Belantamab mafodotin for the treatment of relapsed/refractory multiple myeloma in heavily pretreated patients: a US cost-effectiveness analysis

ABSTRACT

Background

Patients with relapsed/refractory multiple myeloma (RRMM) require several lines of therapy, with typically shorter remission duration with each additional line.

Research design and methods

The cost-effectiveness of belantamab mafodotin (belamaf; DREAMM-2; NCT03525678) was compared with selinexor plus dexamethasone (SEL+DEX; STORM Part 2; NCT02336815) among patients with RRMM who have received at least four prior therapies. The base case used a US commercial payer’s perspective over a 10-year time horizon. Efficacy data were based on parametric survival analysis of DREAMM-2 and matching-adjusted indirect treatment comparison between DREAMM-2 and STORM Part 2, which assessed relative treatment effects between belamaf and SEL+DEX. Cost inputs included drug treatment, concomitant medications, adverse event management, subsequent treatments, and disease management.

Results

Belamaf decreased total treatment costs per patient by $14,267 and increased patient life years by 0.74 and quality-adjusted life years (QALYs) by 0.49 versus SEL+DEX. Patients receiving belamaf accrued 0.12 fewer progression-free life years versus patients on SEL+DEX.

Conclusions

From a US commercial payer’s perspective, belamaf had lower costs, and increased QALYs and life-year gain, compared with SEL+DEX. Belamaf is therefore likely to be a cost-effective treatment option for patients with RRMM who have received four or more prior lines of therapy.

KEYWORDS:

• Cost-effectiveness
• efficacy
• HRQoL
• modeling
• RRMM
• safety

1. Introduction

Multiple myeloma (MM) is the third most common hematological malignancy in the United States (US), accounting for 1.8% of all new malignancies [1]. Five-year survival for patients with MM in the US has improved over the past 20 years, from ~30% in 1990 to 53.9% in 2010–2016 [1]. However, MM remains incurable, and most patients eventually relapse and require several lines of therapy, with typically shorter remission duration with each additional line [2,3].

The current treatment landscape for relapsed/refractory MM (RRMM) includes, among other therapies, immunomodulatory agents, proteasome inhibitors (PIs), monoclonal antibodies (mAbs), histone deacetylase inhibitors, corticosteroids, and alkylators [4,5]. Despite multiple approved therapies, patients with RRMM may quickly exhaust treatment options as they experience more disease relapses [2,3]. This is particularly the case for heavily pretreated patients with RRMM, especially those who are refractory to three or more prior therapies [6,7]. Daratumumab, an anti-CD38 mAb, can be used to treat patients with RRMM who have received at least three prior therapies, including a PI and an immunomodulatory agent, or who are double-refractory to a PI and immunomodulatory agent [4,8]. However, the prognosis for patients who become unresponsive to anti-CD38 mAbs remains poor [9]. In the multicenter, retrospective MAMMOTH study, which reported outcomes for 275 patients with MM who were refractory to anti-CD38 mAbs (including daratumumab and isatuximab), median overall survival (OS) was 8.6 months [9]. The multicenter, single-arm, open-label STORM trial investigated the selective inhibitor of nuclear export, selinexor, in combination with dexamethasone (SEL+DEX). Selinexor is administered orally and selectively inhibits XPO1 by reactivating tumor-suppressing proteins and inducing tumor cell apoptosis [10]. The results of STORM reported a partial response or better observed in 26% of patients (95% confidence interval [CI]: 19, 35). This led to the approval of SEL+DEX in 2019 as a treatment option for patients with RRMM who have received at least four prior therapies and are refractory to two or more PIs, two or more immunomodulatory agents, and an anti-CD38 mAb [4,11,12]. Belantamab mafodotin (belamaf) is the first off-the-shelf humanized afucosylated antibody-drug conjugate targeting B-cell maturation antigen (BCMA) and has a multimodal mechanism of action [13,14]. In DREAMM-2, an open-label, multicenter study of single-agent belamaf 2.5 mg/kg Q3W, 31% of patients (97.5% CI: 20.8, 42.6) achieved an overall response [15]. Following this study, belamaf was approved in the US and received conditional authorization in the EU in August 2020, for the treatment of patients with RRMM who have received at least four prior therapies including a PI, an immunomodulatory agent, and an anti-CD38 mAb [15–18]. Both selinexor and belamaf offer an additional therapeutic option for patients with RRMM who have received at least four prior therapies. The STORM Part II study and DREAMM-2 Primary population were very similar which allowed the comparison of these studies [11,15] (Table 1).

Table 1. Patient population comparison DREAMM-2 versus STORM Part 2

	Belamaf	SEL+DEX
Populations	DREAMM-2 Primary Population (n = 97) [15]	STORM Part 2 (n = 122)* [11]
Percent (%) with at least 3 prior lines of therapy	100%	100%
Median number of prior lines	7	7
Percent (%) exposed to PI and an immunomodulatory agent	100% to PI and an immunomodulatory agent	100% to PI and an immunomodulatory agent
Percent (%) refractory to PI and an immunomodulatory agent	100% double class-refractory	100% triple class-refractory
Percent (%) exposed to anti-CD38 mAb	100%	100%
Percent (%) refractory to anti-CD38 mAb	100%	100%
Received active treatment following inclusion	Yes	Yes

* Modified intention to treatment population was N = 122, whereas safety population was N = 123

Anti-CD38 mAb, anti-CD38 monoclonal antibody therapy; belamaf, belantamab mafodotin; DEX, dexamethasone; OS, overall survival; PI, proteasome inhibitor; SEL, selinexor; SoC, standard of care.

We developed an economic model and evaluated the cost-effectiveness of belamaf from a US commercial payer’s perspective, compared indirectly with SEL+DEX, for adults with RRMM who have received four or more prior lines of therapy, including a PI, an immunomodulatory agent, and an anti-CD38 mAb (alone or in combination).

2. Methods

2.1. Study design and scope

2.1.1. Overview of study design and scope

This cost-effectiveness analysis (CEA) was based on the efficacy and safety results of DREAMM-2 (NCT03525678) [15]. A systematic literature review and feasibility assessment were performed to identify possible comparators for belamaf in terms of compatibility of trial population characteristics and clinical outcomes with DREAMM-2 [19]. Because DREAMM-2 specifically enrolled only patients who were double-class refractory to a PI and immunomodulatory agent, exposed to prior daratumumab therapy, and had received ≥3 prior lines of treatment, only SEL+DEX, as investigated in STORM (NCT02336815), was considered an appropriate comparator [11,15] (Table 1). STORM was a multicenter, open-label Phase IIb study of SEL+DEX in patients with RRMM who were refractory to bortezomib, carfilzomib, lenalidomide, and pomalidomide (quad-refractory disease); in STORM Part 2, patients were required to be refractory to daratumumab (penta-refractory disease) [11]. The CEA was performed from a US commercial payer’s perspective. Deterministic and probabilistic sensitivity analysis and scenario analyses were performed to investigate the impact of uncertain model inputs and structural assumptions on the cost-effectiveness outcomes of belamaf versus SEL+DEX.

2.1.2. Model structure

A partitioned survival model was developed incorporating the following health states: progression-free on-treatment, progression-free off-treatment, progressed, and dead (Figure 1). OS partitioned the cohort between alive and dead states; progression-free survival (PFS) partitioned alive patients between progression-free off-treatment and progressed; and time-to-discontinuation, progression assessed by an independent committee, or death (TTDPD) partitioned progression-free patients between on- and off-treatment. All patients were assumed to start as progression-free on-treatment and not receive treatment beyond progression. A 10-year time horizon was sufficient for all patients to reach the death health state. A weekly model cycle was selected to accommodate varying administration schedules and costs. Costs and health outcomes were discounted with a 3% annual discount rate based on the Institute for Clinical and Economic Review reference case [20].

Figure 1. Model structure: partition survival analysis model.

PFS partitioned patients between progression-free and progressed, and TTDPD partitioned progression-free patients between on- and off-treatment; OS partitioned patients between alive (progression-free or progressed) and dead.

OS, overall survival; PFS, progression-free survival; TTDPD, time to treatment discontinuation, progression, or death.

2.2. Data sources, inputs, and modeling

2.2.1. Clinical efficacy

Efficacy outcomes for belamaf were based on the 13-month data cut using the 2.5 mg/kg (approved dose) cohort (N = 97) from DREAMM-2 [15,16]. As the time horizon of the cost-effectiveness model (CEM) exceeds the follow-up in DREAMM-2, long-term efficacy was represented by parametric survival models fitted to observed Kaplan–Meier data from the trial. Following recommendations from the NICE Decision Support Unit [21], six parametric distributions were fitted to DREAMM-2 data: Weibull, log-logistic, lognormal, exponential, generalized gamma, and Gompertz. The selection of the best fitting parametric distribution for each population was based on statistical criteria for goodness-of-fit and clinical plausibility of extrapolations.

For OS, based on the combined Akaike information criterion (AIC) and Bayesian information criterion (BIC), and visual assessment of goodness-of-fit, the exponential distribution provided the best fit to the Kaplan–Meier data, with lognormal and log-logistic providing the second and third best fits (Table S1). The exponential distribution tail was also deemed plausible based on clinical opinion and was therefore selected in the base case. The lognormal and log-logistic distributions were considered in scenario analysis. Additionally, a scenario analysis was investigated by using a PFS-to-OS hazard ratio (HR) (Appendix S1.1).

For PFS assessed by an independent review committee, based on AIC and BIC and visual assessment of fitting quality, the generalized gamma distribution provided the best fit to the Kaplan–Meier data, with lognormal and log-logistic providing the second and third best fits (Table S1 [22]). Upon visual inspection, the generalized gamma distribution had a flat tail, which was deemed unlikely to be clinically plausible. Therefore, the lognormal distribution was selected in the base case and the log-logistic distribution was considered in scenario analysis.

OS and PFS models for SEL+DEX were based on matching-adjusted indirect comparison (MAIC) of DREAMM-2 versus STORM. An unanchored MAIC of available efficacy outcomes was conducted following NICE guidelines for population-adjusted indirect treatment comparisons [23]. The NICE Decision Support Unit guidelines recommend that imbalances in all known prognostic factors and treatment effect-modifiers be adjusted. To determine the list of factors included in the population adjustment, independent clinical experts were presented with a list of potential prognostic factors and effect-modifiers of OS and PFS. The base case MAIC model adjusted for imbalances in age (65–74, ≥75 years), sex, Eastern Cooperative Oncology Group performance status (1 or 2), extramedullary plasmacytomas (1 or more), creatinine clearance (≥60 mL/min), revised International Staging System score (I versus II versus III), cytogenetics (high risk defined as t[4;14], t[14;16], and 17p13del versus standard risk – all others), number of prior lines of therapy (≥5 versus ≥9), and refractory to the last line of therapy received. Patient populations were already comparable for refractory status to PI, immunomodulatory agents, and daratumumab, so no matching was required for these factors. Importantly, no comparative data could be found from the STORM Part 2 study population for frailty of patients at baseline beyond creatinine clearance, or for extramedullary disease or presence of lytic bone lesions at baseline, two important prognostic factors highlighted by the clinical experts and/or the prognostic factor investigations. The resulting MAIC HRs of belamaf versus SEL+DEX were 0.53 (95% CI: 0.34, 0.83; p = 0.005) for OS and 1.29 (95% CI: 0.87, 1.92; p = 0.199) for PFS. The unadjusted HRs were 0.60 (95% CI: 0.41, 0.88; p = 0.01) for OS and 1.15 (95% CI: 0.80, 1.66; p = 0.438) for PFS, and were tested in scenario analysis. Details on the MAIC approach have been reported elsewhere [19].

2.2.2. Treatment discontinuation

For treatment discontinuation of belamaf, to avoid crossing of the PFS distribution with the estimate for TTDPD, a HR linking PFS with TTDPD was derived by jointly fitting PFS and TTDPD data from DREAMM-2. This HR reflected the excess risk of treatment discontinuation before progression, in addition to the risk of progression or death. Jointly fitting PFS and TTDPD yielded a HR of 1.43 (95% CI: 1.04, 1.97; p = 0.027). Parametric distributions were also fitted to the Kaplan–Meier data of TTDPD for belamaf with the log-logistic distribution providing the best fit in terms of AIC and BIC (Table S1). This distribution was considered in scenario analysis. Published TTDPD for SEL+DEX has not been identified. To represent treatment discontinuation for SEL+DEX, the PFS HR from MAIC was applied to the treatment discontinuation estimate of belamaf to obtain the equivalent estimate for SEL+DEX.

2.2.3. Costs and resource utilization

The cost categories included in the CEM (Table S2) covered drug acquisition and administration, disease management, adverse event (AE) management, subsequent treatments, treatment-specific monitoring, and concomitant medication costs.

Drug acquisition costs were based on the belamaf 2.5 mg/kg Q3W arm of DREAMM-2, assuming a mean dose intensity of 82.8% to account for dose modifications and adjustments. Drug acquisition costs for SEL+DEX were based on SEL 80 mg + DEX 20 mg twice weekly in 4-week cycles (assumed 100% dose intensity as dose intensity data for STORM Part 2 have not been published). Wholesale acquisition costs were considered for SEL+DEX, and if multiple strengths were available, the cheapest strength was chosen. Vial sharing was considered in the base case for belamaf by accounting for the distribution of patients’ mean weight = 78.4 kg (standard deviation [SD] = 21.8 in DREAMM-2), and the different vial sizes per treatment.

Drug administration costs for SEL+DEX were assumed to be $0 as both medications are administered orally. Belamaf administration (intravenous [IV]) costs considered the number of doses per administration cycle and the duration of administration, which was assumed to be a 30-min infusion in a physician’s office, with a cost of $546 per IV infusion, based on the cost of IV infusion of up to 1 hour for single or initial substance, sourced from InHealth (2019) [24]. The resulting monthly administration cost for belamaf was $791.

Disease management costs (Table S3) were modeled by health state and were based on a micro-costing approach. A survey on resource use requirements for managing the disease manifestations of RRMM was developed and circulated to nine US clinicians [25]. The survey enquired about the type, frequency, and proportion of patients requiring visits to health-care professionals, laboratory and imaging tests, or other procedures [25]. In the base case, the resource use categories reported in Pelligra et al. (2017) were used [26]. These included visits to a hematologist, laboratory tests (complete blood count, FREELITE test, complete chemistry panel, blood immunofixation, serum protein electrophoresis), and transfusions [26]. In scenario analysis, alternative resource use categories were modeled based on the resource use survey [25]. This scenario included visits to health-care professionals (hematologist, primary care physician, nurse), laboratory tests (complete blood count, FREELITE test, complete chemistry panel, blood immunofixation, serum protein electrophoresis, serum albumin, serum β-2 microglobulin), and imaging tests (bone x-ray). The base case and scenario analysis used a resource survey to inform on both the proportion of patients receiving each resource and the frequency of administration [25]. Unit costs were based on reimbursed national rates for commercial insurers from InHealth (2019) [24]. In the base case, monthly disease management costs were $947 for progression-free on-treatment, $630 for progression-free off-treatment, and $1,178 for progressed health states. A one-off terminal care cost of $5,516 was applied at the time of death. This was calculated based on clinicians’ responses on the type and duration of resources required at terminal care (palliative nurse home visit, palliative care unit admission, hospice admission) and their cost per day [24].

The incidence of AEs for belamaf and incidence of AEs for SEL+DEX were obtained from Lonial et al. (2020) and Chari et al. (2019) respectively [11,15]. Only Grade 3 or 4 AEs reported for at least 5% of patients treated with either belamaf or SEL+DEX were considered. The AE incidence was converted to a probability per model cycle using the median treatment duration in DREAMM-2 and STORM (9 weeks [3 treatment cycles] for belamaf and 9 weeks for SEL+DEX) [11,15]. AE incidence and the calculated monthly probabilities based on treatment duration are shown in Table S4. The costs per event for most AEs were selected from published literature and inflated to 2019 dollars using the medical component of the Consumer Price Index (Table S5) [27]. For keratopathy, the mean cost per episode was derived from MarketScan data [25]. In scenario analysis, AE costs were calculated based on a micro-costing approach, for which the resource use requirements for each AE were derived from the responses of nine US clinicians.

Subsequent treatment costs were applied to patients who progressed at each model cycle. In the base case, the distribution of subsequent treatments in individual regimens (Table S6) was based on the average of estimates provided by nine US clinicians. A weighted-average, one-off cost for subsequent treatments was calculated using the subsequent treatments’ distribution, assuming an average treatment duration of 3.1 months, which was reported in the MAMMOTH study for patients refractory to anti-CD38 therapy with a median of four prior lines of therapy [9]. Each regimen was costed based on dosage information from FDA prescribing information, and the per-unit wholesale acquisition cost.

Monthly treatment monitoring costs were included in the model and were based on recommended imaging, laboratory tests, physician visits, and platelet transfusions identified from the FDA’s prescribing information for belamaf and SEL+DEX [16,28]. Unit costs were based on reimbursed national rates for commercial insurers [24]. Monthly monitoring costs for each regimen are summarized in Table S2. All belamaf-treated patients were assumed to have monitoring and ophthalmology visits related to potential ocular AEs every 3 weeks.

Concomitant medications (Table S7) associated with each regimen were modeled based on the FDA labels of belamaf and SEL+DEX [16,28]. If drug classes were recommended instead of a specific drug, US key opinion leaders were consulted. Unit costs were based on the lowest available average wholesale price for each treatment listed in the Red Book (2019) [29]. Patients receiving belamaf were assumed to administer preservative-free lubricant eye drops once daily, with an estimated cost of $5.64 per month. Patients receiving SEL+DEX were assumed to take ondansetron 8 mg once daily by mouth, with an estimated cost of $9.63 per month.

2.2.4. Health utilities

In DREAMM-2, disease-specific measures of quality of life (QoL) were collected using the European Organization for Research and Treatment of Cancer questionnaires QLQ-C30 and QLQ-MY20, and were mapped to the European QoL-5 Dimensions (EQ-5D) using a published mapping algorithm [30]. EQ-5D utility scores were analyzed using mixed-effects linear models [25]. The utility model selected as base case included two health states: progression-free and progressed. Health state utility weights were 0.73 (SD = 0.02) for progression-free and 0.66 (SD = 0.03) for progressed patients; Table S8). Scenario analysis evaluated the impact of alternative EQ-5D utility weights derived from the KarMMa study [31].

Utility decrements were applied to patients experiencing Grade 3 or 4 AEs (summarized in Table S5). The utility decrement for dry eye was assumed to be the same as for blurred vision. The duration of each AE, upon which the disutility is applied, was based on responses received from nine US clinicians [25]. The duration of hypophosphatemia, hyponatremia, hypokalemia, hyperglycemia, hypercalcemia, and mental status change was not available; for these AEs, a duration of 28 days was assumed.

2.3. Model validation and analysis

The model was developed in Microsoft Excel and was validated based on the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) framework and current guidelines from the International Society for Pharmacoeconomics and Outcomes Research-Society of Medical Decision Making [32,33]. Validation included conceptual validity with key opinion leaders and technical verification of the programming implementation. Details are provided in the text section of the Supplementary appendix (S1.2) [38-44].

One-way sensitivity analysis was conducted to test the impact of uncertainties of individual model parameters on the incremental net monetary benefit. This was completed by individually testing the upper and lower bounds of model parameters. Probabilistic sensitivity analysis (PSA) of 1,000 Monte Carlo simulations was performed to explore uncertainty of model parameters simultaneously using underlying parametric distributions. A willingness-to-pay threshold of $100,000 per quality-adjusted life-year (QALY) was used per the Institute for Clinical and Economic Review’s value assessment framework [34]; and scenario analysis was conducted to understand cost-effectiveness of belamaf versus SEL+DEX when key base case assumptions were varied.

3. Results

3.1. Base case analysis

Over a 10-year time horizon, belamaf decreased total treatment costs per patient by $14,267, and increased patient life years by 0.74 and QALYs by 0.49, versus SEL+DEX. Therefore, belamaf was dominant to SEL+DEX. Patients receiving belamaf accrued 0.12 fewer progression-free life years (PFLYs) versus patients receiving SEL+DEX. This result was driven by relative effects of OS and PFS, which indicated that belamaf has longer OS and shorter PFS than SEL+DEX.

Health outcomes, cost by treatment, and incremental cost per LY/QALY/PFLY gained are summarized in Table 2.

Table 2. Cost-effectiveness analysis: base case with 10-year time horizon

Outcomes	Belamaf	SEL+DEX	Difference, belamaf versus SEL+DEX
Life-year
PFLYs (Overall)	0.62	0.74	−0.12
On-treatment	0.37	0.52	−0.15
Off-treatment	0.25	0.23	0.03
PPLYs	1.01	0.15	0.86
TOTAL	1.63	0.89	0.74
QALY
PFQALYs (Overall)	0.44	0.52	−0.08
On-treatment	0.26	0.35	−0.10
Off-treatment	0.19	0.17	0.02
PPQALYs	0.67	0.10	0.57
TOTAL	1.11	0.62	0.49
Costs (2019 US dollars)
Drug acquisition	$105,498	$145,405	−$39,907
Drug administration	$3,417	$0	$3,417
Concomitant medication	$25	$60	−$35
Treatment monitoring	$2,473	$1,892	$581
AE management	$7,193	$21,880	−$14,686
Disease management	$29,268	$17,258	$12,010
Progressed disease	$6,121	$7,571	−$1,450
Progressed disease	$23,147	$9,687	$13,459
Subsequent treatment	$64,661	$40,307	$24,353
Total	$212,535	$226,802	−$14,267

AE, adverse event; belamaf, belantamab mafodotin; DEX, dexamethasone; PFLY, progression-free life-year; PFQALY, progression-free quality-adjusted life-year; PPLY, post-progression life-year; PPQALY, post-progression quality-adjusted life-year; QALY, quality-adjusted life-year; SEL, selinexor.

3.2. Sensitivity analyses

3.2.1. One-way sensitivity analysis

One-way sensitivity analysis revealed that incremental net monetary benefit (using a $100,000/QALY willingness-to-pay threshold) was most sensitive to changes in drug acquisition costs per cycle, the HR for PFS of SEL+DEX versus belamaf, and patient body weight (Figure 2).

Figure 2. Cost-effectiveness analysis: one-way sensitivity analysis.

*The incremental net monetary benefit is the incremental QALYs per patient multiplied by willingness-to-pay minus incremental cost per patient, calculated using a $100,000/QALY willingness-to-pay threshold. AE, adverse event; belamaf, belantamab mafodotin; BSC, best supportive care; DEX, dexamethasone; HR, hazard ratio; ICER, incremental cost-effectiveness ratio; OS, overall survival; PFS, progression-free survival; QALY, quality-adjusted life-year; SEL, selinexor; TTDPD, time to treatment discontinuation, progression, or death.

3.2.2. Probabilistic sensitivity analysis

Results from 1,000 Monte Carlo simulations were summarized in the incremental cost-effectiveness plane (Figure 3a) and the cost-effectiveness acceptability curve (Figure 3b). Most PSA simulations fell in quadrants I and IV. At a willingness-to-pay threshold of $100,000 per QALY gained, belamaf was dominant (cost-effective) over SEL+DEX in 87% of the PSA simulations. At a threshold of $50,000 per QALY gained, belamaf was dominant in 76% of the simulations.

Figure 3. (a) Cost-effectiveness analysis: Probabilistic sensitivity analysis results, cost-effectiveness plane. (b) Cost-effectiveness analysis: Probabilistic sensitivity analysis results, cost-effectiveness acceptability curve.

The diagonal dashed line (a) represents the willingness-to-pay threshold at $100,000/QALY.

Belamaf, belantamab mafodotin; DEX, dexamethasone; QALY, quality-adjusted life-year; SEL, selinexor.

3.2.3. Scenario analysis

With the adjustment of various assumptions of the base case, belamaf was dominant to SEL+DEX in almost all scenarios (Table 3). Scenarios with changes in OS, PFS, or TTDPD had the largest impact on cost and survival outcomes.

Table 3. Cost-effectiveness analysis: scenario analysis

Scenario	Incremental results, belamaf versus SEL+DEX
	Life-year	QALY	Cost (2019 US dollars)	ICER/QALY ($)
Base case	0.74	0.49	−$14,267	Dominant
General settings
Time horizon = five years	0.67	0.45	−$15,976	Dominant
Time horizon = lifetime (40 years)	0.74	0.49	−$13,913	Dominant
Discount rate for cost and health outcomes = 0%	0.78	0.52	−$14,676	Dominant
Discount rate for cost and health outcomes = 6%	0.70	0.47	−$13,848	Dominant
Efficacy
Alternative extrapolations for OS (belamaf): lognormal	1.27	0.84	−$17,321	Dominant
Alternative extrapolations for OS (belamaf): log-logistic	1.24	0.82	−$14,133	Dominant
Alternative extrapolations for PFS-IRC (belamaf): log-logistic	0.74	0.50	−$17,959	Dominant
Alternative TTDPD for belamaf: log-logistic	0.74	0.49	−$5,983	Dominant
Alternative OS HR of belamaf versus SEL+DEX: 0.60	0.63	0.42	−$35,772	Dominant
Alternative PFS HR of belamaf versus SEL+DEX: 1.15	0.74	0.49	−$7,315	Dominant
OS based on PFS/OS HR	−0.74	−0.50	−$64,123	Less costly and less effective
PFS and OS equivalence	0.00	0.00	−$1,914	Dominant
Costs
Disease management from resource use survey [25]	0.74	0.49	−$7,527	Dominant
AE costs based on micro-costing from resource use survey [25]	0.74	0.49	−$222	Dominant
Negligible cost for managing AE: mental status change	0.74	0.49	−$12,859	Dominant
Negligible cost for managing AE: keratopathy	0.74	0.49	−$16,352	Dominant
Utilities
Alternative utility value for progressed health state from the KarMMA study [31] (progression-free: 0.78 progressed: 0.76)	0.74	0.57	−$14,267	Dominant

AE, adverse events; belamaf, belantamab mafodotin; DEX, dexamethasone; HR, hazard ratio; ICER, incremental cost-effectiveness ratio; IRC, independent review committee; OS, overall survival; PFS, progression-free survival; QALY, quality-adjusted life-year; SEL, selinexor; TTDPD, time to discontinuation, progression, or death.

4. Discussion

Over a 10-year time horizon, in this CEA of adult patients with RRMM who received four or more prior lines of therapy, belamaf was dominant to SEL+DEX, extending patients’ lifetime by 0.74 years, increasing QALYs by 0.49, and decreasing costs per patient by $14,267. These results were driven by the relative effects for OS and PFS. Based on indirect comparisons of DREAMM-2 and STORM, patients treated with belamaf had longer OS and shorter PFS than SEL+DEX. The longer OS resulted in additional life years and was a major driver of the incremental QALYs. The shorter PFS contributed to fewer PFLYs and lower drug costs for belamaf. While the observed imbalance between OS and PFS relative effects is not clearly understood, the long-term OS benefits may be explained by the long duration of response achieved in patients who received belamaf in DREAMM-2 (the unadjusted and MAIC-adjusted hazard ratios for duration of response of belamaf versus SEL+DEX were 0.41 and 0.32, respectively). Additionally, the longer OS with belamaf may also be attributed to a longer post-progression period.

One-way sensitivity analysis revealed that results were most sensitive to variations in the HR for PFS of SEL+DEX versus belamaf, the drug costs for SEL+DEX, and patient body weight. After accounting for the parameters of uncertainty, PSA showed that belamaf would remain the cost-effective or dominant treatment option 87% of the time when a willingness-to-pay ratio of $100,000/QALY is considered. To assess the impact of structural uncertainty on the cost-effectiveness results, various scenarios were tested. These included alternative distributions for OS, PFS, and TTDPD, use of unadjusted OS and PFS HRs obtained without population matching, alternative costing approach for disease management and adverse event costs, and alternative utility values, as well as the impact of time horizon and discounting. Belamaf remained dominant over SEL+DEX in 16 of the 17 additional scenarios. In one scenario, in which OS was derived from PFS using an OS-to-PFS relation, belamaf was less costly and less effective. Details on the OS-to-PFS relation are given in Appendix S1.1.

In the absence of a directly comparable cost-effectiveness study in terms of population and interventions, the results from our study were compared with other cost-effectiveness studies on treatment of RRMM [20,26,35,36]. Unsurprisingly, the health outcomes for both belamaf and SEL+DEX were lower than in other cost-effectiveness studies owing to more heavily pretreated populations in DREAMM-2 and STORM. However, health outcomes were in line with those reported in the NICE technology appraisal guidance (TA510) [37] for daratumumab that included a more comparable population. Key cost outcomes (drug acquisition, AE management, disease management, and subsequent treatment) were within range of the outcomes reported in other published CEAs.

The findings of this study should be interpreted in light of modeling limitations. Drug acquisition costs were modeled based on belamaf 2.5 mg/kg Q3W, but patients enrolled in DREAMM-2 could have a dose reduction to 1.92 mg/kg if they had an AE [15]. If an AE was reported at the 1.92 mg/kg dose level, treatment was delayed. Furthermore, the MAIC analysis may not have balanced all major differences in trial designs (e.g. schedule of PFS assessments) or included all prognostic factors or effect modifiers in the matching process. Despite matching populations based on reported data, unavailable data for STORM Part 2 patient characteristics at baseline may have confounded cross-trial comparisons. For instance, other than creatinine clearance, data describing frailty of patients at baseline were not reported for STORM Part 2. Three important prognostic factors identified by the clinical experts and exploratory analyses using data from the DREAMM-2 study – extramedullary disease, presence of lytic bone lesions at baseline, and baseline levels of serum BCMA – were also not available. Rerunning the analyses by matching populations on these factors should be considered if STORM Part 2 study data become available.

5. Conclusion

This economic evaluation determined that belamaf treatment of adult patients with RRMM who received four or more prior lines of therapy (including a PI, an immunomodulatory agent, and an anti-CD38 mAb) yielded lower costs and a QALY gain compared with SEL+DEX, over a 10-year period. Belamaf is therefore cost-effective from a US commercial payer’s perspective and represents an option for equitable care of heavily pretreated patients with RRMM who have limited treatment options.

Author contributions

A Nikolaou, A Shah, W Ma, V Kapetanakis, and J Willson were involved in the conception or design of the study and data acquisition, analysis, and interpretation. A Ambavane was involved in the conception and design of the study and acquisition of data. J Tosh was involved in data acquisition, analysis, and interpretation. F Wang, C Hogea, B Gorsh, B Gutierrez, S Sapra, and Y Samyshkin were involved in the conception or design of the study and data analysis and interpretation. A Suvannasankha was involved in data analysis and interpretation. All authors were involved in the drafting of the paper, revising it critically for intellectual content, and the final approval of the version to be published, and agree to be accountable for all aspects of the work.

Declaration of interest

A Nikolaou, A Ambavane, A Shah, W Ma, J Tosh and V Kapetanakis are employees of Evidera who received research funding from GSK. J Willson, F Wang, B Gorsh, B Gutierrez, S Sapra and Y Samyshkin are employees of and have stocks and shares in GSK. A Suvannasankha has received consulting fees from GSK, Janssen, and Karyopharm Therapeutics; research funding from Bristol-Myers Squibb, Celgene, GSK, and Janssen; personal fees from GSK and Janssen; and is supported by the Veterans Affair merit award (BX004514). C Hogea was an employee of GSK at the time this analysis was conducted.

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Data sharing statement

GSK makes available anonymized individual participant data and associated documents from interventional clinical studies which evaluate medicines, upon approval of proposals submitted to www.clinicalstudydatarequest.com. To access data for other types of GSK sponsored research, for study documents without patient-level data and for clinical studies not listed, please submit an enquiry via the website.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Clinical trial registration

www.clinicaltrials.gov identifiers are NCT03525678 and NCT02336815

Acknowledgments

The authors would like to thank Gene Felber for his contributions to conceptualization of the initial study design.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This study was funded by GlaxoSmithKline (GSK; 207155). GSK contributed to the study design, implementation, data collection, interpretation, and analysis. Medical writing support was provided by Muchaala Yeboah, PhD, and Sharon Bryant, DPT, of Fishawack Indicia, Ltd., part of Fishawack Health, and funded by GSK.