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Conference Coverage

Analyzing Single-Arm Trial Data to Cover Drugs Granted Accelerated Approval

Maria Asimopoulos

Collaboration between health care stakeholders and use of real-world data are key to guiding coverage decisions for drugs granted accelerated approval based on single-arm trials. Speakers defined the challenges payers face in a session at AMCP 2022.

“You have to make decisions based on imperfect data. How can we mitigate some of those uncertainties?” said Ambarish J Ambegaonkar, PhD, chief executive officer, Apperture LLC.

Single-arm trials are clinical trials that lack a comparator. These studies are nonrandomized, include small sample sizes, rely on surrogate endpoints, result in immature data, and have greater potential for biased results compared to randomized, double-blind trials, which are considered the gold standard, Dr Ambegaonkar said.

Single-arm trials are most common for medications intended for rare diseases or oncology, in which the pool of potential participants is limited and there is often high unmet need. Promising phase 1 data, as well as patients’ desire for fast access after exhausting other treatment options, have increasingly encouraged regulatory acceptance of single-arm trials.

“That is where innovation is heading right now,” Dr Ambegaonkar said. “There is a significant unmet need, and that unmet need is driving the emergence of single-arm trials.”

Between 2015 and 2021, the US Food and Drug Administration (FDA) issued approvals for 48 drugs based on single-arm trial data, Dr Ambegaonkar said. New approvals were largely based on phase 2 data (28), followed by phase 1/2 data (9) and phase 3 data (4).

When the FDA grants accelerated approval, pharmaceutical companies are then required to provide additional data supporting the drug’s efficacy, most of which is acquired in phase 3 trials. Confirmatory studies produce data in 3 years on average, which may result in complications for a drug’s approval, Dr Ambegaonkar said.

The estimated orphan drug market is expected to increase between 2021 and 2026, from $143 billion to $208 billion on a global scale, and from $42 billion to $61 billion in North America. Oncology and neurology drugs occupy the first and second largest shares of the market, respectively, said Winston Wong, PharmD, principal, W-Squared Group.

Of the 20 oncology-related medications and diagnostic agents approved in 2020, 15 agents were approved with phase 1 or phase 2 data, and 15 approvals were supported by data gathered in a single-arm trial.

“These are diseases with small populations, and looking for a larger population will take much longer to generate the kind of data you encounter in a larger study,” Dr Wong said.

Payers face several challenges for covering drugs approved with data from single-arm trials. Dr Wong advised payers to consider how other plans are covering the drug, as well as whether the drug fits into current treatment guidelines for its respective disease state.

“This is where the need for the preapproval information exchange becomes very significant. I’m not trying to promote the program, but that’s something we definitely need,” Dr Wong said.

Expedited approvals are also associated with higher costs, Dr Wong noted, prompting the need for cost-effectiveness research. This presents a new problem, as cost-effectiveness data may not be applicable in a real-world setting.

“In some situations, we do have cost-effectiveness evaluations by ICER or NICE,” Dr Wong said. “But it’s also questionable as to whether the evaluations are indicative of...the real-world setting, not because of a flawed process by those organizations, but mainly because of the limited information that can be used to feed into cost-effectiveness models.”

Unknown long-term benefits and tolerability can also impact comparative effectiveness evaluations.

Large and self-funded employers may request coverage of orphan drugs to maintain their employees’ satisfaction with health benefits. Private payers have more flexibility to cover or to not cover medications than public payers, Dr Wong said. Public payers such as Medicare and Medicaid will therefore take on more risk and higher costs by comparison.

“Due to the tendency of these medications to be used at higher cost, we have to now start looking at the possibility of financial toxicity,” Dr Wong said. “Organizations really need to establish a framework by which these medications can be evaluated.”

Payers must determine the true unmet need in the disease, the clinical benefit and associated durability of each approved medication, and the overall costs of care while accounting for patient outcomes, Dr Wong advised.

“We need to take a much more holistic approach and use all the relevant data…to make changes in our decision process in real time,” Dr Wong said.

Real-world data should set the standard for entering value-based partnerships, Dr Wong said, so payers can ensure the net price of a treatment is linked to expected outcomes.

Several sources of data can be used to create an external control arm and potentially mitigate these challenges, said Satish Valluri, PhD, head of CAR-T global market access, Janssen Pharmaceutical Companies of J&J. These can include prior clinical trial data or real-world data such as that of database studies, chart reviews, and patient registries.

“You can combine these different data sources. These are not exclusive,” Dr Valluri said.

The session included a checklist for payers assessing indirect comparison data:

  1. How well are the patients matched on the inclusion and exclusion criteria? Is the external data fit for the purpose?
  2. Is the protocol and the statistical analysis plan developed a priori?
  3. Is there immortal time bias (especially relevant for oncology studies)? Does the analysis adjust for the most important confounders?
  4. Are the relevant endpoints being compared and measured similarly in the clinical study and the external control arm?
  5. Are the results consistent regardless of various statistical methods used? Can the results be replicated with different external real-world data sources?

Speakers encouraged partnerships between providers, payers, and pharmaceutical companies to generate real-world data and comparative evidence, understand long-term outcomes, and evaluate potential costs.

“We will see more medicines approved based on single-arm trials, new mechanisms of action, new modalities…so it is important that there is an appropriate framework for population health decision makers to assess the value of these medicines,” Dr Valluri said.

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