The complexity of the tumor microenvironment represents a significant challenge to the personalized medicine movement in the field of oncology. While genetic and genomic analyses enable an understanding of the patient’s genotype, this does not necessarily translate to active tumor microenvironment expression – phenomics – through which pharmacodynamic pathways are modulated by targeted therapies. Similarly, while single biomarker immunohistochemistry (IHC) can effectively quantify expression of a particular biomarker, it fails to evaluate the entire picture of the tumor microenvironment, where a myriad of potentially confounding factors exists to distort the causal relationship between expression of a single marker and treatment response.Enter context-based analysis of biomarker expression – quantitative, multiplex IHC technology leveraging “big data” capabilities to overcome the inherent limitations of existing diagnostic techniques and more precisely assess the tumor microenvironment. Applied as a companion diagnostic (CDx), quantitative IHC or IF (qIHC/IF) using image analysis (IA) technology represents a potentially paradigm-shifting approach to predict patient response to oncologics and thus bring the movement of personalized medicine to fruition.
Expanding Patient Access to Personalized Medicine
From both a payer and oncologist perspective, the greatest value proposition for qIHC/IF technology is likely its ability to more accurately predict patient response to targeted therapy. In an increasingly value-based environment, payers seek the best patient outcomes for their dollar-spend on expensive drugs. Likewise, oncologists seek to promote high quality patient care through well-informed treatment decision-making. The key to achieving these goals is the ability to accurately identify patients most likely to respond to a particular therapy. As a companion or complementary diagnostic, qIHC/IF may enable more precise patient selection, ultimately providing strong diagnostic support to drive patient access to personalized medicines.
Optimizing the Laboratory
A companion diagnostic based on quantitative IHC/IF analysis also presents significant potential upside from a laboratory perspective. Image analysis offers a unique combination of automation (i.e. interpretation and reporting) and objective precision that could allow clinical laboratories to accurately, reliably assess tissue samples in a more efficient manner. As a value driver efficiency will resonate more strongly if a qIHC/IF companion diagnostic is indicated for a more prevalent cancer, such as lung, breast or colorectal, for which clinical labs have a great volume of samples to process on a daily basis. The downstream clinical impact of such efficiency is greater throughput, expanded capacity and valuable time saved for labs to focus on other tasks. One can expect a potential financial benefit for the laboratory based on these advantages as well. Overall, the potential clinical benefits and workflow enhancements enabled by a qIHC/IF companion diagnostic could support a compelling value story to facilitate strong adoption and uptake in the clinical laboratory setting.
Finding a Pathway to Market Access and Reimbursement
Access to a companion diagnostic should not be the limiting factor in patient access to personalized medicine. To be ready for primetime, a CDx manufacturer must be able to address market access and reimbursement challenges and overcome potential adoption barriers. A qIHC/IF CDx is no different. A well-designed evidence development plan and sound reimbursement strategy are two considerations of particular importance to tackle these challenges.
Robust clinical and economic evidence is an absolute necessity in today’s value-based healthcare landscape. Such evidence must be designed to resonate with all core qIHC/IF CDx access stakeholders – oncologists to drive request for testing, laboratorians to facilitate adoption in the clinical lab setting and payers to support coverage and reimbursement decision-making. Clinical evidence should demonstrate strong performance to support underlying value messages related to accuracy, quality of care and precision medicine. For a companion diagnostic technology, positive predictive value is perhaps the most critical performance parameter – a low false positivity rate ensures appropriate patients are selected for a targeted therapy. This is an important consideration not only for qIHC/IF CDx access stakeholders, but for pharmaceutical companies, too, as they determine the most suitable diagnostic partner. Ultimately, a CDx implementing quantitative IHC/IF based on image analysis must be well-validated in the patient population for which it will be indicated for use.
Additionally, economic evidence will be crucial, and arguably most impactful from a lab and payer perspective, to demonstrate the downstream cost impact of utilizing a qIHC/IF CDx. Economic evidence should translate clinical performance, care quality and workflow impact into cost-savings and articulate overall budget impact from appropriate stakeholder perspectives. It is important for the economic value story to be focused, transparent and valid to increase stakeholder receptivity to financially-centered value messages.
Quantitative IHC/IF companion diagnostics using image analysis technology must have a viable pathway to routine, optimal reimbursement. This is imperative to drive laboratory adoption of such technology. Labs will not be willing to adopt a qIHC/IF CDx if reimbursement for the technology is unreliable, inconsistent or insufficient to cover the test kit and associated labor.
The core components of reimbursement strategy are coverage, coding and payment. Coverage represents insurer willingness to offer qIHC/IF CDx as a covered benefit for plan beneficiaries. This decision will be made on a payer-by-payer basis, and is dependent on a multitude of considerations (i.e. guidelines inclusion, published literature, economics, etc.) too extensive to describe here.
Coding represents the language used as a mechanism to accurately describe and bill the qIHC/IF CDx test. In the United States, a couple potential Current Procedural Terminology (CPT) coding pathways exist for qIHC/IF CDx. For one, a manufacturer may pursue existing methodology-specific (i.e. IHC) CPT coding. Alternatively, if a qIHC/IF CDx incorporates an algorithmic component to generate the test result, obtaining a multi-analyte algorithmic analysis (MAAA) code may be an opportunity. There are benefits and trade-offs to either coding strategy. For a methodology-specific code an established reimbursement rate is likely available, but at a commodity-based payment rate. For an MAAA code, it will likely take longer to obtain reimbursement, but value-based payment is achievable. There are other benefits and trade-offs associated with these coding strategies, but overall, viable pathways do exist to appropriately code for a qIHC/IF CDx in the United States.
The final component of reimbursement strategy is the actual payment (or reimbursement) rate for the qIHC/IF CDx. This is typically based on the fee schedule rate associated with the chosen CPT code and varies from payer to payer. As previously mentioned, some CPT coding constructs are associated with commodity-based (lower) payment rates, while others are associated with value-based (higher) payment rates, designed to accommodate innovation.
While manufacturers of image analysis-based qIHC/IF approaches are certainly justified to seek a value-based payment for their innovative products given the potential benefits such technology offers, such an aspiration can present quite a conundrum if it subsequently impedes access to precision medicine. There is no correct answer to what is the right reimbursement strategy for a qIHC/IF CDx, but manufacturers must ensure that sufficient evidence and a compelling value story is presented alongside their product to support the case for adoption and uptake.
About the Author:
Dan Carlow is a Market Access and Reimbursement Strategist at GfK. Dan’s expertise in diagnostics spans the areas of oncology, infectious disease and women’s health. His actionable insights and recommendations help innovators achieve commercial success. To contact Dan, please send an email to Dan.Carlow@gfk.com