By analyzing the outcomes for thousands of actual cancer patients, we can better compare drugs' effectiveness and develop pathways that are more precisely tailored to individual patients.
In an ideal world, identifying the highest-value regimen for a given patient's cancer would be straightforward. Oncologists would quickly look up the therapies with the longest overall survival and compare the rate and severity of complications associated with each. Then, if two or more options were roughly equal in efficacy and toxicity, their costs would serve as a tiebreaker.
The reality is far messier. More and more often, promising cancer drugs are fast-tracked through Food and Drug Administration (FDA) review, leaving unanswered questions about their true efficacy and toxicity. Many are approved based not on their impact to survival, but on surrogate measures such as progression-free survival. In phase 3 clinical trials, they are sometimes compared against a drug that was favored years, even decades ago, rather than today's standard of care. And participants in such trials are not representative of the overall cancer population, which is typically sicker, poorer and more likely to be a minority.
How do drugs perform in the real world, where patients may have diseases in addition to their cancer, financial barriers or other challenges not as common in the controlled environment of a clinical trial? You'll be hard-pressed to find the data because post-approval studies to confirm a drug's efficacy, though required by the FDA, are reported just over half the time. And comparative effectiveness studies of different cancer drugs are surprisingly scarce.
To compensate for these shortcomings, those of us who design clinical pathways don't review clinical trial results in isolation. New Century Health convenes a host of experts—practicing medical oncologists and radiation oncologists, as well as patient advocates—on our Scientific Advisory Boards to guide us. They pore over what evidence exists about the performance of cancer therapies after FDA approval and discuss the results they see first hand in their patients. At times, this group has steered us away from proposed pathways based on their consensus that actual results don't match the promise from clinical trials.
_q_tweetable:"Real-world evidence has the potential not only to strengthen existing pathways, but also to spur the creation of increasingly granular pathway options, tailored to the unique characteristics of each patient case."_q_
But we are approaching a future in which we'll have far more information to guide these decisions. Real-world evidence (RWE), in the form of vast databases collecting details on patients' cancer cases, their treatments, survival and complications, is rapidly maturing after years of development. Mining this RWE, we will be able to compare how patients fared on different drugs when they had similar cases—the same cancer type and stage, biomarkers, comorbidities and more.
RWE has the potential not only to strengthen existing pathways, but also to spur the creation of increasingly granular pathway options, tailored to the unique characteristics of each patient case. If a patient has stage 3 breast cancer but also diabetes and heart disease, we can use RWE to identify regimens associated with the best results in similar cases.
Merged with claims data, RWE could also help us better understand the true costs of different cancer regimens, aside from the cost of the drug itself. How often do complications result in emergency department visits or hospitalizations for a specific group of patients on a given regimen? These visits can quickly wipe out the savings you might achieve with a lower-cost regimen, and we should account for them.
As optimistic as I am about the coming new era of oncology pathways, RWE is not a panacea. It won't provide black and white answers, but rather carefully drawn recommendations based on sophisticated analysis of messy data. We'll need to be mindful that correlation does not equal causation. There may be explanations that our data cannot capture for one regimen performing slightly better than another.
In addition, promising new drugs are entering the market at a rapid pace, changing the alternatives for treating different cancers. It may be years before we have enough RWE to analyze their efficacy, toxicity and true costs for patients.
However, when RWE is available, it can complement well-designed (hopefully) clinical trials and be used in the drug approval process, forming a powerful combination of data to help us direct therapy to the most appropriate patients.
About the AuthorFollow on Linkedin More Content by Andrew Hertler, MD