論文ID: CR-25-0123
Background: Chronic heart failure (CHF) affects millions worldwide, posing a significant burden on healthcare resources. For patients with HF with reduced ejection fraction (HFrEF) following a worsening event, vericiguat is a promising new treatment. In this study we evaluated the budgetary impact on Japan’s health system with the introduction of vericiguat as an add-on to standard of care (SoC) for chronic HFrEF after a worsening event.
Methods and Results: An economic model was developed comparing SoC to a scenario in which vericiguat is introduced as an add-on therapy over a 5-year time horizon. A literature review, medical claims data and clinical trial data were used to derive inputs. Total healthcare costs after introducing vericiguat were estimated to increase <1% over 5 years compared to the SoC scenario showing a cumulated budget impact of US$41,027,304. Increases were driven by drug and medical costs, but were partially offset by decreasing costs for hospitalizations, terminal care, and urgent HF visits. In the sensitivity analyses, the hospitalization rate had the largest effect on the overall budget impact.
Conclusions: This analysis highlighted the minimal budgetary impact of vericiguat and its potential to reduce hospitalizations in Japan. Although drug and monitoring costs increased, reductions in acute care expenses helped offset these costs. Further research is needed on long-term cost-effectiveness and real-world outcomes.
Heart failure (HF) is a clinical syndrome characterized by inadequate cardiac output to meet metabolic demands, and it is an increasing global healthcare burden, including in Japan. Although there have been no large-scale population-based studies in Japan, it is estimated that there may be approximately 1 million patients with chronic HF (CHF) placing a considerable burden on the healthcare system.1,2 With aging populations and rising prevalence, HF affects more than 64 million people worldwide,3,4 and elderly patients have a worse prognosis than younger patients.5 Thus, there is an urgent need to explore innovative therapeutic options to enhance HF management, to prevent repeated HF-related hospitalizations.6
It is common for CHF patients to experience exacerbations that require hospital admissions, emergency room visits, and increased safety-related expenses.7 In particular, patients with reduced ejection fraction (HFrEF) have even higher medical resource use and costs mainly due to recurrent inpatient hospitalizations.8 Acute episodes experienced by these patients may often be worsening events, defined as medical occurrences that require hospitalization or the initiation of intravenous diuretic therapy in the outpatient setting. These worsening events are experienced in about 30% of HFrEF patients and contribute to reduced long-term prognoses and quality of life.9
Vericiguat, a novel soluble guanylate cyclase stimulator, has emerged as a potential therapeutic option for CHF through its enhancing of the production of cyclic guanosine monophosphate (cGMP), leading to vasodilation and a reduction in myocardial fibrosis.10 It has shown promising results in clinical trials conducted outside Japan, demonstrating efficacy and safety in reducing HF hospitalizations and improving patient outcomes.10,11 Vericiguat is approved for use in the USA by the US Food and Drug Administration for the treatment of adult patients with HFrEF following a worsening event, and was approved in Japan in 2021 for clinical use.12–14 In the current treatment landscape of HFrEF in Japan, vericiguat may be a promising option based on the findings of the VICTORIA study,15 a randomized placebo-controlled double-blinded phase 3 trial that showed a therapeutic benefit for vericiguat in lowering the incidence of HF hospitalizations or cardiovascular (CV) death.12 A previous budget impact analysis (BIA) of vericiguat as an add-on therapy to guideline-directed medical therapy (GDMT) for the treatment of chronic HFrEF following a worsening event conducted from the US payer perspective showed only limited budget impact, predominately driven by drug costs, but offset by reduced cost of hospitalizations and CV deaths.16
In light of the known clinical course of chronic HFrEF and the potential economic burden associated with its care, a BIA was performed to understand the implications of introducing vericiguat into the Japanese healthcare system, including consideration of drug costs, associated medical procedures, and the downstream savings resulting from improved HF management.
A model was developed to assess the budget impact of adding vericiguat as an add-on therapy to standard of care (SoC) for the treatment of chronic HFrEF following a worsening event in the Japanese healthcare system. A schematic model structure is presented in Figure 1 and was previously applied to the US population from a commercial health plan perspective over a 3-year horizon.16 The model compared 2 scenarios: without vericiguat (i.e., SoC alone) representing the current market state, and with vericiguat as add-on therapy to SoC.
Budget impact model structure: schematic illustration of the model used in the analysis comparing 2 scenarios. Scenario 1 represents the current market landscape with only standard of care (comparator) being used in the clinical practice. In scenario 2, vericiguat is used as an add-on treatment to the comparator. Parameters related to cost of drug and healthcare resource utilization were entered for each treatment.
Model Overview
The analysis was conducted from the Japanese payer’s perspective. The base case considered a 5-year time horizon (2022–2026). All cost inputs and results were calculated in Japanese yen then converted into US dollars using the exchange rate as of August 1, 2022 at the time of study initiation (133.2 Japanese yen, ¥=1 US dollar, $).
The daily dose of vericiguat used in the model was escalated up to week 5 according to the recommended posology reported in the summary of product characteristics.17 The recommended starting dose is 2.5 mg once daily, and the dose is doubled approximately every 2 weeks to reach the target maintenance dose of 10.0 mg once daily. Patients are assumed to remain on treatment as long as they are alive, and the dosing schedule for week 12 is reflective of the schedule for the remainder of life. Only direct medical costs were included.
This BIA considered efficacy data from the intention-to-treat population of the VICTORIA trial,15 and considered data from a cost-effectiveness model (CEM) of vericiguat on top of a background of SoC, which was used in the previous research.18 The budget impact model comprised a Markov structure built with 3 health states: Alive, Post HF hospitalization event 1, and Post HF hospitalization event ≥2 (Supplementary Figure 1). The areas under the respective survival curves and treatment-specific health state occupancy per year generated by the CEM were used as inputs in the model. To ensure that the model was reflective of real-world treatment practices, and in line with the Japanese healthcare system, local Japanese data for the population and economic parameters were obtained from the Portal Site of the Official Statistics of Japan (e-Stat), a targeted literature review (TLR), and an analysis of the Medical Data Vision Co., Ltd. (MDV) database, and, where appropriate, validated by expert opinion from key opinion leaders.
Targeted Literature ReviewThe purpose of the TLR was to identify Japan-specific data (e.g., demographics, SoC, costs, resource activities) and treatment options for inclusion in the model. The TLR search strategies were run on 2 online bibliographic databases (PubMed and ICHUSHI). The methods outlined for the TLR followed the principles published by the Cochrane Collaboration and the UK’s National Institute for Health and Clinical Excellence (NICE).19 The initial search identified 147 studies and after further examination, a total of 20 studies were deemed eligible for data extraction. Population of interest parameters, including starting age of target population, prevalence of HF, annual incidence of HF, and proportion of chronic HFrEF among HF cases, comprised the majority of key findings from publications included in the TLR. Also, some publications reported SoC components for chronic HFrEF patients.
MDV Database AnalysisThe MDV database is an electronic health records-based database comprising anonymized hospital data from 445 hospitals, which cover approximately 26% of acute care hospitals and data for about 40 million people. Although MDV database is hospital-based, contributing hospitals have outpatient clinics where many patients receive care. The MDV database includes diagnosis-procedure combination claims,20 detailed inpatient and outpatient encounters, drugs prescribed, diagnoses, and laboratory tests performed. Types of inpatient and outpatient encounter data included drugs (e.g., written prescriptions, brand name, dose, number of days’ supply), drug indication, medical practice data (e.g., date of visit, name of practice, department visited), diagnoses (e.g., date of diagnosis, date(s) of visit/inpatient stay, ICD-10 diagnosis codes), laboratory tests performed, and laboratory test results. Other data elements in the database include patient demographics (e.g., age, sex), cost data, and data on hospital characteristics.
The latest price of the relevant drugs based on national drug price listings were identified, and the cost and healthcare resource utilization (HCRU) of the relevant procedures and health services in Japan were obtained from the MDV database analysis. The study population was defined as adult patients who, regardless of hospitalization history, were diagnosed with chronic HFrEF with a prior worsening HF event, and the identification period was from October 1, 2008, to March 31, 2019. The index date corresponded to the date of the first HFrEF diagnosis during the identification period.
In conducting this analysis, the following conditions, [1] and (([2] and [4]) or ([4]and [6]) or [3] or [5]) were defined as patients with HFrEF.
[1] Patients with any HF diagnosis (ICD10: I50x recorded as the primary disease or the disease that triggered hospitalization) for the first inpatient claim (index hospitalization (IH) recorded as hospitalization for treatment purposes) within the identification period AND ≥1 diagnosis of HF (ICD10: I50x) within the look back period (6 months prior to index date).
[2] Patients with no atrial fibrillation (ICD 10: I48x) diagnosis during the IH.
[3] Patients with ≥1 claim with a diagnosis of myocardial infarction (disease codes: 8846988, 8832376, 8834919, 8847059, 8847060) before the IH admission date.
[4] Patients with ≥1 claims for β-blockers (EphMRA ATC code CX7XX) during the 180 days before or 30 days after the IH discharge date.
[5] Patients with ≥1 claim with a diagnosis of dilated cardiomyopathy (ICD-10: I420) before the IH admission date.
[6] Patients with ≥1 claim with cardiac rehabilitation (receipt codes: 180027410, 180027510) before the IH discharge date.
We used inpatient data for HFrEF prevalence estimates due to better documentation of EF status. However, for NYHA classification, we relied on outpatient data because functional status is more commonly assessed in ambulatory care settings. The first HF-related hospitalization and/or intravenous diuretic use (inclusive of the ATC code of EphMRA: C03A (diuretics)) with the code for injection use that occurred post-index date was considered a worsening event, and the subsequent 12-months was considered the follow-up period.
The key outcomes extracted from the MDV database analysis included the patient’s baseline characteristics, treatment patterns, HCRU, and costs. For each HCRU parameter, patients were identified following the 3 Markov health states.
Model InputsPopulation The eligible population was defined as adult patients with chronic HFrEF (LVEF <45%) following a worsening event in line with the VICTORIA trial population.15 The size of the population was estimated using both the prevalence and incidence data for chronic HFrEF patients in Japan based on the data obtained from the TLR, national statistics sources, and MDV database analysis. Details of the population inputs considered for the model are presented in Table 1. To estimate the eligible population over the model time horizon, the model included incident and prevalent cases entering the model at year 1 and annual incident cases entering the model in the following years. The eligible population size was estimated to be 104,667 patients in the first year. After the first model year, the total patients in each subsequent year consisted of a mix of (1) incident patients entering the model in the current year, and (3) patients entering the model in the previous year(s) and remaining alive for the current year. The base case model variables were set to reflect the standard Japanese chronic HFrEF patients.
Population Inputs Used in the Budget Impact Model
| Parameter | Value | Reference |
|---|---|---|
| Total population of interest in Japan | 125,340,000 | e-Stat, Feb 202228 |
| Start age of target population | 30 | Starting age chosen for MDV database analysis |
| Proportion of population aged 30 years and over | 73.7% | e-Stat, Feb 202228 |
| Prevalence of HF (as %) | 0.5% | Calculation based on 2020 Patient Survey by Ministry of Health, Labor and Welfare (age ≥30 years)29 |
| Annual incidence of HF (as %) | 0.1% | Annual sex- and age-standardized incidence rate based on Marume et al. (2022)24 |
| Proportion of HF with HFrEF | 47.7% | Hamaguchi (2012)30; HFrEF was 48% in Kinugawa (2019, SMILE study31) |
| Average proportion of people diagnosed (NYHA class II–IV) | 85.7% | Tsuji (2017, CHART-2 Registry32) |
| Proportion of people eligible for vericiguat + SoC | 46.2% | MDV database analysis results |
| Proportion of eligible people starting treatment | 99.8% | MDV database analysis results |
| Annual % growth of general population | −0.6% | e-Stat, July 202233 |
HF, heart failure; HFrEF, HF with reduced ejection fraction; NYHA, New York Heart Association; SoC, standard of care.
Comparator Selection Due to the variability of existing treatments for chronic HFrEF in Japan, the SoC components and other comparators were based on expert opinion, following initial findings from the MDV analysis. In this analysis the SoC comprised angiotensin-converting enzyme inhibitors, angiotensin-receptor blockers, β-blockers, mineralocorticoid receptor antagonists and ivabradine. The SoC treatment distribution from the VICTORIA trial was used as the starting point and assumed to be constant over time.15 Patients are assumed to remain on treatment for as long as they were alive, which meant that no treatment stopping rules were applied in the model.
Market Shares The existing and projected market shares for chronic HFrEF patients following a worsening event in the scenarios with vericiguat being introduced on the market, considering actual distribution and sales forecast. An incremental increase in vericiguat + SoC utilization rate every year was assumed for the base case (0.4% in 2022; 2.0% in 2023; 4.0% in 2024; 6.0% in 2025; 8.0% in 2026). Market share of SoC in the world without vericiguat was 100% across the time horizon because it was the sole comparator. The market shares applied to both disease incidence and prevalence. For simplicity, it was assumed that the market shares already accounted for the possibility of treatment switching between treatment options.
Clinical Inputs The clinical inputs of first HF hospitalization and CV death were based on the primary composite outcome in the VICTORIA trial (Supplementary Table 1). The number of HF hospitalization and CV deaths were estimated from the primary composite outcome (combining first HF hospitalization or CV death). The budget impact model was based on CV death, given the relatively short time horizon and the fact that there was no statistically significant difference in non-CV deaths between the 2 arms. It was assumed that the subsequent HF hospitalization proportion may occur in the same year as the first HF hospitalization.
Costs and Resource Use Drug costs were retrieved from the KEGG DRUG database, and mean costs for hospitalizations, clinical visits, adverse events (AEs), and terminal care were obtained from the MDV database analysis (Supplementary Table 2). Daily drug acquisition costs for vericiguat and each individual were calculated as the product of the unit cost per tablet and number of tablets per day for each drug based on the average daily doses obtained from the MDV database analysis (Supplementary Table 3).
Sensitivity and Scenario Analyses To examine the robustness of the analysis result, one-way deterministic sensitivity analyses were performed. For the sensitivity analysis, ±20% of values for base case analysis was used for all tested parameters. To address uncertainties related to population estimates of HF incidence and prevalence, 2 separate scenarios were pursued in which annual rates were calculated with 10% fewer and 10% more incident HF patients, and also with 10% fewer and 10% more prevalent HF patients. The budget impact was also examined in relation to lower and higher market share scenarios compared to the base case for introduction of vericiguat into the Japanese population over the 5-year horizon. The lower market share scenario comprised a more modest incremental increase in vericiguat + SoC utilization rate every year (0.4% in 2022; 1.0% in 2023; 2.0% in 2024; 3.0% in 2025; 4.0% in 2026). The higher market share scenario comprised a larger incremental increase in vericiguat + SoC utilization rate every year (0.4% in 2022; 3.0% in 2023; 6.0% in 2024; 9.0% in 2025; 12.0% in 2026). Market share of SoC in the world without vericiguat was 100% across the time horizon because it was the sole comparator.
Using a payer perspective over a horizon of 5 years starting from 2022, the base case analysis was run on a total of 104,677 patients eligible for HF treatment with vericiguat, estimated on the total population of Japan of adults aged ≥30 years. Without vericiguat introduced into the market and costs completely attributed to SoC for HFrEF, the estimated total budget was $6,996,499,269, reflecting about 5–8% increase per year over the previous year (Table 2). When vericiguat was introduced at projected annual utilization rates of 0.4%, 2.0%, 4.0%, 6.0%, and 8.0%, the budget was estimated to be $1,206,792,996 in year 1, $1,298,070,008 in year 2, $1,411,184,607 in year 3, $1,514,087,340 in year 4, and $1,607,391,623 in year 5, resulting in a total budget of $7,037,526,573 (Table 2). In both scenarios, the amount increased gradually over the horizon for all cost categories, except for costs related to AEs, because rates were applied to both incident and prevalent patients in the first year and only to incident patients in the following years.
Total Health Care Costs With Standard of Care Only (Without Vericiguat) and Scenario With Vericiguat as an Add-On Treatment
| Cost category | Year | Cumulative healthcare costs ($) |
||||
|---|---|---|---|---|---|---|
| 2022 | 2023 | 2024 | 2025 | 2026 | ||
| Total cost per year (without Vericiguat) |
1,206,367,113 | 1,295,028,493 | 1,403,997,563 | 1,501,834,793 | 1,589,271,308 | 6,996,499,269 |
| Drug costs (SoC) | 126,356,437 | 142,329,957 | 155,076,185 | 166,034,914 | 175,674,885 | 765,472,377 |
| Hospitalization | 190,648,332 | 113,209,080 | 95,393,778 | 88,823,442 | 85,835,589 | 573,910,222 |
| Routine care & monitoring | 793,041,481 | 932,009,898 | 1,034,691,899 | 1,120,081,818 | 1,194,092,328 | 5,073,917,425 |
| Terminal care | 93,342,218 | 106,788,829 | 118,144,972 | 126,203,892 | 132,977,778 | 577,457,689 |
| Adverse events | 336,854 | 78,114 | 78,114 | 78,114 | 78,114 | 649,311 |
| Urgent HF visits | 2,641,791 | 612,614 | 612,614 | 612,614 | 612,614 | 5,092,245 |
| Total cost per year (with vericiguat) |
1,206,792,996 | 1,298,070,008 | 1,411,184,607 | 1,514,087,340 | 1,607,391,623 | 7,037,526,573 |
| Drug costs (vericiguat + SoC) |
126,899,003 | 145,557,994 | 162,225,357 | 177,670,888 | 192,274,812 | 804,628,054 |
| Hospitalization | 190,558,384 | 113,074,942 | 95,209,797 | 88,586,050 | 85,540,341 | 572,969,513 |
| Routine care & monitoring | 793,053,462 | 932,146,145 | 1,035,272,421 | 1,121,439,655 | 1,196,539,755 | 5,078,451,438 |
| Terminal care | 93,305,341 | 106,602,331 | 117,790,567 | 125,706,414 | 132,354,512 | 575,759,165 |
| Adverse events | 336,598 | 77,817 | 77,520 | 77,223 | 76,926 | 646,084 |
| Urgent HF visits | 2,640,209 | 610,779 | 608,945 | 607,110 | 605,276 | 5,072,319 |
All costs presented in US dollars. Note: Decimal values are not shown; therefore, cumulative values may vary due to rounding. Abbreviations as in Table 1.
The cumulative budget impact was $41,027,304 for the 5-year time horizon, reflecting an estimated increase of 0.6% over the 5 years (Figure 2). Budget impact was driven by higher annual drug costs, and routine care and monitoring costs as vericiguat captured a larger market share year-over-year, but these costs were offset by decreasing costs for hospitalizations, terminal care, and urgent HF visits (Figure 3). According to the base case scenario, the introduction of vericiguat with SoC would lead to a reduction of 11.8 HF hospitalizations and 4.5 CV deaths in year 1, and a total of 123.3 HF hospitalizations and 796.2 CV deaths over the 5-year horizon compared to SoC alone.
Budget impact for the 5-year time horizon. Total cost in each year during the 5-year time horizon (2022–2026) and its cumulative cost for the 2 scenarios. Treatment scenario with vertiguat and standard of care (SoC) (red: scenario 2) is slightly higher than treatment without vertiguat (green: scenario 1). The difference between scenarios (i.e., budget impact) increased every year (blue).
Budget impacts of the cost items in each year during 2022–2026 are shown. Right-most bar represents the cumulative cost of the study period. The budget impacts for “drug costs” and “routine care and monitoring” showed a steady increase over time, but “hospitalization”, “terminal care”, “urgent heart failure (HF) visits” and “adverse events” decreased.
Sensitivity and Scenario Analyses
In the deterministic sensitivity analysis for assessing the uncertainty of the model inputs and assumptions, variation in hospitalization frequency appeared to have the largest effect on the budget impact results (Figure 4). For example, the tornado diagram analysis showed that if the hospitalization rate per year were to increase up to the upper bound values for patients treated with SoC, the total budget impact would decrease. For year 1, an increase in SoC hospitalization rates to the upper bound level would lead to a reduction in budget impact by 10.0%. In contrast, if the annual hospitalization rate for patients on vericiguat with a backdrop of SoC were to increase to the upper bound values, budget impact would increase by 8.8%. Among the parameters for which its variation showed the most effect on results, the total estimated budget impact remained between $36,912,652 and $44,416,315. When population model input values reflected 10% higher incident HF than the base case, the total budget impact increased by 5.2% (Supplementary Table 4). Altering the number of prevalent HF cases by 10% appeared to affect the total budget impact only minimally. The evaluation of lower and higher vericiguat market share scenarios compared to the base case showed the total budget impact to be $20,726,594 and $61,328,014, respectively, over the 5-year horizon (Supplementary Figures 2,3).
Deterministic sensitivity analysis of input parameters on budget impact shown as a tornado diagram. Red bars represent the upper bound and blue represent the lower bound of the total healthcare costs when the parameter ranges were changed in the budget impact model. Among the 15 conditions tested, the hospitalization rate per year had the largest impact. HF, heart failure; SoC, standard of care.
The approval of vericiguat after the success of the VICTORIA trial has offered the opportunity for improved clinical management of patients with HFrEF following a recent worsening event. Introducing a treatment into the market brings with it associated costs, but the overall budget may also be impacted by differences in the downstream healthcare burden related to the novel treatment, particularly for critical diseases such as CHF. Results of our analysis showed an increased overall budget impact primarily driven by direct drug costs and increased resources needed to accommodate routine care and monitoring of an increasing survivorship population. However, because vericiguat has demonstrated potential to reduce the frequency and severity of HF exacerbations,21 the analysis showed reductions in costs associated with hospital admissions, terminal care, and urgent HF visits. Recent real-world evidence from Japan also suggests that optimizing GDMT during hospitalization for worsening HF is associated with significantly improved prognosis, including reductions in readmission and all-cause death.22 This pattern of re-allocation of resources within the healthcare system is often a reflection of a novel treatment that is associated with improved long-term clinical course and reduced deaths. The budget impact initially showed a cost savings in 2022 for medical care costs such as hospitalizations, but with improved survival probabilities, more overall routine care and monitoring costs would be needed over the subsequent years.
Expanding the rate of vericiguat use in the targeted market to up to 12% (vs. 8% base case) by the fifth year could increase the total budget impact by about 33%, but this is expected to also proportionally reduce the number of HF hospitalizations and CV deaths, as also reported in a previous study.16 Among the parameters in which the model appeared to be most sensitive, underestimates for hospitalization rates in the SoC scenario and overestimates of the hospitalization rates for SoC with vericiguat as an add-on would result in higher budget impact estimates.
This is the first study to examine the budget impact of introducing vericiguat into the Japanese population for treating patients experiencing HFrEF with a recent worsening event. There was an increased overall economic burden, but there will be a need to assess this within the context of associated long-term clinical and economic benefits in order to support informed healthcare decision-making. A recent study with a cost-effective analysis conducted within the US healthcare setting showed that vericiguat as an add-on to SoC was estimated to increase quality-adjusted life years (QALY) and was cost-effective at a willingness-to-pay threshold of $100,000 per QALY gained over a 30-year lifetime horizon.18 Those results were based on clinical parameters derived from the VICTORIA trial, in which it was also estimated that vericiguat + SoC would result in 19 fewer HF hospitalizations and 13 fewer CV deaths per 1,000 patients. Future cost-effectiveness analyses adapted to the Japanese population is an important next step to further support implications for medical fee reimbursement and in fully adopting vericiguat into the healthcare system.
In Japan, major drivers of total costs of HF are exacerbated by the increased aging of the population and the reportedly poor prognosis associated with the elderly.23,24 HF is a leading cause of hospitalization, with rates estimated to be about 129 per 100,000 person-years,24 and the median length of hospital stay was about 18 days according to a Japanese study; about 37.4% of patients had HFrEF.25 Exercise capacity in the context of a healthy lifestyle is often difficult due chronic symptoms making worsening events more likely, with associated increases in medical procedures, treatments, and ICU admissions that require significant medical expenditure.26,27 The results of this BIA showed increases in costs associated with the distribution of vericiguat itself, but clearly showed the potential for these costs to be partially offset by reducing costs related to long-term clinical care.
Study LimitationsAlthough we took a rigorous approach to determining model input values reflective of real-world Japanese circumstances, available inputs for clinical parameters were based on results of the VICTORIA trial population, which took place within a control setting outside of Japan. Model input decisions are inherent challenges to most modeling analyses. However, we took a rigorous approach to identifying the most up-to-date and detailed input values by conducting a systematic literature review, analyzing data from a medical claims database, accessing national statistics on population demographic and population-based estimates of disease incidence and prevalence, and consulting clinical and health economics experts. The results of the model depend on the assumptions for annual market share of vericiguat in Japan, but we presented results for 2 additional market share projections reflecting lower and higher scenarios compared to the base case. Nevertheless, the results may not be generalizable to populations with different market share rates. Importantly, at the time of the VICTORIA trial, SGLT2 inhibitors were not widely adopted in clinical practice for HFrEF in Japan, and their cost-effectiveness in combination with vericiguat was not part of this analysis. Finally, the current results are based on a model that did not account for productivity loss such as presenteeism and absenteeism nor any variance in some cost parameters without additional intervention, which may have added to the economic burden associated with introducing vericiguat into the population. It will be of interest to consider these in future updated BIAs with inputs fully derived from Japan-specific contexts, as well as reflecting real-world practices and market share projections related to vericiguat.
Total healthcare costs after introducing vericiguat into the Japanese setting were estimated to increase <1% over % years compared to the SoC scenario. Decreasing costs associated with hospitalizations, terminal care, and urgent HF visits would offset the increasing budget dedicated to drugs and routine care and monitoring costs as vericiguat captured a larger market share year-over-year. The findings of this analysis provide valuable insights into the potential benefits and challenges associated with introducing vericiguat into the Japanese healthcare system.
Clinical Competencies The study results underscore the importance of incorporating vericiguat into treatment regimens for HFrEF patients post-worsening event, highlighting its minimal budgetary impact and potential to reduce hospitalizations. This knowledge enables clinicians to enhance their competency in patient care by making informed decisions that consider both clinical efficacy and economic sustainability. It encourages a continuous commitment to education on emerging therapies within the HF treatment landscape.
Translational Outlook Our findings identified the need for further investigation into the long-term cost-effectiveness and patient outcomes associated with vericiguat in real-world settings. The study highlighted the importance of addressing barriers to widespread adoption, including clinician awareness and healthcare system integration. Future research should focus on comparative effectiveness studies and the exploration of vericiguat’s role within broader HF management strategies.
We thank the Real World Evidence team, Syneos Health Japan K.K. for technical assistance in study design, analysis and medical writing.
This work was support by funding from Bayer Yakuhin, Ltd.
K.K. received consulting fees and lecture fees from Bayer. A.I. received consulting fees from Bayer. T.T. and Y.N. are employees of Bayer (or were at the time of the study). R.M. and Y.W.S. are employees of Syneos Health. K.K. is a member of Circulation Reports’ Editorial Team.
Public Health Research Foundation granted an exemption from requiring ethics approval.
T.T. and Y.N. conceived and designed the study; T.T., Y.N., A.I., K.K. and R.M. were involved in data collection; T.T., Y.N., K.K., R.M. and Y.W.S. conducted the analysis; T.T., Y.N., K.K., R.M. and Y.W.S. drafted the first version of the manuscript. All authors critically reviewed and edited the manuscript for intellectual content and gave final approval of the final version.
Please find supplementary file(s);
https://doi.org/10.1253/circrep.CR-25-0123
