Why Gathering Health Economic Data for Cancer Drugs is Now Essential

The oncology space has historically not been burdened by the reimbursement and access challenges common in other therapeutic areas.

As a result, health economic and outcomes research (HEOR) datasets have rarely been integral to product development and communication plans. However, as health systems around the world implement programs designed to contain growing healthcare costs, oncology therapeutics must now demonstrate clear value to patients, physicians, and payers.

For transformative therapies that achieve large changes in traditional “hard” outcomes (such as overall survival), demonstrating value is often straightforward. For therapies where benefits may translate into “softer” measures, or surrogate markers, or are incremental rather than transformative, building a compelling value story requires specific evidence that is often overlooked in clinical trial design, and can only be obtained from these datasets. Incorporating health economic and outcomes research evidence into oncology drug development pathways is no longer optional but essential.

For this to occur, the usual development pathway for oncology agents will have to shift from including a wide range of exploratory clinical trials across potential tumor types to collecting these datasets to support patient access to a more limited number of indications. This will require a reallocation of R&D resources. Unless a therapy is truly transformative, it is likely that oncology drugs will be required to undergo the same rigors assessment of value as in other disease states moving forward.

Why is the increasing importance of value in clinical oncology increasing?

Cancer drug spending grew from $75 billion in 2009 to $100 billion in 2014, an increase of 33%. Photo credit: Bill Brooks/Creative Commons

Just a few years ago, data showing a six-month extension in overall survival in a tumor setting would be cause for celebration and praised for innovation. That world is changing.

In the November issue of the New England Journal of Medicine, an editorial noted the cost of new cancer drugs and remarked that “the cost to insurers and patients of using the drug for this condition…can’t be ignored.” Payers around the world have taken note of the significant growth in cancer drug spending (from $75 billion in 2009 to $100 billion in 2014, an increase of 33%) and physicians are expressing concerns about the impact of the costs of these innovative medicines on the financial health and well-being of their patients. As noted in the NEJM editorial: “…the prices of new cancer drugs are increasing far faster than the benefits they offer.”

The only way to address the challenge is to measure and communicate value. Patients are becoming more informed about the cost of care and are instrumental in treatment decision-making.

Several groups, including the American Society of Clinical Oncology and the National Comprehensive Cancer Network, have recently released tools that include some measure of value to assist patients with treatment decisions. Outside the US, most healthcare authorities and reimbursement groups apply strict value measures to their coverage policies, which can limit access to medications. Indeed, the UK’s National Institute of Clinical Evaluation, which conducts value assessments of all approved agents in England and Wales, recently removed more than 100 cancer therapies from their list of reimbursed medications because they did not provide sufficient value.

The biggest hurdle to overcome is most often not a low therapeutic effect or high cost but rather having the right types of data to support overall value. Decreased healthcare utilization like fewer hospitalizations, outpatient care versus in-hospital treatment, the reduced need for caregiver/nursing support, and the ability to continue working are all part of the “value story” commonly created in other therapeutic areas, but not traditionally evaluated or reported in cancer studies.

What types of datasets and resources are needed to support patient access in the future?

Several types of HEOR approaches and datasets are available to assist in making informed healthcare coverage and access decisions. The following highlights how these may be applied for the oncology space.

1. HEOR endpoints should be included in clinical trials. These should include aspects of medical resource utilization and patient-reported outcomes that evaluate disease- or treatment-related patient functioning. These assessments are often cut from clinical trials because of the associated incremental investment required and because they are unlikely to lead to labeled claims. However, reimbursement decision makers are not limited to labeled claims when making coverage and formulary placement decisions.

2. Supplement clinical trial data with HEOR-driven data generation that is fully aligned with the clinical development program and strategic objectives for the product. It can be up to two years post-launch until there is sufficient real-world utilization data available; however, a prospective registry or observational study can be conducted within this period to generate evidence in the clinical practice setting.

3. View generation of real-world evidence as essential as pursuing early proof-of-concept studies. The drug development in oncology frequently includes conducting several early proof-of-concept trials to assess where a particular drug may be effective; these trials are usually exploratory or aspirational and often fail to show sufficient benefit to warrant further development. Moving forward, organizations might consider investing research funds to capture real-world evidence through greater inclusion of patient-reported outcomes and HEOR measures in mid-stage and late-stage clinical studies; peri-launch and post-launch real-world evidence initiatives such as chart reviews, database analyses, and registries) to understand drug use in clinical practice.

HEOR, once considered just a support function, is an integral component of the clinical development and commercialization strategy for a compound, and a central part of both internal and external decision-making processes. While healthcare systems may differ in how HEOR data are applied, the urgent need for these types of data in the oncology setting will only continue to grow.

Thus, incorporating HEOR evidence into oncology drug development pathways is no longer optional but essential. So, wouldn’t reallocation of some of the R&D resources be better served to collect HEOR datasets to support patient access to more limited number of indications?

Jason McDonough is SVP of medical strategy at Cello Health Communications.