Cost-utility of Sunitinib Versus Pazopanib in Metastatic Renal Cell Carcinoma in Canada using Real-world Evidence

The Cost Effectiveness of Genomic Medicine in Cancer Control: A Systematic Literature Review

BACKGROUND AND OBJECTIVE

Genomic medicine offers an unprecedented opportunity to improve cancer outcomes through prevention, early detection and precision therapy. Health policy makers worldwide are developing strategies to embed genomic medicine in routine cancer care. Successful translation of genomic medicine, however, remains slow. This systematic review aims to identify and synthesise published evidence on the cost effectiveness of genomic medicine in cancer control. The insights could support efforts to accelerate access to cost-effective applications of human genomics.

METHODS

The study protocol was registered with PROSPERO (CRD42024480842), and the review was conducted in line with Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) Guidelines. The search was run in four databases: MEDLINE, Embase, CINAHL and EconLit. Full economic evaluations of genomic technologies at any stage of cancer care, and published after 2018 and in English, were included for data extraction.

RESULTS

The review identified 137 articles that met the inclusion criteria. Most economic evaluations focused on the prevention and early detection stage (n = 44; 32%), the treatment stage (n = 36; 26%), and managing relapsed, refractory or progressive disease (n = 51, 37%). Convergent cost-effectiveness evidence was identified for the prevention and early detection of breast and ovarian cancer, and for colorectal and endometrial cancers. For cancer treatment, the use of genomic testing for guiding therapy was highly likely to be cost effective for breast and blood cancers. Studies reported that genomic medicine was cost effective for advanced and metastatic non-small cell lung cancer. There was insufficient or mixed evidence regarding the cost effectiveness of genomic medicine in the management of other cancers.

CONCLUSIONS

This review mapped out the cost-effectiveness evidence of genomic medicine across the cancer care continuum. Gaps in the literature mean that potentially cost-effective uses of genomic medicine in cancer control, for example rare cancers or cancers of unknown primary, may be being overlooked. Evidence on the value of information and budget impact are critical, and advancements in methods to include distributional effects, system capacity and consumer preferences will be valuable. Expanding the current cost-effectiveness evidence base is essential to enable the sustainable and equitable translation of genomic medicine.

Scoping Review of Economic Analyses of Rare Kidney Diseases

Introduction

Rare kidney diseases (RKDs) place a substantial economic burden on patients and health systems, the extent of which is unknown and may be systematically underestimated by health economic techniques. We aimed to investigate the economic burden and cost-effectiveness evidence base for RKDs.

Methods

We conducted a systematic scoping review to identify economic evaluations, health technology assessments, and cost-of-illness studies relating to RKDs, published since 2012.

Results

A total of 161 published studies, including 66 cost-of-illness studies and 95 economic evaluations; 72 grey literature reports were also included. Most published literature originated from high-income nations, particularly the USA (81 studies), and focused on a handful of diseases, notably renal cell carcinomas (70) and systemic lupus erythematosus (36). Limited evidence was identified from lower-income settings and there were few studies of genetic conditions, which make up most RKDs. Some studies demonstrated the cost-effectiveness of existing treatments; however, there were limited considerations of broader economic impacts on patients that may be important to those with RKDs. Included health technology assessments highlighted difficulties in obtaining high-quality clinical evidence for treatments in very small patient populations, and often considered equity issues and other patient impacts qualitatively alongside clinical and economic evidence in their recommendations.

Conclusion

We found large gaps in the economic evidence base for RKDs and limited adaptation of methods to account for the uniqueness of these diseases. There may be significant scope for innovation in building an investment case for RKD treatments, as well as in decision-making processes to inform investment decisions.

Real-World Cost-Effectiveness Analysis: How Much Uncertainty Is in the Results?

Cost-effectiveness analyses of new cancer treatments in real-world settings (e.g., post-clinical trials) inform healthcare decision makers about their healthcare investments for patient populations. The results of these analyses are often, though not always, presented with statistical uncertainty. This paper identifies five ways to characterize statistical uncertainty: (1) a 95% confidence interval (CI) for the incremental cost-effectiveness ratio (ICER); (2) a 95% CI for the incremental net benefit (INB); (3) an INB by willingness-to-pay (WTP) plot; (4) a cost-effectiveness acceptability curve (CEAC); and (5) a cost-effectiveness scatterplot. It also explores their usage in 22 articles previously identified by a rapid review of real-world cost effectiveness of novel cancer treatments. Seventy-seven percent of these articles presented uncertainty results. The majority those papers (59%) used administrative data to inform their analyses while the remaining were conducted using models. Cost-effectiveness scatterplots were the most commonly used method (34.3%), with 40% indicating high levels of statistical uncertainty, suggesting the possibility of a qualitatively different result from the estimate given. Understanding the necessity for and the meaning of uncertainty in real-world cost-effectiveness analysis will strengthen knowledge translation efforts to improve patient outcomes in an efficient manner.

Avelumab Maintenance Treatment After First-line Chemotherapy in Advanced Urothelial Carcinoma-A Cost-Effectiveness Analysis

BACKGROUND

Recently, a clinical trial (NCT02603432) showed that avelumab maintenance treatment, post first-line chemotherapy, can significantly prolong the overall survival of patients with advanced urothelial carcinoma (UC), however, the treatment was very expensive. This study aimed to determine the cost-effectiveness of avelumab maintenance therapy in advanced or metastatic UC from the US taxpayer perspective.

METHODS

Based on the data of the JAVELIN Bladder 100 clinical trial (NCT02603432), a Markov multi-state model was constructed to investigate the costs and clinical outcomes of avelumab maintenance after platinum-based chemotherapy versus best supportive care (BSC) for advanced or metastatic UC. Parameters of the model came from the 2020 Average Sales Price Drug Pricing Files and published literature. The main outputs were costs, life years (LYs), quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER). Robustness was tested by deterministic and probabilistic sensitivity analyses. The analysis was stratified to include both the overall population and a subset of programmed death-ligand 1 (PD-L1)-positive patients.

RESULTS

Avelumab maintenance therapy was estimated to generate an additional 0.26 QALYs (1.46 vs. 1.20 QALYs) and costs $183,271 ($278,323 vs. $95,052) more compared to BSC alone in the overall population, yielding an ICER of $699,065/QALY. For the PD-L1-positive population, avelumab produced a 0.42 increase in QALYs (1.74 vs. 1.32 QALYs) and raised costs to $223,238 ($320,355 vs. $97,117), resulting in an ICER of $521,850/QALY for this population. Both ICERs were above the willingness-to-pay (WTP) threshold of $200,000/QALY. Sensitivity analyses manifested that the model was robust.

CONCLUSION

From the perspective of the US taxpayer, avelumab maintenance therapy is considered cost-ineffective for patients with advanced or metastatic UC at a WTP threshold of $200,000/QALY in the overall population as well as in PD-L1-positive population.

Rapid Review of Real-World Cost-Effectiveness Analyses of Cancer Interventions in Canada

Cost-effectiveness analysis (CE Analysis) provides evidence about the incremental gains in patient outcomes costs from new treatments and interventions in cancer care. The utilization of "real-world" data allows these analyses to better reflect differences in costs and effects for actual patient populations with comorbidities and a range of ages as opposed to randomized controlled trials, which use a restricted population. This rapid review was done through PubMed and Google Scholar in July 2022. Relevant articles were summarized and data extracted to summarize changes in costs (in 2022 CAD) and effectiveness in cancer care once funded by the Canadian government payer system. We conducted statistical analyses to examine the differences between means and medians of costs, effects, and incremental cost effectiveness ratios (ICERs). Twenty-two studies were selected for review. Of those, the majority performed a CE Analysis on cancer drugs. Real-world cancer drug studies had significantly higher costs and effects than non-drug therapies. Studies that utilized a model to project longer time-horizons saw significantly smaller ICER values for the treatments they examined. Further, differences in drug costs increased over time. This review highlights the importance of performing real-world CE Analysis on cancer treatments to better understand their costs and impacts on a general patient population.

Pazopanib or Sunitinib? cost-utility analysis of pazopanib versus sunitinib in the first-line treatment of metastatic renal cell carcinoma in Jordan

Objectives

To evaluate the cost-effectiveness of pazopanib for the treatment of metastatic renal cell carcinoma (mRCC) in the first-line settings from a payer perspective.

Methods

A state-transition model with three health states was developed to estimate the incremental cost per quality-adjusted life years (QALY) gained for pazopanib compared to sunitinib. A lifelong time horizon was adopted in the base-case analysis. The transition probabilities were estimated based on the COMPRAZ trial, utility weights were taken from literature, and costs were based on estimating medical resource utilization data at King Hussein Cancer Centre (KHCC), deriving unit cost inputs from KHCC databases and the Jordan Food and Drug Administration website. Both costs and outcomes were discounted using 3% rate. The model’s uncertainty was tested using a probabilistic and deterministic sensitivity analyses.

Key findings

The base-case results showed that pazopanib was dominant when using the listed price for both medications. Pazopanib was associated with an incremental saving of −$10 721.55 and an incremental QALY of 0.08. The results were sensitive to utility values and the progression health state cost. The probabilistic sensitivity analysis showed that the probability of pazopanib being cost-effective compared to sunitinib is around 60–70% at KHCC cost-effectiveness threshold values. However, the result was reversed when the price of sunitinib was reduced by 40% making sunitinib the dominant strategy.

Conclusions

Pazopanib is a potential cost-effective option in the first-line settings for mRCC when the listed price of sunitinib is used. Therefore, price negotiations are recommended before final listing decisions to get the most cost-saving treatment.

Economic evaluation of sunitinib versus pazopanib and best supportive care for the treatment of metastatic renal cell carcinoma in Chile: cost-effectiveness analysis and a mixed treatment comparison

Background: Sunitinib and Pazopanib are two metastatic renal cell carcinoma (MRCC) treatment alternatives, however the health system in Chile does not consider coverage for any. The cost-effectiveness versus relevant comparator was assessed to support evidence-based decision making. Methods: A four health states Markov model was built: first, second line treatments, BSC and death. Benefits were measured in QALYs, and efficacy estimates were obtained from an indirect treatment comparison. A 10-year time horizon and a 3% undifferentiated discount rate were considered. Deterministic and probabilistic sensitivity analyses were performed. Results: The costs of treating MRCC with Sunitinib were higher than Pazopanib and BSC. When comparing Sunitinib versus Pazopanib, the incremental benefit is small favoring Sunitinib (0.03 QALYs). The base case scenario shows an average ICER of PA versus BSC of US$62,327.11/QALY and of US$85,885/QALY for Sunitinib versus Pazopanib. The ICER was most sensitive to the OS relative to BSC, where evidence was associated to important bias. Conclusions: Sunitinib or Pazopanib can be considered cost-effective if a 3 GDP per-capita threshold is assumed. The decision between SU or PA is highly sensitive to the price of the drugs, rather than the outcomes. Therefore, the decision might be made based on cost-minimization exercise.