Introduction and Overview of IO
Immunotherapy in oncology (also referred to as immuno-oncology or IO) represents a promising new treatment category. Modern IO therapies use T-cells (white blood cells) that are stimulated to recognize and attack cancer cells, thereby equipping the body’s own natural defenses to fight cancer.
IO is a fairly broad category of treatment, encompassing different mechanisms of action for therapies. Perhaps the most well-known IO treatments are checkpoint inhibitors, which include PD-1 inhibitors (pembrolizumab [marketing approval for MM, NSCLC, HNSCC (US only)], nivolumab [MM, NSCLC, RCC, HL, HNSCC (US only)]), PD-L1 inhibitors (atezolizumab [NSCLC]), and CTLA-4 inhibitors (ipilimumab [MM]). Chimeric antigen receptor (CAR) T-cell therapies (eg, adoptive cell therapies) that are in development for B-cell malignancies (leukemias and lymphomas) also fall into the category of IO, as do oncolytic viruses (approved for MM) and cancer vaccines (in development for several solid tumor types).
All of these specific treatment types within IO have shown promising results in comparison to traditional chemotherapeutic agents and other targeted therapies for both solid tumors and hematologic malignancies. The IO category seems poised for success, with FiercePharma listing an upcoming IO drug release in its predicted top 10 launches of 2017. Despite being hailed as the future of oncology, given the high cost of therapy and payer skepticism toward new oncologic agents, obtaining coverage and reimbursement for IO therapies can be difficult. In this article, we will discuss the challenges of obtaining approval from global HTA authorities and local market payers, and we will present some potential solutions to address evaluator concerns that may negatively impact IO therapy coverage and reimbursement within a given market.
Challenges in Obtaining Coverage and Reimbursement for IO Therapies
It should come as no surprise that increasing oncology drug costs are a main driver of the challenges surrounding coverage and reimbursement. This becomes even more problematic from the payer perspective when IO drugs are being added to already-expensive treatment regimens for melanoma, lung cancer, and the like. From the perspective of HTA authorities focusing on value of the drug vs costs to the healthcare system, the addition of an IO drug to the regimen may produce a very high incremental cost-effectiveness ratio (ICER) for the add-on product. Perhaps the most well-known example of this situation in IO therapies was the initial decision by the National Institute for Health and Care Excellence (NICE) not to issue positive guidance for ipilimumab in 2012 based on its ICER being above the common £30,000 threshold for cost-effectiveness. Thus, the drug was only available at the time of the decision through the Cancer Drugs Fund. Ultimately, it took the issuance of an undisclosed discount by the manufacturer to the National Health Service (NHS) in order for the drug to receive positive guidance from NICE several years later (ICER after discount was £47,900/quality-adjusted life year [QALY] vs dacarbazine and £28,600/QALY vs vemurafenib).
Lack of Biomarkers in IO
At this point in time, there are still few biomarkers or diagnostic tests to help determine tumor susceptibility to treatment with checkpoint inhibitors or other IO therapies. Historically, single marker tests—including BRAF, KRAS, ALK, and others—have been the gold standard for mutation testing in oncology. However, clinical trial results for IO therapies have shown that biomarkers such as PD-1 and PD-L1 are much less helpful as predictive biomarkers of response. Therefore, this current inability to narrow down the population to a subgroup that is more likely to respond is certain to drive up ICERs and reduce average patient improvement across efficacy measures in any trial. Fortunately, efforts are underway to determine other possible predictive biomarkers in IO, including transcriptome (or gene expression) profiling, flow cytometry, and protein microarrays. Until diagnostic tests or other methods of determining the best responders to an IO therapy are available, payers and HTA evaluators may continue to be skeptical of the value of the treatment when given to all patients within a given indication.
Trial Robustness and Post-hoc Analyses
Loosely related to the issue of a lack of biomarkers in IO is the issue of trial robustness and the ability to conduct post-hoc analyses of trial results. For many of the pivotal studies for IO therapies, the populations meet very specific requirements and are often too small to be split across many subgroups and still see statistically significant differences in measures of efficacy vs the comparator. Furthermore, therapies that have received marketing authorization as a result of accelerated approval processes (ie, fast track approval) could lack larger pivotal phase 3 trials (eg, nivolumab in metastatic melanoma). In both of these situations, small sample sizes make the job of HTA authorities difficult in terms of ascertaining true benefit of the drug, especially in small subgroups of patients. As an example of this principle in action, the assessment by the Institute for Quality and Efficiency in Healthcare (IQWiG) of nivolumab for metastatic melanoma in Germany led to different added benefit ratings across subgroups split by gender, age, previous treatment history, or prevalence of genetic mutation. Some of these groups received “minor” or “hint” of added benefit ratings due to having low or no statistical significance with such a small subgroup size. Similarly, nivolumab for metastatic melanoma also received a mixed approval decision from the pan-Canadian Oncology Drug Review (pCODR) Expert Review Committee (pERC), which was split by genetic mutation. The reasoning for this decision included a statement on “immaturity of the data” and “limitations in the evidence from the available clinical trial.”
Opportunities for IO Therapies in Coverage and Reimbursement Decisions
In the quest to achieve coverage and reimbursement across global markets, several key factors can make a difference in an HTA submission for an IO therapy. First, having a clear understanding of the market landscape and payer expectations can help set the stage for a successful HTA submission. Therefore, collecting payer insights through early advice requests and market access expert/KOL market research events is an important step in preparing for data generation and dossier development.
Additionally, payer and HTA evaluator education is key. They need to clearly understand from the dossier who the intended population is, what the burden of illness is, and the IO treatment’s place in therapy. Related to the place in therapy, choosing the correct (or incorrect) comparator can have a major impact on the HTA evaluation. As the nivolumab assessment for unresectable or metastatic (stage III or IV) melanoma by the Pharmaceutical Benefits Advisory Committee (PBAC) in Australia showed, other IO therapies—even in a head-to-head study (in this case, nivolumab vs ipilimumab*)—may not be the right comparator if the HTA authority has not already issued a positive decision for the comparator product. Furthermore, as fast track approvals may lead to reimbursement decisions being made for products with immature data or small sample sizes, additional real-world outcomes data collected through retrospective or prospective studies can be a crucial factor in achieving a positive coverage decision.
Additionally, clear demonstration of cost-effectiveness is vital for approval in markets where HTA evaluations hinge on cost or cost-per-outcome. Cost-effectiveness analyses should be simple, credible, and demonstrative of the value of the product within the specific indicated population. Where cost-effectiveness is likely to be above standard thresholds for an HTA authority, it is wise to consider risk-sharing agreements or patient access schema that may create an opportunity for a more favorable decision. Bristol-Myers Squibb was able to do just that in getting nivolumab approved in combination with ipilimumab for MM in the UK in record time by allowing an undisclosed discount on ipilimumab in order to make the combination cost-effective (ICERs after discount were £10,400/QALY [BRAF-mutation negative population] and £19,300/QALY [mixed population] vs ipilimumab alone).
Achieving coverage and reimbursement in HTA markets can be difficult for new oncology therapies given the current landscape. However, the promising results with IO coupled with the right data and approach can lead to a successful positive decision.
MM, metastatic melanoma
NSCLC, non-small cell lung cancer
HNSCC, head and neck squamous cell carcinoma
RCC, renal cell carcinoma
HL, Hodgkin’s lymphoma
BRAF, proto-oncogene B-raf, serine/threonine kinase
KRAS,V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog
ALK, anaplastic lymphoma kinase gene
*At the time of assessment of nivolumab, ipilimumab had not received a positive coverage decision from the PBAC. The negative decision on ipilimumab at the time was based on unacceptable cost-effectiveness.