“A lot of clinical trials are a bit artificial in that the eligibility criteria are ‘purple and pink polka dot patients,’ [but those patients] really don't exist.”
That was the start of my conversation with Dr. Julie Vose at the 2019 American Society of Clinical Oncology (ASCO) annual meeting, where we sat down to talk about real-world evidence and its importance in oncology. Dr. Vose is a believer in evidence-based medicine, and real-world evidence is an important tool in her arsenal for making treatment decisions at the University of Nebraska Medical Center, where she is the head of hematology and oncology.
According to Dr. Vose, since clinical trials don’t often recruit everyday patients, then everyday outcomes won’t be reflected in the trial results. That’s why real-world evidence is so important to oncologists. Analyzing real-world evidence is the key to understanding how well a therapy works in “real” patients—not an extremely specific set of patients, like those with “purple and pink polka dots”—outside the confines of a tightly controlled clinical trial. Real-world patients are often older and less healthy, and oftentimes have co-morbidities that aren’t studied in the clinical trial.
Randomized clinical trials remain the gold standard for evidence that physicians rely upon to make treatment decisions—and often for good reason. One need only look at the data presented during the ASCO plenary session on olaratumab to see why. Olaratumab received accelerated approval by the FDA in 2016 based on a phase Ib/II open-label trial that had shown an 11.8-month improvement with olaratumab over a placebo for advanced soft-tissue sarcoma patients. But the phase III study results, also shared during the session at ASCO, failed to confirm the survival benefit, causing Eli Lilly to withdraw the product from the global market.
However, despite their significance, randomized controlled trials present challenges of their own. They require large cohorts of patients, which can often be challenging and costly to recruit. And they are time-consuming, especially when overall survival is the endpoint and the therapy under consideration is efficacious at prolonging life. Moreover, with the shift toward precision medicine, there’s an increasing desire to not just understand if a therapy works, but to understand which patients it will work for the most. As a result, it’s no surprise that pharma manufacturers go to great lengths to ensure successful trials by heavily controlling the eligibility criteria for patients to participate in a clinical trial.
While RWE offers insight into how everyday patients might respond to a therapy without the same challenges presented by a randomized controlled trial, it’s difficult to get a large enough sample of patients to make scientifically sound decisions. “We definitely analyze the different disease entities and different treatments within our own practice to make sure that what we're saying to patients is correct,” said Dr. Vose. “And then we also use, of course, real-world evidence that's based upon larger multi-center projects. And we often collaborate with other academic centers to make sure that we combine our data and analyze that in different situations.”
The multipronged approach is a reflection of the disaggregated nature of the data needed to make real-world evidence more powerful. Many large hospitals and health systems collect their own data and seek to tap into shared data from other sources as well because big data is needed to make the insights most actionable. ASCO’s CancerLinq was designed for just that purpose and now contains de-identified real-world data on more than 1.5 million cancer patients, according to Dr. Vose.
With so much opportunity available, how can manufacturers help providers unlock the power of real-world data? Here are three opportunities to get started:
1. Data aggregation: With all the disparate sources of real-world data, there’s a need to link data across providers and platforms so that insights can be gleaned from patient outcomes beyond those observed within a single practice.
2. Localized insights: Providers care most about data that will help them make evidence-based decisions that are right for each individual patient within their individual practice. There’s a need to translate big data into relevant, specific insights.
3. Adding to the “pool” of data: Big data works best when there’s more information in the system. There’s a need to collect and share more data more broadly to add to the body of evidence available.
4. Leveraging RWE to show efficacy in ultra-rare patient types: Recent examples of RWE analyses by Roche-Genentech for entrectinib (demonstrating efficacy in lung tumors with ROS1 fusions) and Pfizer for Ibrance (gaining approval for Ibrance in male breast cancer, and Bavencio for merkel-cell carcinoma) demonstrate the power of RWE to show efficacy in small patient populations that would otherwise be infeasible to study in a large randomized clinical trial.
While there are still many unmet needs to be addressed with real-world data, it’s clear that real-world evidence will continue to grow in importance. What is your organization doing to advance the promise of real-world evidence in oncology?