Cost-effectiveness model of trastuzumab deruxtecan as second-line treatment in HER2-positive unresectable and/or metastatic breast cancer in Finland

Paulissen, Jeroen H. J. et al. Article — Published Version Cost-effectiveness model of trastuzumab deruxtecan as second-line treatment in HER2-positive unresectable and/ or metastatic breast cancer in Finland The European Journal of Health Economics Provided in Cooperation with: Springer Nature Suggested Citation: Paulissen, Jeroen H. J. et al. (2023) : Cost-effectiveness model of trastuzumab deruxtecan as second-line treatment in HER2-positive unresectable and/or metastatic breast cancer in Finland, The European Journal of Health Economics, ISSN 1618-7601, Springer, Berlin, Heidelberg, Vol. 25, Iss. 4, pp. 689-699, https://doi.org/10.1007/s10198-023-01617-3 This Version is available at: https://hdl.handle.net/10419/318006 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) 1 3 The European Journal of Health Economics (2024) 25:689–699 https://doi.org/10.1007/s10198-023-01617-3 ORIGINAL PAPER Cost‑effectiveness model oftrastuzumab deruxtecan assecond‑line treatment inHER2‑positive unresectable and/ormetastatic breast cancer inFinland JeroenH.J.Paulissen1,2 · AhmedH.Seddik3 · KyleJ.Dunton4· ChristopherJ.Livings5· MarinusvanHulst1,6 · MaartenJ.Postma1 · LisaA.deJong1 · RoelD.Freriks2,7 Received: 27 January 2023 / Accepted: 26 June 2023 / Published online: 24 July 2023 © The Author(s) 2023 Abstract Objectives Trastuzumab deruxtecan (T-DXd) was recently recommended by the Committee for Medicinal Products for Human Use as a treatment for adult patients with unresectable or metastatic HER2-positive breast cancer, who had received a prior anti-HER2-based regimen. In our study, we evaluated the cost-effectiveness of T-DXd compared with ado-trastuzumab emtansine (T-DM1) for this indication in Finland. Methods A three-state partitioned survival analysis model was developed with a payer’s perspective. Time to event data from the DESTINY-Breast03 (DB-03) trial were extrapolated over a lifetime horizon either directly—for progression-free survival and time to treatment discontinuation—or using an alternative approach utilizing long-term T-DM1 survival data and DB-03 data—for overall survival. Discount rates of 3% were applied for costs and effects. Inputs were sourced from the Medicinal Products Database from Kela, Helsinki University Hospital service price list, Finnish Medicines Agency assessments, clinical experts, and DB-03. Sensitivity analyses were performed to characterize and demonstrate parameter uncertainties in the model. Results Total quality-adjusted life years (QALYs) and life years (LYs) gained for T-DXd compared with T-DM1 were 1.93 and 2.56, respectively. Incremental costs for T-DXd compared with T-DM1 were €106,800, resulting in an ICER of €55,360 per QALY gained and an ICER of €41,775 per LY gained. One-way sensitivity analysis showed the hazard ratio of T-DXd vs T-DM1 for OS was the most influential parameter. The probabilistic sensitivity analysis showed similar results to the base case. Conclusions T-DXd is cost-effective based on surrogate WTP thresholds of €72,000 and €139,000 per QALY. Keywords Cost-effectiveness· Breast cancer· Metastatic· HER2-positive· Trastuzumab deruxtecan JEL Classification D61 Introduction Breast cancer was the cause of 968 deaths in Finland in 2020 and, with 4885 new cases that year, it was also the most common newly diagnosed cancer [1]. Patients with unresectable and/or metastatic breast cancer (uBC and/or mBC) experience significantly impacted quality of life [2], and disease management is associated with high costs [3]. Though mBC is treatable, it remains incurable, and breast cancer subtype is a strong predictor of survival [4]. A subtype of interest for targeted treatments is human epidermal growth factor receptor 2 overexpressing (HER2-positive) * Jeroen H. J. Paulissen [email protected] 1 Department ofHealth Sciences, University Medical Center Groningen, Groningen, TheNetherlands 2 Asc Academics, Groningen, TheNetherlands 3 Daiichi Sankyo Europe GmbH, Munich, Germany 4 Daiichi Sankyo UK Ltd, Uxbridge, UK 5 AstraZeneca Plc., Cambridge, UK 6 Department ofClinical Pharmacy andToxicology, Martini Hospital, Groningen, TheNetherlands 7 Department ofEconomics, Econometrics andFinance, Faculty ofEconomics & Business, University ofGroningen, Groningen, TheNetherlands 690 J.H.J.Paulissen et al. 1 3 disease, which accounts for approximately 15–20% of breast cancers [5]. In the past two decades, treatment advances and the rise of monoclonal antibodies have improved survival outcomes for HER2-positive advanced breast cancer patients, and targeted therapies are approved for multiple lines in the treatment pathway for HER2-positive mBC [6]. In the first line, the European Society for Medical Oncology (ESMO) clinical practices guidelines for advanced breast cancer recommend the combination of trastuzumab–pertuzumab–taxane as standard for HER2-positive mBC [7]. In the second line, ado-trastuzumab emtansine (T-DM1) had been the gold standard for this indication since 2012 based on the EMILIA trial results, and until recently, there had been no advances in second-line treatment since its introduction [4, 7]. Trastuzumab deruxtecan (T-DXd) is an HER2-directed antibody–drug conjugate that was recently recommended by the Committee for Medicinal Products for Human Use for approval as indicated for adult patients with HER2-positive uBC and/or mBC who had received a prior anti-HER2based regimen [8]. Approval was recommended based on results from the phase 3 DESTINY-Breast03 (DB-03) trial, which compared T-DXd with T-DM1 in patients previously treated with a taxane and trastuzumab. T-DXd demonstrated improved progression-free survival (PFS, hazard ratio [HR] 0.28; 95% CI 0.22 to 0.37; p < 0.001) and overall survival (OS, HR 0.55; 95% CI 0.36 to 0.86; p = 0.007, prespecified significance boundary not reached) compared with T-DM1 [9]. The ESMO guidelines now recommend T-DXd as the preferred second-line treatment for HER2-positive uBC and/ or mBC [7]. The aim of this study was to evaluate the cost-effectiveness of T-DXd compared with T-DM1 as a second-line treatment for adult patients with HER2-positive uBC and/ or mBC previously treated with trastuzumab and a taxane in Finland. Methods A partitioned survival analysis (PartSA) model, widely used to assess cost-effectiveness in oncology treatments, was developed in Microsoft Excel (2016) to evaluate the cost-effectiveness of T-DXd compared with T-DM1 as a second-line treatment for adult patients with HER2-positive uBC and/or mBC previously treated with trastuzumab and a taxane in Finland. The model compared T-DXd with T-DM1, and model structure and inputs were determined using clinical trial data (DB-03; data cutoff date: May 21, 2021; median duration of follow-up: 16.2months [0–32.7] with T-DXd and 15.3months [0–31.3] with T-DM1), literature reviews, and consultation with clinical and health economic experts. The analysis was conducted from a payer’s perspective, aligned with previous Fimea assessments [10, 11]. Outcomes were the incremental cost-effectiveness ratio (ICER) calculated as cost per quality-adjusted life year (QALY) gained and the ICER calculated as cost per life year (LY) gained. A discount rate for costs and effects of 3% per annum was applied [12]. The cycle length was 3weeks, aligned with the dosing schedule from DB-03. This cycle length was short enough to capture clinically and economically meaningful events between cycles. Half-cycle correction was applied. A lifetime horizon of 41years was used in the base case analysis to capture all essential costs and health effects [12]. Additionally, several analyses were performed to determine the model sensitivity to parameter uncertainty, including a one-way sensitivity analysis (OWSA) and a probabilistic sensitivity analysis (PSA), and scenario analyses were performed to assess the robustness of the model. The study followed the Professional Society for Health Economics and Outcomes Research (ISPOR) Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist and adhered to good reporting practice for health economic evaluations [13]. Patient characteristics The modelled cohort comprised patients aged 18years or older with HER2-positive uBC and/or mBC previously treated with trastuzumab and a taxane, based on the patient population from the DB-03 trial [9]. The mean age of the model cohort was 54.4years, the proportion of female patients was 99.6%, and the average weight and body surface area were 62.40kg and 1.65m2, respectively (Table1), based on the unpublished DB-03 clinical study report. These characteristics were used to calculate ageand sex-dependent inputs (such as general population mortality) and drug dosing requirements. Model structure A three-state PartSA model was developed consisting of three health states: progression free, post-progression, and death (Fig.1). Health states were mutually exclusive. Patients entered the model in the progression-free state and received either T-DXd or T-DM1. Patients in this state could remain progression free, their disease could progress, or they could die. Patients could remain progression free while receiving T-DXd or T-DM1 (on treatment) or patients could remain progression free without receiving treatment (off treatment). Off-treatment patients were not able to return to treatment at a later time point. Patients in the post-progression state could not return to the progression-free state, but they could remain alive in the post-progression state, or they could die. 691 Cost‑effectiveness model oftrastuzumab deruxtecan assecond‑line treatment inHER2‑positive… 1 3 Table 1 Summary of model inputs for patient characteristics and medical, resource use, and adverse event costs Parameter Model input Reference Patient characteristics Mean age 54.4years DB-03 clinical study report Percent female 99.6% Average weight 62.40kg Average body surface area 1.65 m2 Costs Drug Costs (per vial) Dose (every 3weeks) T-DXd 100mg €1660.00 5.4mg/kg DB-03 clinical study report, Kela [14] T-DM1 100mg €1817.45 3.6mg/kg T-DM1 160mg €2907.92 3.6mg/kg Administration costs Oral €0 Assumption Parenteral €160aHUH [15] Health state utilities T-DXd T-DM1 Progression free 0.8181 0.8009 DB-03 clinical study report Progressed 0.5403 0.5403 DB-03 clinical study report, Lloyd etal. [16] Resource use and costs Resource Cost Number per cycle Specialist physician/oncologistb€86.86c0.27 Mäklin etal., Fimea T-DXd [10, 17] Blood testsb€21.24d1.02 [10, 17] ECHO/MUGA-scanning, cardiological examinationb€269.99e0.09 [10, 17] CT scanningb€161.16f0.27 [10, 17] Nurse visitb€36.63c0.45 [10, 17] End of life Last 60days of life €9148.17 20% Haltia etal. [18] Adverse event costs (per event) Adverse event Costs Neutrophil count decrease €258.48 Mäklin etal. [17] Anaemia €1189.86 Mäklin etal., Fimea Nivolumab [11, 17] White blood cell decrease €258.48 [17] Platelet count decrease €258.48 [17] Nausea €238.60 [17] Increased AST € 238.60 [17] ILD €4112.70 [17] LVEF decrease €3189.70 [17] AST aspartate aminotransferase, CT computerized tomography, DB-03 DESTINY-Breast03, ECHO echocardiogram, HUH Helsinki University Hospital, ILD interstitial lung disease, LVEF left ventricular ejection fraction, MUGA multigated acquisition, T-DM1 ado-trastuzumab emtansine, T-DXd trastuzumab deruxtecan a V1182010/V1182011/V1182012 b Used in both progression-free and post-progression health states c Outpatient care d Codes combined: 2474, 1552, 2203, 4520, 4594, 2516/6024, 4586, 1999, 1046/4587, 1128/4591, 1026/1024 e NA3BG f NA3AD 692 J.H.J.Paulissen et al. 1 3 State membership was determined from the PFS and OS curves reported in the DB-03 trial, as shown in Fig.1. PFS was used to determine the proportion of patients in the progression-free health state over time. OS was used to inform membership in the death state. For the post-progression state, state membership was derived from the difference between the OS and PFS curve at each time point. Time to treatment discontinuation (TTD) data from DB-03 was used to distinguish between patients in the progression-free state who are on treatment and those who are off treatment. Clinical parameters Standard parametric models—exponential, Weibull, Gompertz, log-logistic, log-normal, generalized gamma, and gamma—were fitted to the TTD and PFS data from DB-03 using their distribution parameters (Table1—Supplementary Information 1) [12]. The best fit was selected based on goodness-of-fit statistics, visual inspection, and clinical plausibility of the long-term extrapolations. For OS, an alternative approach was used, described in detail below. Time totreatment discontinuation andprogression‑free survival In the base case, TTD data from DB-03 were directly extrapolated to estimate TTD for patients in the T-DM1 and T-DXd arms, and the log-normal distribution was used for both arms. PFS data from DB-03 were also directly extrapolated to estimate PFS for patients in the T-DM1 and T-DXd arms in the base case. The log-normal was the best fit for T-DXd, while the generalized gamma provided the best fit for T-DM1; however, the Pharmaceutical Pricing Board guidelines suggest fitting separate parametric models of the same type to both arms [12]. Furthermore, the log-normal distribution resulted in the closest median PFS to the median PFS observed in DB-03 for T-DXd (investigator assessed) and T-DM1 (assessed by BICR)—25.1 and 6.8months, respectively (Tables3 and 5—Supplementary Information 1), based on the unpublished DB-03 clinical study report. Thus, log-normal distributions were used for both arms (Table2 and 4—Supplementary Information 1). The resulting PFS curves for T-DXd and T-DM1 are shown in Fig.2. Overall survival OS event rates from DB-03 were not high enough to inform long-term direct extrapolations. For this reason, an alternative approach adapted from similar published methods was used in the base case [19, 20]. This approach generates a curve using data from two sources: DB-03 OS KM data was used for both T-DXd and T-DM1 until the time point at which the last death was observed (20months). After 20months, the curves for both T-DXd and T-DM1 were generated using long-term T-DM1 OS data from the EMILIA clinical trial and the HR for T-DXd versus T-DM1 from the unpublished DB-03 clinical study report (0.56, 95% CI 0.36 to 0.86) [21]. The EMILIA trial compared T-DM1 to lapatinib plus capecitabine in patients with HER2positive advanced breast cancer who had previously been treated with trastuzumab and a taxane, with a follow-up of 20months [21]. The EMILIA data was validated through Fig. 1 Structure of the PartSA model demonstrating the health state membership across time for the progression-free (on treatment and off treatment), post-progression, and death health states. OS overall survival, PartSA partitioned survival analysis, PFS progressionfree survival, S(t) survival over time, t time, TTD time to treatment discontinuation 693 Cost‑effectiveness model oftrastuzumab deruxtecan assecond‑line treatment inHER2‑positive… 1 3 Fig. 2 Kaplan–Meier survival curves and resulting survival curves used in the model for PFS (A) and OS (B). Kaplan–Meier curves were constructed based on the unpublished DB-03 clinical study report. Log-normal parametric distributions were fitted to the Kaplan–Meier curve for PFS of T-DXd and T-DM1. Generalized gamma parametric distribution was fitted to the digitized T-DM1 Kaplan–Meier curve for OS from EMILIA [1] and attached to the Kaplan–Meier survival curve to create T-DM1 OS estimates. The resulting OS curve for T-DM1, Kaplan–Meier survival curve for T-DXd, and HR from DB-03 were used to create T-DXd OS estimates. DB-03 DESTINY-Breast03, KM Kaplan–Meier, OS overall survival, PFS progression-free survival, T-DM1 ado-trastuzumab emtansine, and T-DXd trastuzumab deruxtecan 694 J.H.J.Paulissen et al. 1 3 multiple methods (provided in Supplementary Information 2) and deemed to reflect anticipated long-term outcomes for the DB-03T-DM1 arm. The approach comprised the following steps: 1. Standard parametric models were fitted to the long-term EMILIA OS for T-DM1 and assessed on goodness-offit statistics, visual inspection, and clinical plausibility of the extrapolations. Since standard parametric models were not fitted to DB-03T-DM1 data directly, an additional analysis of clinical plausibility was performed (Supplementary Information 2). The generalized gamma distribution was selected as the best fit and used to generate the extrapolated tail of the curve. 2. Two hazard rate functions were calculated: one based on the T-DM1 curve resulting from the previous step (after 20months), and one based on the DB-03T-DM1 data (until 20months only). 3. These two hazard rate functions were combined into one hazard rate function by assigning the hazard rates calculated from the DB-03T-DM1 data to each time point until 20months and assigning the hazard rates from the generalized gamma fit to EMILIA T-DM1 to each time point from 20months onwards. 4. The T-DM1 OS curve for the model was derived from this combined hazard rate function. 5. The T-DXd OS curve was constructed using the KM data from DB-03, the derived T-DM1 OS curve, and the HR from DB-03. Until 20months, the T-DXd OS curve was based on the KM data from DB-03. After 20months, the HR from DB-03 was applied to the T-DM1 OS curve to calculate the T-DXd OS curve. Combining these together creates the final T-DXd OS curve used in the model. The resulting OS curves for T-DXd and T-DM1 are shown in Fig.2. Adverse events The base case analysis included the costs associated with adverse events (AEs) with a severity of Grade 3 or higher when 5% or more patients in one of the treatment arms experienced AE. Additionally, costs associated with interstitial lung disease and decrease in left ventricular ejection fraction were included in the model regardless of incidence or severity, as these were considered AEs of special interest in DB-03. Incidence of AEs for T-DXd and T-DM1 were sourced from the unpublished DB-03 clinical study report. AE costs were only incurred in the first cycle of the model, concurrent with treatment initiation. Health state utilities Treatment-specific progression-free health state utilities (Table1) were sourced from the DB-03 trial. It was assumed these captured disutility. Post-progression health state utilities (Table1) were derived from the algorithm developed by Lloyd etal. using overall baseline characteristics from the unpublished DB-03 clinical study report [16] (Eq.1—Supplementary Information 1). Costs andresource use Costs included in the model were drug and administration costs, costs of disease management, end-of-life costs, and treatment costs for AEs (summarized in Table1). Drug costs were sourced from the Medicinal Products Database from Kela [14]. Administration costs were sourced from the Helsinki University Hospital service price list [15]. Type and frequency of resource use were sourced from previous technology assessments by the Finnish Medicines Agency (Fimea) and validated by Finnish clinical experts [10]. Resource costs and AE-related costs were sourced from the Finnish Institute for Health and Welfare or previous Fimea assessments and have been adjusted to 2021 using consumer price index from the Statistics Finland [11, 17, 22]. Subsequent treatment costs—consisting of drug and administration costs—were sourced from previous Fimea assessments [10, 23]. The proportion of patients receiving a specific treatment option after T-DXd or T-DM1 was based on Finnish clinical expert opinion (Table7—Supplementary Information 1). The proportion of patients receiving any treatment option as subsequent treatment was sourced from the unpublished DB-03 clinical study report—i.e. 60.7% and 76.1% for patients in the T-DXd arm and T-DM1 arm, respectively. It was assumed that patients received subsequent treatment until death. Relative dose intensity A relative dose intensity (RDI) was applied to the T-DXd and T-DM1 dose. The RDI was taken from the unpublished DB-03 clinical study report. Sensitivity andscenario analyses One‑way sensitivity analysis (OWSA) An OWSA was conducted to demonstrate the impact of parameter uncertainty by varying parameters individually within their 95% confidence interval or by plus or minus 20% of the base case value. Parameters with set values (e.g. drug costs) were not varied as they do not bring uncertainty to the model. 695 Cost‑effectiveness model oftrastuzumab deruxtecan assecond‑line treatment inHER2‑positive… 1 3 Probabilistic sensitivity analysis (PSA) A PSA was conducted to comprehensively characterize parameter uncertainty by varying all input parameters for 1000 iterations. The cost parameters were sampled from gamma distributions, and the HR from DB-03 of T-DXd versus T-DM1 for OS was sampled from a log-normal distribution. Other inputs, such as utility values, incidence of AEs, incidence of AE-related hospitalizations, proportions of patients, and RDI were sampled from beta distribution. To account for correlation between parameters in survival distributions, a Cholesky decomposition algorithm was used [24]. Scenario analysis The model also incorporated scenario analyses exploring structural model uncertainty by changing the model time horizon, discount rates, vial sharing, no half-cycle correction, background mortality, the proportion of patients receiving subsequent therapy, the health state utility source, and provides a scenario in which the DB-03 OS data was directly extrapolated using the distribution with the best statistical fit (i.e. log-logistic). Results Base case results Over a lifetime horizon, the deterministic results show the total QALYs and LYs gained for T-DXd compared to T-DM1 were 1.93 and 2.56, respectively. Incremental costs for T-DXd compared to T-DM1 were €106,800, resulting in an ICER of €55,360 per QALY gained and an ICER of €41,775 per LY gained. Sensitivity andscenario analyses One‑way sensitivity analysis The 20 most influential parameters in the OWSA are presented in Fig.3. The results show that parameter uncertainty has the greatest impact on the ICER for the following: the HR of T-DXd vs T-DM1 for OS; the RDI used for T-DXd; the progression-free utility value for T-DXd; the patients in the T-DM1 arm receiving any subsequent treatment; and the post-progression utility value for T-DXd. Probabilistic sensitivity analysis The mean probabilistic results (using the average costs and QALYs of all iterations) generated by varying the base case settings randomly within their respective boundaries produced a mean ICER of €56,084 per QALY gained for Fig. 3 Tornado diagram of the ICER of T-DXd versus T-DM1. Adm administration, CT computerized tomography, Distr distribution, gen. gam generalized gamma, HR hazard ratio, ICER incremental costeffectiveness ratio, Log norm log-normal, OS overall survival, PF progression free, PFS progression-free survival, PP post-progression, Prop proportion, RDI relative dose intensity, Res resources, T-DXd trastuzumab deruxtecan, T-DM1 ado-trastuzumab emtansine, Txt treatment, Subs. subsequent treatment 696 J.H.J.Paulissen et al. 1 3 T-DXd compared with T-DM1 (Table8—Supplementary Information 1). The mean ICER resulting from the PSA is close to the base case ICER of €55,360 per QALY, which demonstrates the robustness of the model and the base case. Figure4 shows the cost-effectiveness plane of T-DXd versus T-DM1, where the incremental health outcomes (in QALYs) of T-DXd are plotted against the incremental costs of T-DXd for 1000 iterations. Most iterations (approximately 99%) indicate that T-DXd has higher costs and more QALYs gained compared to T-DM1. In the absence of a clear willingness-to-pay (WTP) threshold in Finland, the results of the Fimea assessment of T-DXd as a third-line treatment in HER2-positive mBC were used as a surrogate WTP threshold that are likely to be accepted by decision makers. Two surrogate thresholds were identified: €72,000 per QALY and €139,000 per QALY [10]. The cost-effectiveness acceptability curve showed that T-DXd versus T-DM1 has a likelihood of 68.40% and 95.40% of being cost-effective versus the surrogate WTP thresholds of €72,000 per QALY and €139,000 per QALY, respectively (Fig.5—Supplementary Information 1). Scenario analysis A scenario using rates of subsequent treatment from Cortés etal.—29.9% for the T-DXd arm and 62.4% for the T-DM1 arm—resulted in an ICER of €55,135 per QALY [9]. Results from scenarios exploring utility values for the progression-free and post-progression health states did not differ substantially from the base case ICER. The greatest effect was seen when applying treatment-specific health state utilities from DB-03 to both health states (€64,136 per QALY), followed by applying utilities derived from Lloyd with DB-03 patient characteristics to both health states (€58,012 per QALY), and applying non-treatmentspecific health state utilities from DB-03 to both health states (€55,452 per QALY). Extrapolating the DB-03 OS data using the direct extrapolation resulted in an ICER of €68,588 per QALY. Results of all scenario analyses are shown in Table9—Supplementary Information 1. Discussion T-DXd was recently recommended as a second-line treatment for HER2-positive mBC in the ESMO clinical guidelines [7]. This recommendation was based on the improved survival outcomes for T-DXd compared with T-DM1 as second-line treatment for HER2-positive mBC demonstrated in the DB-03 clinical trial [9]. This is the first study to evaluate the cost-effectiveness of T-DXd in this patient population. We used DB-03 trial results to conduct a costeffectiveness analysis comparing T-DXd with T-DM1 for the second-line treatment after trastuzumab and a taxane of HER2-positive uBC and/or mBC from the Finnish payer’s perspective. The results show that, using prices from Kela's Fig. 4 Cost-effectiveness plane of T-DXd versus T-DM1. PSA probabilistic sensitivity analysis, QALY quality-adjusted life year