Budget impact analysis of first-line treatment with pazopanib for advanced renal cell carcinoma in Spain

Renal cell carcinoma (RCC) is the most common kidney cancer [1] and accounts for approximately 3% of all cancers in males and 2% in females [2]. Advanced RCC has traditionally been a difficult to treat disease due to its inherent resistance to cytotoxic therapy, radiation or hormone therapy [3]. Prior to the advent of angiogenesis inhibitors, interferon alfa (INF-α) and interleukin-2 (IL-2) were the main therapies used for the treatment of advanced RCC, despite the significant toxicity and limited efficacy associated with their use [4, 5].

Advances in the understanding of the molecular pathways of the tumor biology have enabled the identification of specific molecular targets for therapy, including the vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF) and mammalian target of rapamycin (mTOR), what has led to the development of several drugs (sorafenib [6], sunitinib [7], bevacizumab (plus IFN-α) [8, 9], temsirolimus [10] and everolimus [11]) that have substantially improved outcomes for RCC patients [12]. Pazopanib, a novel tirosinkinase inhibitor that targets VEGF, PDGF and stem cell factor receptor (c-Kit), is the latest drug approved for first line treatment of advanced RCC [13]. Pazopanib, sunitinib and bevacizumab (plus IFN-α) are recommended in the clinical guidelines for first-line treatment of advanced RCC in patients with favorable and intermediate risk [14‐16].

COMPARZ (COMParing the efficacy, sAfety and toleRability of paZopanib vs. sunitinib) phase III clinical trial has evaluated the efficacy and safety of pazopanib compared to sunitinib in subjects with advanced RCC who had received no prior systemic therapy for advanced RCC. Pazopanib demonstrated non-inferiority to sunitinib in terms of median progression-free survival (PFS): 8.4 (95% CI: 8.3; 10.9) and 9.5 (95% CI: 8.3; 11.1) months, respectively (HR = 1.05 (95% CI: 0.90; 1.22 < 1.25)) [17].

Despite the current economic environment in which healthcare resources are scarce, to our knowledge, there is no published pharmacoeconomic evidence guiding the choice of one therapy over another as first-line therapy for advanced RCC in the Spanish setting. We aimed to develop a population-based model that describes the natural history of RCC and predicts the number of future cases of advanced RCC, so that it can be used in healthcare decision-making. We further aimed to use this model to analyze the budget impact (i.e. the financial consequence of adopting a new healthcare intervention [18]) associated with the introduction of pazopanib, compared to the current standard of care in Spain (i.e. sunitinib), in first-line treatment of advanced RCC under the Spanish National Healthcare System (NHS) perspective.

Adult RCC prevalence predicted by the model is as follows: 7.5/100,000 (1-year); 20.7/100,000 (3-year) and 32.5/100,000 (5-year). As can be seen in Figure 2, the model accurately matches GLOBOCAN reported prevalence figures for RCC (90% of kidney cancer prevalence [24]): 7.6/100,000, 20.2/100.000 and 31.1/100,000, respectively. These results validate the model externally in terms of its structure and the parameters chosen. The model predicts a total of 1,591 advanced RCC patients with favorable or intermediate risk in Spain in 2013. This figure is the result of the sum of the incident patients diagnosed with advanced disease within a year and those patients who relapse after surgery for the treatment of localized disease.

Pharmacological costs per cycle for pazopanib and sunitinib were €4,046 and €4,904, respectively (Table 2). Annual (8 cycles) per patient pharmacological costs were 32,365€ and 39,232€, respectively. Costs associated with the management of AE were €662 and €974, respectively (Table 3). The overall annual per patient cost for pazopanib was €7,179 (18%) lower compared to sunitinib. The budget impact resulting from the introduction of pazopanib as a function of the percentage of patients treated is depicted in Figure 3. In 2013, a point increase in the percentage of patients treated with pazopanib compared to sunitinib would prevent the NHS from incurring an overall annual amount of €67,236. In the most efficient scenario, where all the 1,591 advanced RCC patients predicted by the model receive pazopanib, we estimate potential annual savings for the NHS of €6,723,622. Results for 2014 and 2015 are also presented in Table 2.

The univariate sensitivity analysis confirmed the robustness of the model. Among the model parameters, kidney cancer incidence, the proportion of advanced RCC patients with favorable or intermediate risk, the percentage of advanced RCC at diagnosis and RCC incidence were the most relevant. The incremental cost remained negative for any scenario considered, meaning that the introduction of pazopanib results in savings for the NHS (Figure 4).

Healthcare expenditure has drawn the attention of payers as well as of clinicians involved in oncologic care due to both the increased pressure on healthcare budgets as a consequence of the current economic environment and the relentless increase in healthcare spending as a portion of countries’ Gross Domestic Product over the past decades [30]. Anti-VEGF therapies for RCC are not an exemption and are subject to scrutiny from healthcare budget holders, pharmacists and oncologists alike. In this context, we sought to develop a model that describes the natural history of RCC, so that it can be applied to healthcare decision-making. To our knowledge, there are no published estimates of the future number of cases of advanced RCC in our country. We thus developed a time-dependent population-based Markov model to predict the future cases of advanced RCC and used this model to examine the budget impact associated with the introduction of pazopanib, compared to sunitinib, in the treatment of first-line advanced RCC patients with favorable or intermediate risk.

In order to effectively capture all the relevant costs and consequences, guidelines recommend BIA populations to be open [18, 31], in the sense that individuals can enter or leave the population pool depending on whether they meet the criteria for inclusion (i.e. diagnosis of advanced RCC). This is in contrast with most Markov models in which populations are closed, with hypothetical patient cohorts being followed throughout a defined time horizon. Following a more realistic approach, we capture the changes in the advanced RCC population by means of a time-dependent population-based Markov model, based on the incidence of advanced RCC at diagnosis and on the likelihood of disease recurrence after surgery for localized disease. Patients leave the model when they experience progression during first-line therapy for advanced disease. Markov models have been used in other disease areas as well for this purpose [32].

The model accurately matches GLOBOCAN reported prevalence figures for RCC in Spain, providing evidence that it is able to reproduce the natural history of the disease and that it is therefore a reliable tool for estimating the future prevalence of advanced RCC based on RCC incidence. Moreover, the model results are robust as demonstrated by the sensitivity analysis performed. Even though this model includes Spanish-specific parameters (e.g. incidence rates and baseline populations), disease-specific parameters, such as the percentage of patients with advanced disease at diagnosis and the time-dependent probabilities of recurrence, have been obtained from the best available sources in the literature and are not country-specific. This model can be therefore easily transferred to other settings by simply replacing Spanish population estimates (publicly available from national statistics) and renal cancer incidence figures (publicly available from GLOBOCAN [22]) by country-specific data.

In our study, pazopanib results in considerable savings for the Spanish NHS, as a consequence of both reduced pharmacological costs and lower costs associated with the management of AE. Based on COMPARZ results, there are some AE that occur with a higher frequency with sunitinib (e.g. thrombocytopenia, anemia and neutropenia), while others seem to be more frequent with pazopanib (e.g. liver enzyme elevation) [17]. We thus included the costs associated with the management of AE for both drugs in order to account for such differences. Despite being very relevant for RCC patients [33], fatigue and hand-foot syndrome are not associated with a great increase in healthcare resource use or costly concomitant medications. They thus had a limited contribution to the difference in overall therapy costs in our analysis.

We developed a time-dependent population-based Markov model that can be used to estimate the future number of cases of advanced RCC. We used it to undertake the BIA resulting from the introduction of pazopanib compared to sunitinib in the treatment of first-line advanced RCC under the Spanish NHS perspective. The introduction of pazopanib is cost-saving for the Spanish NHS, as a consequence of both reduced pharmacological costs and lower costs associated with the management of AE.