As is the case with so many other aspects of economic (or non-economic) activity, in the health sector cost-effectiveness analysis is the prevailing decision-making approach. Indeed, the cost-effectiveness plane has been established as a prerequisite in economic evaluations and unequivocally, its four quadrants provide an efficient means for conveying findings.
On this plane, the X-axis represents costs, while the Y-axis represents outcomes. Also, one can safely say that among the quadrants, the Southeast (SE) and the Northwest (NW) are straightforwardCitation1. The former means the new product dominates (better and cheaper), while the latter implies that the new product is dominated (worse and more expensive).
Nevertheless, the interpretation of the remaining two, namely the Southwest (SW) and the Northeast (NE) are intricate, and it is contingent on another crucial metric: the willingness-to-pay (WTP) threshold. The WTP defines, in monetary terms, what a society is willing to invest in order to gain one quality-adjusted life year (QALY) for one beneficiary. And while this definition conflicts with the fundamental priceless attribute of health, health is priceless for everybody, thus for health expenditures to be able to safeguard the whole of the beneficiary pool, an upper limit must be introduced, which is set based on rational assumptions.
While the majority of healthcare economists and policy makers endorses the concept of WTP, the value at which it is set is plagued by considerable ambiguity and inconsistency. This is spanned either through approximate or definite thresholds, which vary across countries, even with similar financial characteristics. WTP is formed by an array of variables, which include cohesiveness, maturity of the society, and of course, the general economic status of the countryCitation2. It is worth mentioning that in its advent, its range was germane to the annual costs of dialysis patients in the United States.
Studies demonstrating the incremental cost-effectiveness ratio (ICER) exceeding the defined WTP thresholds abound in the literature. Their premise is simple: “the product is effective but the costs are excessive and we could have fared better if the resources were allocated in a more rational manner, elsewhere in the system”. Usually, the remedy is the introduction of a discount or other managed entry agreement, which is aimed at effectively constraining costs towards decreasing ICER.
One of the biggest challenges in the interpretation of the ICER plane stems out of the SW quadrant. Usually, the WTP is extended from the NE to the SW as well. What is thus SW implying is utility is lost, in tandem with bearing fewer costs. Notably, the SW has been consistently neglected since it is primarily anticipated that better and more expensive products will emerge, as these are expected to move from their current position in the NE quadrant. Therefore, NE has been in the spotlight and has been the focus of a large and growing body of literature.
An intriguing part of the WTP is the noted asymmetry between the WTP and the willingness-to-accept (WTA). What we know was largely proposed by O’ Brien, who was the first to draw attention to the disparities between the WTP in order to gain one QALY, and the WTA in order to lose one QALYCitation3–4.
This asymmetry is caused by the Measurement Artifact, Substitute Commodities, and the Endowment Effect. The Measurement Artifact assumes that all conditional valuation studies may contain measurement bias. An integral part of WTA studies is the assumption that people already own the commodity under evaluation, even if there are only slim chances that they will ever own such a commodity (health gain). Moreover, it is also not clear who is going to bear the cost, this being another reason which may push the WTA amount higher.
Also, health has virtually non-comparable substitute commodities, a notion, which impedes the assignment of a monetary value to the loss of an otherwise measurable unit of health.
The foundation of the Endowment Effect is the Loss Aversion and Framing Effect. The Framing Effect, which has been extensively studied in psychology, suggests that people are heavily influenced by the presented positive or negative connotations of a hypothesis, and not the actual gain or loss. As a result, they assign more weight to a negative fact connotation. Based on this notion, in our case, the foregone utility has a greater impact than the gained utility i.e. in absolute terms, it assumes that the loss of a utility is greater than the gained utility.
All of the aforementioned explain why the WTA has a higher threshold than the WTP.
In the Journal of Medical Economics, Xin Guan et al. reported on the cost-effectiveness of Fruquintinib versus Regorafenib as the third-line therapy for metastatic colorectal cancer in ChinaCitation5. Metastatic colorectal cancer is associated with poor survival; therefore, an unmet medical need exists, regarding effective and safer products. As is the case with the majority of new products, no direct comparative studies exist between competing products, a fact that further accentuates the level of uncertainty. In their study, the authors created a Markov Model and extracted data from two studies. They suggested that Fruquintinib was inferior to Regorafenib, but at the same time cheaper. Therefore, they postulated that Regorafenib is not cost-effective in comparison to Fruquintinib.
Nevertheless, authors should build their argument in the context of Fruquintinib and the foregone utility which stems out of its adoption, instead of reimbursing regorafenib. Based on the available data, patients on Fruquintinib lose 0.05 QALY compared to Regorafenib, at 11,454 USD savings. This leads to an estimated WTA of 230,000 per QALY foregone. This is not the same as WTP for a QALY gained since Regorafenib was already in the market when Fruquintinib was launched.
In the range of the reported ICER, which is found to be well above China’s threshold, no differences apply. Nevertheless, if the reported ICER was lower, then the problem could be posed in terms of the pre-defined WTP. If the 0,05 foregone QALY was associated with less than 1,612 USD then the WTP would render Regorafenib as cost-effective, given the fact that Regorafenib entered the market after Fruquintinib. In the care sequence, the WTA should be higher- some authors claim it to be twice as much- as WTP, based on the asymmetryCitation6. Therefore, Fruquintinib should have been rejected since the foregone utility should have been related to a higher WTA threshold. In such a case, the solution would be a lower price of Fruquintinitb, while on the contrary, a lower price of Regorafenib would be necessary, if Regorafenib had been launched after Fruquitninib, all other elements held constant.
The current landscape of the pharmaceutical sector along with the soaring prices, has, in certain cases, reached a steady state in innovation where the new products are non-inferior to established modalities. As a result, some products will fall in the SW quadrant. Moreover, the lack of direct head-to-head trials further exacerbates uncertainty. While we gleaned our data on the NE quadrant, we still need to contemplate the legitimacy of the SW quadrant and improve on its theoretical basis. A stepping stone should be the clear establishment of a WTA threshold. But prior to this, a crucial factor, which should be brought to the forefront, is a deliberation as to whether as a society we can afford to lose utility in any health care sector, let alone in oncology patients.
Transparency
Declaration of funding
There is no funding to declare for this research.
Declaration of financial/other relationships
The author has none to declare.
JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Acknowledgements
None reported.
References
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- Petrou P. Willingness-to-pay threshold: a Japanese perspective. J Med Econ. 2020;23(10):1043–1045.
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- Guan X, Li H, Xiong X, et al. Cost-effectiveness analysis of fruquintinib versus regorafenib as the third-line therapy for metastatic colorectal cancer in China. J Med Econ. 2021;24(1):339–344.
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