mg/mL vial).46 The effect of dose reduction and a discount scenario were further explored in a second scenario analysis.

Healthcare utilization was derived from the literature and includes outpatient visits, hospitalization, and emergency room visits. Per bleed resource use was obtained from a real-world study and assumed similar across treatment arms.47 Nonbleed-related healthcare utilization was divided into 19–45 years of age and >45 years old and also assumed the same across treatment arms.49 Healthcare utilization was matched with Dutch Treatment and Diagnosis Combination Codes and tariffs from the Dutch Healthcare Authority (Nederlandse Zorgautoriteit; NZa) to calculate costs.27,47–49 Untreated bleeds were assumed to accrue no cost, but they did incur a utility decrement (i.e., disutility), therefore these will not be further reported.23

Costs were split into healthcare and non-healthcare costs. Healthcare costs were further divided pharmaceutical costs (prophylactic and on demand treatment) and nonpharmaceutical costs (healthcare utilization; bleed-related; and nonbleed-related). To adhere to the societal perspective, nonhealthcare cost included costs for patients and family (rehabilitation after surgery and travel expenses) and loss of productivity.27,58 This is in line with Dutch guidelines for economic evaluations.27

Analyses

Incremental benefits and costs between treatment arms were expressed as ICERs.54 The ICER captures the incremental cost per unit of outcome of one intervention compared to another. Here, valrox was compared to prophylactic FVIII and separately to emicizumab yielding 2 ICERs. Prophylactic FVIII and emicizumab were not compared to each other. The ICER is calculated as: (Costintervention – Costcontrol)/(QALYintervention – QALYcontrol).54,59 Costs and (QA)LYs were discounted at 4.0% and 1.5% per annum, respectively, in line with Dutch guidance.27

Uncertainty around parameter estimates were explored via deterministic (DSA) and probabilistic sensitivity analyses (PSA).54,60 The DSA explores impact of individual parameters by alternately varying input values between pre-set minimum and maximum values (Table 1) and can be considered parameter specific best- and worst-case scenarios. Minimum and maximum values were derived directly from the literature (eg, via reported 95% CIs, standard deviation [sd], or standard error [se]) or indirectly (by deriving 95% CI, sd, or se from patient characteristics using epidemiological methods).54 When no variability measures were available, parameters were varied ±20%. A PSA provides a more comprehensive combined uncertainty estimate by simultaneously sampling uncertainty across all parameters. This was done by sampling 1000 iterations of random values for all model input parameters according to their individual distributions (Table 1).61 PSA results are typically presented as a scatterplot in a cost-effectiveness plane. The PSA output was used to estimate the probability of a treatment being cost-effective for a given willingness-to-pay threshold, which was presented in a cost-effectiveness acceptability curves (CEACs). The Dutch informal willingness-to-pay-threshold of €80,000/incremental QALY was applied.27

In 2 scenario analyses, the mean MVBP was calculated for valrox at which its net monetary benefits (NMBs) equaled zero.62 Given discounts of FVIII clotting factors are unknown, in the first scenario analysis, the impact of a range of discount scenarios (0%–80%) on MVBP was explored.30 A 0% discount corresponds with the Dutch list price (€1.00/unit) and an 11% discount was applied in the base case (€0.89/unit).30 In a second scenario analysis, MVBP for valrox was estimated in comparison to emicizumab.

Similar to the FVIII scenario, discounted emicizumab prices informed by expert opinion were explored and estimated to be plausible up to 50%. The price discount scenario was combined with a dose reduction scenario informed by recent research efforts. Donners et al29 describes up to 50% emicizumab dose reduction could be possible, without loss of efficacy. This resulted in the inclusion of combined dose reduction and discount scenario for emicizumab, ranging from 0%–80%. Here, 0% discount corresponds with the Dutch list price and was used as base case (€2476 per 30 mg/mL vial).46

Last, a break-even point was expressed as the estimated time in years needed before treatment of a patient with valrox results in a net improvement in population health (ie, the health gains to the patient exceed the health losses elsewhere from the high upfront costs).54

RESULTS

Base case

The estimated cumulative bleeds and costs per treatment over time derived from the base case model are shown in Figure 2. The base case results in Table 2 show the cost and benefits per treatment arms over the model time horizon (10 y). Major cost drivers were the drug acquisition costs, with mean prophylactic drug costs accounting for 91%, 80%, and 92% of total cost for the valrox, prophylactic FVIII, and emicizumab arm, respectively. Valrox patients experienced 6.7 treated bleeds (ie, target and nontarget joints) compared to 42.1 in the FVIII arm and 11.5 with emicizumab over 10 years. This reduction in treated bleeds compared to FVIII prophylaxis is also reflected in lower PSs, higher total QALYs, and less on demand drug cost across in valrox and emicizumab arms (Table 2).

Table 2. - Estimated Base Case Benefits and Costs per Treatment Over a 10-year Time Horizon.
Valrox FVIII Prophylaxis Emicizumab
Deterministic Analysis 95% Credible Range PSA Deterministic Analysis 95% Credible Range PSA Deterministic Analysis 95% Credible Range PSA
Costs
 Prophylactic drug cost €2,570,885 (€296,326–€9,830,835) €2,626,284 (€42,454–€9,041,070) €3,930,144 (€100,531–€14,368,43)
 On demand drug cost €57,022 (€971–€767,311) €355,193 (€5819−€1,225,133) €108,241 (€1.872–€363,847)
 Nonpharmaceutical cost €89,035 (€81,690–€156,761) €120,181 (€89.241–€197,420) €94,766 (€85,203–€210,534)
 Societal cost €122,268 (€4492–€672,249) €183,032 (€6250−€945,622) €119,015 (€4389–€638,335)
 Total cost €2,839,210 (€487,449–€10,545,521) €3,284,690 (€282,686–€10,444,562) €4,252,167 (€408,737–€14,853,421)
Benefits
 Maximum Pettersson score 24.2 (11.59−40.21) 25.1 (12.26−40.92) 24.4 (11.51−40.07)
 Treated non target joint bleeds 2.8 (0.49−21.89) 17.9 (9.35−27.61) 4.6 (1.39−7.23)
 Treated target joint bleeds 3.8 (0.64−24.79) 24.3 (19.85−29.4) 6.9 (4.1−10.95)
 Total QALYs 7.03 (5.86−8.14) 6.38 (5.59−7.36) 6.90 (5.98−7.96)
 Total life years 9.29 (8.04−10.48) 9.28 (8.05−9.94) 9.28 (8.05−9.94)
FVIII = factor VIII; PSA = probabilistic sensitivity analysis; QALY = quality-adjusted life year; Valrox = valoctocogene roxaparvovec (Roctavian).

F2
Figure 2.:
Simulated outcomes per treatment including 95% confidence interval over time in the base case analysis (cumulative over time). (A) Simulated bleeds (all bleeds and joint bleeds) per treatment. (B) Simulated costs per treatment. FVIII = Factor VIII clotting factor.

Results of the incremental analysis are shown in Table 3. Valrox was found to dominate both FVIII and emicizumab—meaning valrox results in higher incremental benefits at lower total costs. The CEAC shows valrox has a 54.8% probability of being cost-effective when compared to FVIII prophylaxis (Supplemental Digital Figure S1; https://links.lww.com/HS/A215). This means 54.8% of ICER-estimates in the PSA were lower than €80,000/QALY. In the comparison between valrox and emicizumab the estimated percentage was 38.9%. Given the dominant base case, these low CEAC-percentages suggest large uncertainty.

Table 3. - Estimated Incremental Base Case Benefits, Costs and Probability of Being Cost-effective Compared to Valrox of a 10-year Time Horizon.
[B] Treatment Benefits (QALYs) Costs € Incr Benefit Incr Cost ICER Probability of Being Cost-effectivea (%)
Valrox 7.03 €2,839,210
FVIII prophylaxisb 6.38 €3,284,690 0,65 −€358,970 Dominated 54.8
Emicizumabb 6.90 €4,252,167 0,13 −€1,412,957 Dominated 38.9
aProbability of being cost-effective using a willingness-to-pay threshold of €80,000/incremental QALY.
bProper interpretation of the table results.
FVIII = factor VIII; ICER = incremental cost-effectiveness ratio; incr = incremental; QALY = quality-adjusted life year; Valrox =valoctocogene roxaparvovec (Roctavian).

The DSA (Supplemental Digital Figures S2 and S3; https://links.lww.com/HS/A215) shows that similar parameters have most impact on outcomes across both comparisons, specifically: cost/unit of drug (valrox, emicizumab, and FVIII); initial treatment effect; distribution of limited responders and treatment waning. The PSA outcome (Supplemental Digital Figure S4; https://links.lww.com/HS/A215) is shown as a scatter plot of ICER-estimates in a cost-effectiveness plane, providing a visual depiction of the directions and extent of uncertainty of our estimates.

Mean MVBP and discount scenarios are shown in Figure 3. Base case MVBP of valrox (11% discount) compared to FVIII prophylaxis was estimated at €2,650,512 and varied from €2,929,004 in the most conservative discount scenario (0% discount) to €701,067 under the most optimistic scenario (80% discount) (Figure 3A). When compared to emicizumab, the most conservative discount scenario and base case MVBP (0% discount) was €3,527,984, and decreased to €779,405 under the most optimistic scenario (80% discount) (Figure 3B).

F3
Figure 3.:
Maximum value-based price (MVBP) of valrox under discount scenarios. (A) Simulated MVBP with discounted FVIII scenarios with 0% discount represents Dutch list price (striped bar at €1.0/unit), and 11% discount aligns with the base case analysis (dotted bar at €0.89/unit) based on the literature.30 (B) Simulated MVBP with discounted emicizumab scenario’s with 0% discount represents Dutch list price and base case (checked bar at €2476 per 1 mL vial 30 mg/mL), Time horizon: 10 years. FVIII = Factor VIII clotting factor.

The base case break-even point was estimated after 8.03 years for valrox compared to FVIII prophylaxis and 5.68 years when compared to emicizumab (see Figure 4).

F4
Figure 4.:
Return on investment expressed as breakeven point of net benefit. Return on investment expressed as breakeven point of net health benefit (A) and net monetary benefit (B). FVIII = Factor VIII clotting factor.

DISCUSSION

This early CEA shows that the intervention of the novel gene therapy valoctocogene roxaparvovec (valrox; Roctavian) compared to prophylactic FVIII as well as to emicizumab were estimated to result in greater QALYs gains for less costs resulting in dominated ICERs. Base case MVBP for valrox when compared to prophylactic FVIII was estimated at €2,622,663 and when compared to emicizumab €3,527,984. These estimates decreased to €701,067 and €779,405 under the most optimistic discount scenarios of FVIII and emicizumab, respectively. The cost-effectiveness and MVBP of valrox were found to be closely linked to price discounts of the FVIII clotting factor. To break-even on the initial irrecoverable upfront investment of valrox and to ensure net population health gains, it was estimated that the benefits (defined as FVIII > 5%) would need to be sustained at least 8.03 years compared to FVIII prophylaxis and 5.68 years compared to emicizumab. Although these estimates were associated with considerable uncertainty, they are in line with previous analyses of gene therapies in severe HA.19,20 To our knowledge, this is the first early CEA of valrox compared to prophylactic FVIII and emicizumab.

The economic evaluation conducted by Machin et al19 showed a dominated ICER over a 10-year time horizon but at lower cumulative costs and higher benefits. The lower costs can be explained as Machin et al19 included only direct medical costs, lower FVIII dosage, and lower valrox price (ie, $850,000/treatment). Additionally, the study assigned a utility of perfect heath (ie, 1.0) to patients after successful gene therapy treatment and did not include loss of efficacy over time, which in light of recent clinical findings may be an overestimation.9 Cook et al20 constructed a microsimulation model and was the first to include treatment waning. The incremental results reported by Cook et al20 also estimate valrox to be dominant compared to FVIII prophylaxis, but at higher costs.20 This difference can partially be explained by the US rates of FVIII costs which were approximately 3 times higher.20 After initiation of this study, the US Institute for Clinical and Economic Review (ICER-institute) published a report assessing valrox in HA.24 The biggest change compared to their previous report—assessing emicizumab and FVIII—is model structure.23 The latest US ICER-institute model uses a Markov model preceded by a decision tree and puts more emphasis on joint damage. Due to early onset FVIII prophylaxis used in The Netherlands since the 1970s, arthropathy is likely to be most relevant to the elderly HA population and, therefore, less appropriate in the younger population assessed in this study.

During this study, the European regulator issued a negative interim market authorization opinion for valrox and requested additional data.13 Consequently, the developer withdrew valrox’ market authorization application. Some preliminary (unpublished) interim evidence from an ongoing phase III trial has since became available, but full trial results are not expected until November 2024.12,13 In light of these events, our study was characterized as an early CEA in contrast to the studies previously published and discussed earlier.63 Early cost-effectiveness analyses are often conducted with less robust clinical data in early clinical development to explore major uncertainties and inform further, among other purposes, evidence generation and development strategies.25,64 Reassessment when new the evidence becomes available may decrease some uncertainty, but mostly will add to learnings of interpretation of early clinical data.65 To add, full pipelines of novel therapies are observed for HA, including extended half-life FVIII, nonreplacement therapies, and other gene therapies.66 By adding arms to this model, (early) economic evaluations will allow more rapid assessment of their relative-effectiveness and cost-effectiveness.

Although achieving incremental health benefits at lower costs sounds attractive, there are additional considerations which require further discussion. First, as previously mentioned, gene therapies with a sustained or curative claim are administered in the present time, as is the payment. The irreversible upfront treatment cost is only offset by future health benefits. Hence, benefit durability over time is critical and have so far not been clinically confirmed. If a therapy turns out to be less effective than initially claimed this treatment cannot be discontinued due to the one-off nature of provision, nor can the cost be recouped.67 Second, the initial budget impact and/or the proposed timing of payments may pose affordability challenges among payers.68 This raises the question whether affordability may not only be associated with high prices but also with timing of payment. Third, our results reflect benefits and cost on a population level. From the clinical evidence supporting this analysis, as well as previous work, it is known that intrapatient variability is considerable.9,20,51,69 This means that some patients may achieve incremental benefits for less costs, but also vice versa. Increasing insights and predictability of benefits on a patient level is of great interest in the hemophilia space and may decrease decision uncertainty.70,71 Last, cost-effectiveness is expressed a ratio between therapies. Therefore, the ICER measure may suggest an intervention is cost-effective—or even cost-saving—even when the comparator itself is not. This supports the interpretation of cost-effectiveness and affordability of novel interventions in a wider context than ICER estimates only. Additional research is needed to best interpret cost-effectiveness and affordability of one-off therapies with sustained effect, this may include additional measures such as—but not limited to—budget impact, break-even point, MVBP, and treatment durability.

Despite best efforts this study has some limitations. First, our analyses rely mostly on clinical data from a small clinical trial.9,51 Key parameters describing treatment durability are uncertain and showed considerable impact on outcomes. Also, the single arm design of the trial required indirect comparisons between model arms. Together with the different simulation approaches taken in the valrox arm (simulation of bleed rates using FVIII) and prophylactic arms (bleeds rates derived from the literature), this may cause additional bias which has not explicitly been quantified in our sensitivity analyses. However, these are limitations which decision makers will likely increasingly encounter. We aimed to address these limitations by, as described in guidelines, matching inputs based on patient characteristics and using effectiveness parameters from meta-analyses where possible.24,27,33 In addition, (irreversible) future side effects were not included as no supporting clinical evidence was available. Short-term side effects are immunological responses, which may lead to liver function abnormalities, decrease of FVIII and failure of therapy. We aimed to address the latter by including nonresponse in our estimates. Furthermore, the utilities applied in the model reflect HA patients with inhibitors as these were the only available estimates at that time for emicizumab.23 However, patients without inhibitors are expected to have a higher quality of life; therefore our utilities may be underestimated.5 Also, our approach to use FVIII to simulate bleeding rates in the gene therapy arm was done to incorporate treatment durability as well overcome the limitation that valrox and prophylactic FVIII benefits are FVIII-level driven, and emicizumab is not.72 The last limitation is that we did not take into account the costs and burden of administration of FVIII (intravenously) and emicizumab (subcutaneously) by the patients at home 3 times a week (around 1500 times and 250 times over 10 years, respectively), which may mean we underestimated societal costs and burden.

By modeling treatment waning, this is the first study comparing a gene therapy in HA to both FVIII prophylaxis and emicizumab. Other strengths of this study are demonstration of feasibility to include break even time and MVBP, which are not routinely included in (early) cost-effectiveness analyses. Estimation of break-even time can improve contextualization of the ICER for curative therapies, also outside the hemophilia field.68 Future research can further explore feasibility and informativeness to include expected value of information analyses (EVIs). EVIs provide strategic information when a “wrong” strategy is adopted, expected cost of uncertainty, and parameters for which additional research is most useful.73,74 This may be useful to design coverage-with-evidence development payment models and can also be applied earlier on in decision making. EVIs, together with a forgone-health-assessment, can also quantify net benefits (or losses) of postponement of market authorization, informing decision-making and prioritize additional data requests.54

Clinical interpretation

In this model, the decrease of FVIII expression over time in patients treated with valrox is portrayed as a gradual process. However, translation of FVIII expression to bleeding tendency in clinical practice is more dichotomous. As similar joint bleeding rates are observed when FVIII > 100% or FVIII > 15%.31 When FVIII intercepts approximately 10%, annual bleed rates increase considerably. Therefore, perhaps, the initial treatment effect and decrease in FVIII over time are less important than modeled here, as long as patients remain above FVIII > 15%. Also, reduction in FVIII treatment cost due to tenders, discounts, and other reasons were in general seen as a positive trend from a healthcare perspective.30 Although the introduction of new treatment options are welcomed by patients and physicians, they are also associated with high prices. This increases pressure on (hospital) budgets and raises economic and ethical concerns.69

To conclude, the results of this early CEA comparing valoctocogene roxaparvovec (valrox; Roctavian) to standard-half-life FVIII prophylaxis, and to emicizumab in severe hemophilia A without FVIII antibodies in The Netherlands estimated—in both comparisons—that incremental health gains were achieved for less costs. Second, we were able to incorporate treatment durability, a novel gene therapy-specific measure, in an early cost-effective model. In addition, the novel measures MVBP and break-even time were modeled and quantified. Base case MVBP was for valrox was €2,622,663 and €3,527,984 when compared to prophylactic FVIII and emicizumab, respectively. Break-even time was 8.03 and 5.68 years compared to FVIII and emicizumab, respectively. Future work should aim to better characterize uncertainties and increase translation of early cost-effectiveness analyses to inform product development and direct research efforts.

DISCLOSURES

FL discloses grants/research funding (CSL Behring, Sobi, Takeda, uniQure); consultant (BioMarin, Takeda, uniQure, CSL Behring [fees to university]); travel support (Sobi), DSMB Member Roche). All the other authors have no conflicts of interest to disclose.

SOURCES OF FUNDING

This research was supported by an unrestricted research grant from the Haemophilia Foundation (Stichting Haemophilia, https://www.haemophilia.nl).

REFERENCES

1. Fijnvandraat K, Cnossen MH, Leebeek FW, et al. Diagnosis and management of haemophilia. BMJ. 2012;344:e2707.
2. Mannucci PM, Tuddenham EGD. The hemophilias —from royal genes to gene therapy. N Eng J Med. 2001;344:1773–1779.
3. Srivastava A, Santagostino E, Dougall A, et al. WFH Guidelines for the Management of Hemophilia, 3rd edition. Haemophilia. 2020;26(suppl 6):1–158.
4. Nederlandse Vereniging van Hemofiliebehandelaars (NVHB). Guideline Diagnosis and Treatment of Hemophilia 2020 Richtlijn Diagnostiek en Behandeling van Hemofilie 2020 [in Dutch]. 03-02-2021. Available at: https://hematologienederland.nl/wp-content/uploads/2021/02/Richtlijn-Diagnostiek-en-Behandeling-van-Hemofilie-2020-geautoriseerde-versie-20210206-2.pdf. Accessed January 11, 2022.
5. Pedra G, Christoffersen P, Khair K, et al. The impact of factor infusion frequency on health-related quality of life in people with haemophilia. J Haemophilia Prac. 2020;7:102–109.
6. Detela G, Lodge A. EU regulatory pathways for ATMPs: standard, accelerated and adaptive pathways to marketing authorisation. Mol Ther Methods Clin Dev. 2019;13:205–232.
7. van Balen EC, Wesselo ML, Baker BL, et al. Patient perspectives on novel treatments in haemophilia: a qualitative study. Patient. 2019; 13:201–210.
8. Rangarajan S, Walsh L, Lester W, et al. AAV5-factor VIII gene transfer in severe hemophilia A. N Engl J Med. 2017;377:2519–2530.
9. Pasi KJ, Rangarajan S, Mitchell N, et al. Multiyear follow-up of AAV5-hFVIII-SQ gene therapy for hemophilia A. N Engl J Med. 2020;382:29–40.
10. Fuchs H, Bienaime JJ. Valoctocogene Roxaparvovec Phase 2 and Phase 3 Update. San Rafael: Biomarin; 2019. Available at: https://investors.biomarin.com/download/Valrox+Update_deck+__052919_Final_11am.pdf. Accessed January 11, 2022.
11. Eder C, Wild C. Technology forecast: advanced therapies in late clinical research, EMA approval or clinical application via hospital exemption. J Mark Access Health Policy. 2019;7:1600939.
12. Clinicaltrials.gov. Single-arm study to evaluate the efficacy and safety of valoctocogene roxaparvovec in hemophilia a patients (BMN 270-301). U.S. National Library of Medicine. 2021. Available at: https://clinicaltrials.gov/ct2/show/NCT03370913. Accessed July 21, 2021.
13. BioMarin announces positive phase 3 gene therapy trial results in adults with severe hemophilia a; study met all primary and secondary efficacy endpoints in one-year data set. 2021. Available at: https://investors.biomarin.com/2021-01-10-BioMarin-Announces-Positive-Phase-3-Gene-Therapy-Trial-Results-in-Adults-with-Severe-Hemophilia-A-Study-Met-All-Primary-and-Secondary-Efficacy-Endpoints-in-One-Year-Data-Set. Accessed July 21, 2021.
14. Noone D, Coffin D, Pierce GF. Reimbursing the value of gene therapy care in an era of uncertainty. Haemophilia. 2021;27:12–18.
15. Claxton K, Palmer S, Longworth L, et al. Informing a decision framework for when NICE should recommend the use of health technologies only in the context of an appropriately designed programme of evidence development. Health Technol Assess. 2012;16:1–323.
16. Hanna E, Tavella F, Rémuzat C, Auquier P, Toumi M. Market access of atmps: overview and expected challenges. Value Health. 2015;18:A518–A519.
17. Morrow D, Ussi A, Migliaccio G. Addressing pressing needs in the development of advanced therapies. Front Bioeng Biotechnol. 2017;5:55.
18. Jørgensen J, Kefalas P. The use of innovative payment mechanisms for gene therapies in Europe and the USA. Regen Med. 2021;16:405–422.
19. Machin N, Ragni MV, Smith KJ. Gene therapy in hemophilia A: a cost-effectiveness analysis. Blood Adv. 2018;2:1792–1798.
20. Cook K, Forbes SP, Adamski K, et al. Assessing the potential cost-effectiveness of a gene therapy for the treatment of hemophilia A. J Med Econ. 2020;23:501–512.
21. Azvolinsky A. Gene therapy “cure” for blindness wanes. Nat Biotechnol. 2015;33:678.
22. Zimmermann M, Lubinga SJ, Banken R, et al. Cost utility of voretigene neparvovec for biallelic RPE65-mediated inherited retinal disease. Value Health. 2019;22:161–167.
23. Rind D, Agboola F, Kumar V, et al. Emicizumab for hemophilia A: effectiveness and value final evidence report. 2018;1–162. Available at: https://icer.org/wp-content/uploads/2020/10/ICER_Hemophilia_Final_Evidence_Report_041618.pdf. Accessed January 11, 2022.
24. Rind DM, Agboola F, Herron-Smith S, et al. Valoctocogene roxaparvovec and emicizumab for hemophilia A: effectiveness and value. 2020;1–188. Available at: https://icer.org/wp-content/uploads/2020/10/ICER_Hemophilia-A_Final-Report_112020.pdf. Accessed January 11, 2022.
25. Retèl VP, Steuten LMG, Geukes Foppen MH, et al. Early cost-effectiveness of tumor infiltrating lymphocytes (TIL) for second line treatment in advanced melanoma: a model-based economic evaluation. BMC Cancer. 2018;18:895.
26. Hutton J, Trueman P, Henshall C. Coverage with evidence development: an examination of conceptual and policy issues. Int J Technol Assess Health Care. 2007;23:425–432.
27. Tan SS, Bouwmans CA, Rutten FF, et al. Update of the Dutch manual for costing in economic evaluations. Int J Technol Assess Health Care. 2012;28:152–158.
28. Jon Sussex AT, Devlin N. Operationalizing value-based pricing of medicines: a taxonomy of approaches. PharmacoEconomics. 2013;31:10.
29. Donners AAMT, Rademaker CMA, Bevers LAH, et al. Pharmacokinetics and associated efficacy of emicizumab in humans: a systematic review. Clin Pharmacokinet. 2021;60:1395–1406.
30. O’Mahony B, Noone D, Prihodova L. Survey of coagulation factor concentrates tender and procurement procedures in 38 European countries. Haemophilia. 2015;21:436–443.
31. Den Uijl IE, Mauser Bunschoten EP, Roosendaal G, et al. Clinical severity of haemophilia A: does the classification of the 1950s still stand? Haemophilia. 2011;17:849–853.
32. Mahlangu J, Oldenburg J, Paz-Priel I, et al. Emicizumab prophylaxis in patients who have hemophilia A without inhibitors. N Engl J Med. 2018;379:811–822.
33. Diemer F. Farmacotherapeutisch rapport emicizumab (Hemlibra®) als routineprofylaxe van bloedingen bij patiënten met ernstige hemofilie A zonder remmers tegen factor VIII [in Dutch]. Zorginstituut Nederland. 2019. Available at: https://www.zorginstituutnederland.nl/publicaties/adviezen/2020/02/17/pakketadvies-emicizumab-hemlibra. Accessed January 11, 2022.
34. Blanchette VS, Key NS, Ljung LR, et al. Definitions in hemophilia: communication from the SSC of the ISTH. J Thromb Haemost. 2014;12:1935–1939.
35. Fischer K, van Hout BA, van der Bom JG, et al. Association between joint bleeds and Pettersson scores in severe haemophilia. Acta Radiol. 2002;43:528–532.
36. Pettersson H, Ahlberg A, Nilsson IM. A radiologic classification of hemophilic arthropathy. Clin Orthop Relat Res. 1980;149:153–159.
37. Centraal bureau voor Statistiek [Statistics Netherlands]. The Hague, The Netherlands. Available at: https://www.cbs.nl/. Accessed November 5, 2019.
38. Zorginstituut Nederland, the Dutch Health Care Institute. Technology assessment emicizumab (Hemlibra R) [in Dutch]. 3. 2020:1–3. Available at: https://www.zorginstituutnederland.nl/binaries/zinl/documenten/adviezen/2020/02/17/pakketadvies-emicizumab-hemlibra/Pakketadvies+emicizumab+%28Hemlibra%C2%AE%29.pdf. Accessed January 11, 2022.
39. Burt RK, Balabanov R, Burman J, et al. Effect of nonmyeloablative hematopoietic stem cell transplantation vs continued disease-modifying therapy on disease progression in patients with relapsing-remitting multiple sclerosis: a randomized clinical trial. JAMA. 2019;321:165–174.
40. Hoefnagels JW, Schrijvers LH, Leebeek FWG, et al.. Adherence to prophylaxis and its association with activation of self-management and treatment satisfaction. Haemophilia. 2021;27:9.
    41. Antunes SV, Tangada S, Stasyshyn O, et al. Randomized comparison of prophylaxis and on-demand regimens with FEIBA NF in the treatment of haemophilia A and B with inhibitors. Haemophilia. 2014;20:65–72.
    42. Neufeld EJ, Recht M, Sabio H, et al. Effect of acute bleeding on daily quality of life assessments in patients with congenital hemophilia with inhibitors and their families: observations from the dosing observational study in hemophilia. Value Health. 2012;15:916–925.
    43. Fischer K, de Kleijn P, Negrier C, et al. The association of haemophilic arthropathy with health-related quality of life: a post hoc analysis. Haemophilia. 2016;22:833–840.
    44. Ballal RD, Botteman MF, Foley I, et al. Economic evaluation of major knee surgery with recombinant activated factor VII in hemophilia patients with high titer inhibitors and advanced knee arthropathy: exploratory results via literature-based modeling. Curr Med Res Opin. 2008;24:753–768.
    45. Zorginstituut Nederland. Farmacotherapeutisch Kompas. Available at: https://farmacotherapeutischkompas.nl. Accessed November 4, 2020.
    46. Dutch National Health Institute (Zorginstituut Nederland; ZIN). Drug costs in the Netherlands. [in Dutch]. 2019. https://www.medicijnkosten.nl/. Accessed January 20, 2022.
    47. Shrestha A, Eldar-Lissai A, Hou N, et al. Real-world resource use and costs of haemophilia A-related bleeding. Haemophilia. 2017;23:e267–e275.
    48. Dutch Healthcare Authority (Nederlandse Zorgautoriteit; NZa). DBC product-finder for tariffs. 2019. https://zorgproducten.nza.nl/. Accessed January 20, 2022.
    49. O’Hara J, Walsh S, Camp C, et al. The relationship between target joints and direct resource use in severe haemophilia. Health Econ Rev. 2018;8:1.
    50. Earnshaw SR, Graham CN, McDade CL, et al. Factor VIII alloantibody inhibitors: cost analysis of immune tolerance induction vs. prophylaxis and on-demand with bypass treatment. Haemophilia. 2015;21:310–319.
    51. Pasi KJ, Rangarajan S, Mitchell N, et al. First-in-human evidence of durable therapeutic efficacy and safety of AAV gene therapy over three-years with valoctocogene roxaparvovec for severe haemophilia A (BMN 270-201 study). Presented at the International Society of Thrombos. ISTH Academy; 2019. 274198.
    52. Roctavian,Hem A Gene Therapy, Sustains Drop in Bleeding Rates, Phase 3 Data Show. [press release]. BioNews Services, LLC. 2021. Available at: https://hemophilianewstoday.com/2021/01/13/gene-therapy-roctavian-reduces-bleeding-in-hemophilia-a-phase-3-trial-shows/?cn-reloaded=1. Accessed July 21, 2021.
    53. Soares MO, Sharples L, Morton A, et al. Experiences of structured elicitation for model-based cost-effectiveness analyses. Value Health. 2018;21:715–723.
    54. Briggs A, Claxton K, Sculpher M, et al. Decision Modelling for Health Economic Evaluation. 2nd ed. Oxford University Press; 2006:236.
    55. Mazza G, O’Hara J, Walsh S, et al. The impact of severe haemophilia and the presence of target joints on health-related quality-of-life. in Health Qual Life Outcomes. 2018;16:1–8.
    56. Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002;21:271–292.
    57. O’Mahony B. Guide to National Tenders for the Purchase of Clotting Factor Concentrates. 2nd ed. 2015:84. Available at: https://www1.wfh.org/publication/files/pdf-1294.pdf. Accessed July 20, 2021.
    58. Nederlandse Orthopaedische Vereniging [in Dutch Orthopedic Association]. Carepath protocol total knee replacement [in Dutch]. 2015:11. https://www.orthopeden.org/ Accessed January 20, 2022.
    59. Drummond MF, O’Brien B, Stoddart GL, Torrance GW. Methods for the Economic Evaluation of Health Care Programmes. Vol 2. 2nd ed. Oxford University Press; 1999:1–379.
    60. Briggs AH, Weinstein MC, Fenwick EA, et al.. Model parameter estimation and uncertainty analysis: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-6. Med Decis Making. 2012;32:722–732.
    61. Hatswell AJ, Bullement A, Briggs A, et al. Probabilistic sensitivity analysis in cost-effectiveness models: determining model convergence in cohort models. Pharmacoeconomics. 2018;36:1421–1426.
    62. Mladsi D, Earnshaw S, Akashi-Ronquest N, Keith M. Threshold pricing model: not just another cost-effectiveness model. Value Health. 2010;13:A332.
    63. Ijzerman MJ, Steuten LM. Early assessment of medical technologies to inform product development and market access: a review of methods and applications. Appl Health Econ Health Policy. 2011;9:331–347.
    64. Edmunds K, Scuffham P, Reeves P, et al. Demonstrating the value of early economic evaluation alongside clinical trials: exercise medicine for men with metastatic prostate cancer. Eur J Cancer Care (Engl). 2021;30:e13479.
    65. Ten Ham RMT, Hövels AM, Klungel OH, et al. Development and regulation of gene and cell-based therapies in Europe: a quantification and reflection. Trends Pharmacol Sci. 2020;41:67–71.
    66. Makris CHM. Disruptive technology and hemophilia care: the multiple impacts of emicizumab. Res Pract Thromb Haemost. 2021;5:1–6.
    67. Ten Ham RMT, Klungel OH, Leufkens HGM, et al. A review of methodological considerations for economic evaluations of gene therapies and their application in literature. Value Health. 2020;23:1268–1280.
    68. Jørgensen J, Kefalas P. Reimbursement of licensed cell and gene therapies across the major European healthcare markets. J Mark Access Health Policy. 2015;3:29321.
    69. Leebeek FWG, Miesbach W. Gene therapy for hemophilia: a review on clinical benefit, limitations, and remaining issues. Blood. 2021;138:9.
    70. Peters R, Harris T. Advances and innovations in haemophilia treatment. Nat Rev Drug Discov. 2018;17:18.
    71. Pierce G, Naldini L, Pipe S. Gene Therapy in Hemophilia. Presented at: World Federation of Hemophilia (WFH) Global Forum; June 15, 2019: Virtual: Medical Plenary Session.
    72. Bowyer A, Kitchen S, Maclean R. Effects of emicizumab on APTT, one-stage and chromogenic assays of factor VIII in artificially spiked plasma and in samples from haemophilia A patients with inhibitors. Haemophilia. 2020;26:536–542.
    73. Claxton K, Ginnelly L, Sculpher M, et al. A pilot study on the use of decision theory and value of information analysis as part of the NHS Health Technology Assessment programme. Health Technol Assess. 2004;8:1–103, iii.
    74. Oostenbrink JB, Al MJ, Oppe M, et al. Expected value of perfect information: an empirical example of reducing decision uncertainty by conducting additional research. Value Health. 2008;11:1070–1080.

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