Dr Davey Daniel on Lower Cost of Care Seen in Clinical Trials for OCM Enrollees

Although enrollment in clinical trials is typically perceived by payers to result in more aggressive and costly care, findings of our study suggest otherwise, said Davey Daniel, MD.

Daniel served as contributing author of the abstract, “Impact of Clinical Trial Enrollment on Episode Costs in the Oncology Care Model (OCM),” presented at the 2021 ASCO Annual Meeting.

Transcript

Can you discuss how these findings conflict with some of the feedback you get from payers?

A little bit about our abstract that we're presenting at ASCO: So, we looked between 2016 and 2018 at our patients who were enrolled in the Oncology Care Model through Medicare and evaluated how many of those patients were on clinical trials during one of those episodes of care.

We had 5.7% of patients enrolled, and during those years, there were roughly 1000 patients per year on trials for Tennessee Oncology overall and 5.7% of the Medicare population, so that's 459 episodes of care. We then matched those patients to other patients in the Oncology Care Model based on cancer type, metastatic status, number of comorbidities, performance status, and age.

Based on that, we compared the costs of the 2 groups. These patients were all treated at Tennessee Oncology. About half of them were probably in the late-phase trials and half of our patients at Tennessee Oncology on trial are in the drug development unit.

What we found is actually kind of surprising. I think the perception by many, including physicians and certainly payers, is that the enrollment in a clinical trial results in more aggressive care and more costly care. And what we found is actually the opposite: that costs were actually lower for patients who were on trial than those not on trial.

In fact, it was about $6000 cheaper for patients who are on trial compared with those not on trial. We also saw that most of those cost savings came from decreased drug costs, and that really, we didn't see a higher utilization of hospitalizations. And we saw a similar usage of hospice care in both populations.

So, these are not patients who were at the end of life, having more aggressive care. They were still going on hospice at roughly the same rates.

Can payer delays in enrolling patients in trials—or getting approvals in general—impact clinical outcomes?

Any delays in the initiation of treatment can be a problem. Certainly, some patients feel that enrolling on their trial might delay their care. So anytime we see a barrier to that, whether it's delays and getting next-generation sequencing approved, imaging studies approved, that can delay care.

Our default really should be that most patients are able to enroll into a clinical trial. And so anything that deviates from that, or slows that down, really sets almost a default to a nonclinical trial, which is a problem. We need to make some strides forward, certainly. Sarah Cannon [and] Tennessee Oncology have emphasized that over the years—bringing clinical trials into the community setting. We know that the Affordable Care Act now requires insurers to cover clinical trials. In fact, most trials are written in such a way that anything considered experimental, those costs go to the clinical trial.

Really, there shouldn't be true barriers in that setting that set these delays. And so it's important that we almost set the default as considering clinical trial so that we can encourage more patients to enroll.

Are some payers more challenging than others when it comes to enrolling patients in trials?

It is somewhat variable the experience patients have when you consider next-generation sequencing. I think we know that certainly in lung cancer, it's a standard of care for comprehensive genetic sequencing. Other tumor types, we do get some pushback even though that is the only way to identify targetable mutations.

For instance, patients with colon cancer sometimes have some difficulty getting next-generation sequencing paid for even though that is the one way you will find a HER2 mutation that could be a driver.