RE: Cost-effectiveness of sacubitril/valsartan versus enalapril in patients with heart failure and reduced ejection fraction

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Reply: Cost-effectiveness of sacubitril/valsartan versus enalapril in patients with heart failure and reduced ejection fraction

We read with interest the Liang et al.¹ publication on the cost-effectiveness of sacubitril/valsartan in Singapore. We would like to highlight a similar cost-effectiveness publication for sacubitril/valsartan recently published by McMurray et al.² McMurray et al.² evaluated the cost-effectiveness of sacubitril/valsartan compared with an ACE inhibitor (enalapril) in the treatment of chronic heart failure with reduced ejection fraction (HF-REF) from the perspective of healthcare providers in the UK, Denmark, and Colombia. The analysis suggests that, in all three countries, sacubitril/valsartan is likely to be cost-effective compared to an ACEI in patients with HF-REF. There are several methodological differences between the McMurray et al.² and Liang et al.¹ publications, leading to different conclusions regarding the cost-effectiveness profile of sacubitril/valsartan. We would like to highlight a number of these differences; in particular, the time horizon considered, the price of enalapril, the clinical data, and the health-related quality-of-life values included in the analysis.

In the Liang et al.¹ publication (p. 3) it states “a time horizon of 10 years, based on the average life expectancy of 5 to 10 years for patients with HF”^3,4. Consequently, Liang et al.¹ does not capture the costs and outcomes for the proportion of patients who live beyond 10 years. In comparison, the economic model by McMurray et al.² estimates the costs and benefits over the population’s lifetime (i.e. a lifetime horizon was adopted). The mean lifetime expectancy modeled ranges between 9.27 years (UK in sacubitril/valsartan arm) and 7.34 (Denmark in ACEI arm), which is aligned with the average life expectancy reported for HF patients in Singapore². We believe this approach is consistent with the literature on selecting an appropriate time horizon for economic evaluations. For instance, Drummond et al.⁵ state “In principle, this should be the period over which costs and/or effects of the alternative options being compared might differ” (p. 280). The ISPOR report for best modeling practice mentions:

Common approaches include modeling to an age of 120 years or tracking the cohort until more than 99.9% of the individuals are dead. If the intervention affects mortality, the time horizon should be lifetime to capture (quality adjusted) life-years gained from delayed deaths⁶ (p. 5).

The Drug Evaluation Methods and Process Guide for Singapore states that:

The time horizon for estimating clinical and cost effectiveness should be sufficiently long to reflect all important differences in costs or outcomes between the treatments being compared. A lifetime time horizon is required when alternative treatments lead to differences in survival or benefits that persist for the remainder of a person’s life⁷ (p. 32).

In the Liang et al.¹ publication, a price of SGD 6.00 per month for enalapril is assumed. The ACE Drug Evaluation Methods and Process Guide states “the selling price to patient (before any subsidy or insurance coverage is applied) for treatments based on the registered dose should be used in the reference-case analysis”⁷ (p. 31). The price of SGD 6.00 per month for enalapril more closely reflects the subsidized price and not the selling price (before any subsidy) to the patient. A price range of SGD 6.00–30.00 per month for enalapril should be considered in the analysis, as this is the price before any government subsidy is applied. The price range of SGD 6.00–30.00 per month is based on the average private/unsubsidized price obtained by surveying pharmacies at five public hospitals in Singapore.

The ACE Drug Evaluation Methods and Process Guide states that:

Only direct health-care costs from the perspective of the health-care payer should be included in reference case analyses; this includes payments out of the government’s health-care or insurance budget as well as patients’ co-payments including Medisave and out of pocket expenses⁷ (p. 17, Table 6).

If the analysis is conducted from the perspective of the healthcare payer, then only costs borne by the healthcare payer should be included in the evaluation, and costs such as patient co-payments and out of pocket expenses should be excluded. The price to the healthcare payer for sacubitril/valsartan is SGD 6.00 per day and SGD 4.50–22.50 per month for enalapril (estimated based on a typical 30% mark-up). If only the price to the healthcare payer is considered, this would improve the cost-effectiveness results for sacubitril/valsartan.

In the Liang et al.¹ publication, the “Alive” Health State is further divided by NYHA, classes with utility values assigned by NYHA class. The transition probabilities to move patients between NHYA classes are derived from the SENIORS study, which did not study the treatment effect of sacubitril/valsartan, but instead assessed the benefit of the beta-blocker, nebivolol, in HF-REF and non-HR-REF patients ≥70 years⁸. It is stated in Liang et al.¹ that “conservatively, the probabilities were assumed to be the same for both treatment groups, because it was unclear how sacubitril/valsartan altered the progression between health states relative to enalapril”. In the PARADIGM-HF trial, at 8 months, patients in the sacubitril/valsartan arm had a lower rate of worsening NYHA class compared to enalapril (5.4% vs 7.0%; p = 0.004)⁹. This finding is also applicable to the real world setting, as the treatment with sacubitril/valsartan has been shown to lead to an improvement in NYHA class¹⁰. Applying utility values by NYHA class and assuming the same transition probabilities will under-estimate the benefits of sacubitril/valsartan. In McMurray et al.², the economic model assumes a simpler structure and does not divide the “Alive” health state by NYHA class. Utility values are not applied based on NYHA class, but instead directly model EQ-5D scores from PARADIGM-HF using a mixed effects model.

In the Liang et al.¹ publication, the utility values used are taken from the CARE-HF trial, which collects EQ-5D data in patients with NYHA class III or IV heart failure due to left ventricular systolic dysfunction and cardiac dyssynchrony¹¹. In McMurray et al.², the utility values are taken from the PARADIGM-HF trial. The EQ-5D data in PARADIGM-HF is collected from the population of interest, i.e. patients receiving sacubitril/valsartan or enalapril with NYHA class II, III, or IV, and an ejection fraction of 40% or less. As EQ-5D data is available from the PARADIGM-HF, we believe the utility values used in McMurray et al.² are more appropriate as they have been directly measured in the population of interest. As an example, the NICE guidelines state a preference for the use of EQ-5D collected in the clinical trials:

If not available in the relevant clinical trials, EQ-5D data can be sourced from the literature. When obtained from the literature, the methods of identification of the data should be systematic and transparent. The justification for choosing a particular data set should be clearly explained¹² (p. 48, section 5.3.8).

The Liang et al.¹ publication extrapolates hospitalization rates from published Kaplan-Meier curves using a Weibull model with the treatment effect for sacubitril/valsartan taken from the PARADIGM-HF publication. The published Kaplan-Meier curves present only data on the first hospitalization for heart failure, and do not include the significant reductions in all-cause hospitalizations associated with the use of sacubitril/valsartan¹⁰. In the McMurray et al.² publication, a negative binomial regression model, using patient-level data, estimates the rate of all-cause hospitalizations, including re-hospitalizations. The Liang et al.¹ analysis is, therefore, likely to under-estimate the number of hospitalizations, and the number of hospitalizations avoided.

We have highlighted a number of key differences in the methodology used and the limitations in the assumptions made by Liang et al.¹ compared to McMurray et al.². These differences significantly impact the conclusions regarding the cost-effectiveness profile of sacubitril/valsartan in the treatment of HF-REF. Overall, we believe that the McMurray et al.² approach is more robust and aligned with the usual requirements for the cost-effectiveness appraisal of new healthcare technologies. When the economic model described in Murray et al.² has been adapted to the Singapore setting to explore the cost-effectiveness results of sacubitril/valsartan, using the methodology outlined above, an ICER range of SGD 35,578–38,819 per QALY gained is obtained with a price of SGD 9.00 per day for sacubitril/valsartan and a price range of SGD 6.00–30.00 per month for enalapril. If a price to the healthcare payer of SGD 6.00 per day for sacubitril/valsartan and a price range of SGD 4.50–22.50 per month for enalapril is assumed, the ICER range would be SGD 22,914–25,345, per QALY gained. The World Health Organization’s (WHO’s) Choosing Interventions that are Cost-Effective (CHOICE) program defines interventions for which the cost per QALY is less than one GDP per capita as very cost-effective, between one and three times GDP per capita as cost-effective and over three times GDP per capita as not cost-effective¹³. As the ICER range in both scenarios falls below GDP per capita of Singapore, which ∼ SGD 79,000–80,000, sacubitril/valsartan can be considered cost-effective in Singapore. The ICER from the Liang et al.¹ publication can also be considered cost-effective when assuming the WHO cost-effective threshold of between one and three times GDP per capita.

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Declaration of funding

There is no funding to report.

Declaration of financial/other relationships

JC, IT, CN, JT, and DL are employees of Novartis. DT is a director at SourceHEOR, which has provided HEOR consultancy to Novartis.