Section:
Policy proposals addressing the high cost of treating cancer are among the most persistently controversial topics in oncology. The rising national economic burden of cancer in an aging population, combined with skyrocketing costs for cancer diagnostics, therapies, and hospital-based care, all strain patient, family, and health system budgets.1 Few would disagree with the sentiment that controlling the rate of spending growth is fundamental and essential for societies wishing to improve access and reduce inequity in cancer care.
THE TAKEAWAY
-
In the article that accompanies this editorial, Wheeler et al13 used a microsimulation model to demonstrate similar outcomes regardless of therapy sequencing in patients with endocrine-refractory or triple-negative breast cancer, meaning therapeutic decisions in this setting may prioritize costs without affecting clinical outcomes. This manuscript exemplifies the type of high-quality, transparent, and accessible economic analysis that has a direct impact on patient care and is of interest to JCO and JCO OP.
Economic analysis, specifically cost-utility analysis (CUA), is one technique that can be used to bend the cost curve in oncology. CUA has well-established scientific foundations and is used widely around the world for resource allocation decisions. Outside of the United States, CUA is used with little controversy to support drug price negotiations, to inform practice guidelines and pathways, and in some cases to restrict access to low-value therapies. In all countries, CUA has helped the cancer community understand the relative value of prevention, screening diagnostic, and treatment technologies in cancer.
What works well elsewhere, however, has not been successful in the United States, particularly for cancer therapies. Experts have identified several headwinds against using CUA for decision making in the United States. Examples include lack of a centralized health care funding authority that is empowered to make decisions on the basis of CUA results; convoluted, nontransparent pricing, and reimbursement processes obscure the true price of treatments; and laws that place US Food and Drug Administration–approved oncology drugs in a protected class out of reach from Medicare and Medicaid, forcing coverage regardless of the therapeutic benefit relative to alternative therapies. Compounding these effects is an oncology care delivery system whose revenue is dependent on drug margins—reducing or sometimes inverting price sensitivity. Furthermore, historically, American culture has viewed considerations of cost as inappropriate for medical decision making, a notion embraced by many but not all physicians.2–5 Widespread direct-to-consumer marketing of oncology drugs and other medical technologies creates a strong (but poorly informed) demand by patients that puts enormous pressure on the oncology community to prescribe newer and more costly products. Because of these issues and others, CUA faces significant system-based barriers that prevent it from being effectively used to make insurance coverage and reimbursement decisions for oncology therapies in the United States.
The community that produces economic analyses has not always helped its cause. Many CUA manuscripts include nontransparent simulation models that use complex methods unfamiliar to many clinicians, synthesize large amounts of disparate data, some of questionable provenance or quality, and yet present the results and implications with a high degree of certainty. We are not surprised that many clinicians do not fully trust these papers or always accept their conclusions.
Because of (rather than in spite of) these issues, we believe that clinicians should play a role in addressing the cost crisis in oncology. The decisions made by oncologists are a primary force influencing the spending curve in cancer care. Oncology practices, providers, and their patients are in the best position to weigh costs and benefits of treatment choices and are among the most affected financially by those decisions. As journal editors, the question that we pose is as follows: How can the journals assist practice in this area?
Both Journal of Clinical Oncology (JCO) and JCO Oncology Practice (JCO OP) publish manuscripts on health services research and care delivery topics. JCO OP prioritizes papers that inform resource optimization related to the delivery of care rather than simply contrasting outcomes of one therapeutic approach over another. JCO OP hopes to attract more research papers that provide such critical analysis on the many elements of oncology care delivery. All content dealing with understanding the provision of care—the mechanics of practice, care delivery, quality improvement, value, and equity—is the purview of JCO OP. JCO and JCO OP can inform readers with high-quality studies assessing the economic value of new therapies, show comparative benefits, risks, and costs across classes of interventions for a given indication.
One of the most important features of CUA that is known to health economists but often missed by clinicians is that CUA can highlight uncertainties in the evidence chain that stems from indication to management to outcomes. Often, the factors that drive the value (or lack thereof) of a new intervention are highly uncertain, particularly in situations where, for example, a drug or device is approved without high-quality evidence (eg, randomized controlled trials) and has limited or no data on survival or long-term outcomes. Weak or incomplete evidence is a concern for a substantial proportion of oncology drugs, particularly those approved using accelerated approval.6–8
JCO and JCO OP receive a substantial volume of manuscripts presenting economic evaluations. How should the journals make decisions about what to publish? The majority of public and private health insurers do not formally consider cost-effectiveness in their evidence reviews, and our current system provides ample opportunity for drug manufacturers to charge any price they wish with little pushback from the oncology community. Many physicians do not know the transaction price of the products they prescribe and have even more difficulty calculating the downstream economic benefits and costs of treatment. Even when they do, physicians are often reluctant to allow costs to influence decisions made for an individual patient, sometimes on the basis of ethical concerns9 and oftentimes assuming that the costs for that treatment will somehow be covered, one way or another.
How can journals potentially bridge this gap and inform clinicians, payers, and (perhaps equally important) the public? Journals can and should address this information gap for the oncology community. To address this issue effectively, however, requires attention to two fundamental issues that JCO and JCO OP prioritize, one is high-quality science and another is the ability to inform decision making by the various groups above. Here are some considerations that we recommend authors consider when preparing a manuscript on economic analyses of cancer technologies for possible submission to JCO or JCO OP.
-
Methodological rigor: Lack of adherence to methodological standards has been a long-standing problem for CUA. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) address several of the problems for readers who want to assurance regarding scientific rigor. JCO and JCO OP will require completing the CHEERS checklist for every manuscript.10,11
-
Potential clinical impact of findings: In situations where there is widespread support from evidence-based clinical practice guidelines that a new intervention provides meaningful clinical benefits relative to alternatives, CUA is unlikely to influence decisions, even for costly therapies. We will deprioritize these manuscripts. We will consider studies that evaluate costly interventions with benefits that—while significant in the statistical sense—are debated in terms of their clinical importance. Articles of most interest are those where there is clinical equipoise across multiple therapies that differ in terms of safety, efficacy, and cost. Here, the synthesis that CUA provides may offer insights for clinicians who often are in the best position to weigh tradeoffs and chose a therapy that provides high value for the patient and the larger health system. We urge authors to provide guidance that includes both clinical and economic insights to help oncologists weigh clinical and economic tradeoffs.
-
Selection of clinical comparators: It is best to consider clinical practice guidelines in comparisons, as these are the cornerstones of clinical decisions. Comparisons with off-label or little-used therapies are not helpful to practicing clinicians.
-
Use of simulation models: Models are expected in CUA, but clarity and transparency of description of the model are critical. For complex models, supplemental material that details modeling methods and inputs should be part of a submission package. The manuscript should describe models with a clinical audience in mind, taking care to use accessible language when justifying decisions regarding model structure, health states, and outcomes. We may request access to the models themselves for peer review as has been recommended.12
-
Description of uncertainty: Acknowledgment of uncertainty in CUA studies and cautions regarding interpretation of results are critical. Articles that highlight evidence gaps or points of clinical uncertainty that drive the economic outcome can be helpful in their own right. In some cases, the authors may want to highlight the need for further study as a precondition to broader use of the technology.
-
Evaluations of cancer care delivery interventions: Economic analysis of cancer care delivery interventions or processes of care may be useful if the topic considers alternatives that are feasible for oncology practices to implement.
-
Financial impact on patients: Given the high out-of-pocket (OOP) cost burden that patients face and the threats that financial toxicity poses for patients with cancer, we encourage articles exploring the relationship between OOP costs and the impacts on care and outcomes. Because OOP costs may vary across insurance plans and regions, it will be important to clarify the perspective for these types of studies (eg, Medicare, commercial insurer).
-
Industry-sponsored studies: Conflict of interest is a primary concern in industry-sponsored CUA studies and studies by authors with ties to industry. In practice, this conflict can manifest as both methodological bias and selection bias in the CUA studies sponsored from industry. Although positive economic studies sponsored by industry are not inherently all biased, a frequent problem for reviewers and editors is lack of transparency in methods. In short, our bar will be very high in terms of transparency of methods for industry-sponsored studies. Industry-sponsored CUA’s that do not include this level of transparency will receive lower priority.
In companion to this article, Wheeler et al13 exemplifies the type of approach that provides effective policy and clinical guidance for a common clinical problem: therapy sequencing for women with endocrine-refractory or triple-negative metastatic breast cancer. Using a sophisticated and well-described microsimulation model that was informed through multiple discussions with oncologists, the authors show that in this setting, the clinical outcomes are so similar that consideration of cancer care costs can be prioritized in most cases without sacrificing care quality. They go to great lengths to account for the inevitable uncertainty that is part and parcel of modeling, showing that practitioners can have confidence in their conclusions. Following their recommendations would reduce patient financial burden and save our health system hundreds of millions of dollars annually.
In conclusion, JCO and JCO OP encourage submissions of economic analysis in oncology, particularly those analyses that can influence clinical practice and practice policy. Our readers are on the front line of the debate regarding rapidly rising cost of cancer care. Although the best solutions likely lie in the policy domain (we favor a stronger role for CUA), we believe that high-quality, transparent, and accessible economic studies can help clinicians provide excellent care to patients while at the same time promoting sustainable and equitable cancer care.
