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Randomized controlled trials establish strict inclusion and exclusion criteria in an effort to optimize the cohort of trial participants.
Randomized controlled trials (RCT) are the gold standard for demonstrating the safety and efficacy of promising therapies and vaccines. Trial results define the clinical and prescribing information that will become the approved label language, and that information defines the standard of care. By design, RCTs establish strict inclusion and exclusion criteria as part of the study protocol in an effort to optimize the cohort of trial participants.
Unfortunately, these inclusion and exclusion criteria, along with selected trial sites and other structural barriers, often result in specific patient subgroups being underrepresented in or excluded from the clinical trial. When structural barriers related to, for instance, race, ethnicity, age, gender and socio-economic factors limit the ability of certain patients to enroll in clinical trials, the RCT results may not reflect how the new therapy will perform among the underrepresented population.
While there has been an effort in recent years to improve diversity and equity in trial enrollment1, it is simply not practical—from both a cost and logistics perspective—to expect any trial sponsor to indefinitely expand an RCT to include every single patient subpopulation that may someday benefit from a medication. And even when a trial can increase enrollment diversity, the number of added patients involved will not yield statistically significant insights.
The absence of specific subgroups in a clinical trial results in gaps in knowledge that directly impact prescribing practices and thus the ability of patients to access the most appropriate therapy option.2 Similarly, the findings produced during narrowly focused RCTs are often poorly applicable to the broader populations of patients who are likely to be treated using the therapy under real-world conditions at the point of care.
To help close the gaps and develop broader insights related to the clinical and safety impact of a given therapy on patient subgroups that may have been underrepresented in the original RCT, sponsors should increase use of real-world evidence (RWE). Specifically, data collected during routine care can be analyzed to understand real-world treatment results at scale. Traditional and advanced data sources and technologies can be used to understand outcomes in subgroups. Two types of RWE studies are particularly useful to address persistent diversity and equity challenges in clinical trials:
1. Comparative effectiveness studies aim to compare clinical effectiveness of several approved therapies in order to identify which one performs better within specific patient subgroups. Such studies are particularly important for crowded therapeutic spaces, where a particular condition may have many approved therapy options available.
2. Subgroup analytics aim to identify how a given therapy performs within a specific patient subgroup, and to develop new clinical and safety insights that can inform clinical care. These studies are designed to address the knowledge gaps discussed above.
These studies are increasingly being used to refine the standard of care3, where an RCT defines what is safe and effective for a population and RWE defines preferred therapy among treatment options for a given subgroup. When used in this way, RWE will influence care decisions and should be upheld to the same expectation of rigor as RCTs. Inaccurate or “bad” data allowed into regulatory or reimbursement pathways can have unintended and dangerous consequences. Data validity, including accuracy measurement, should be viewed as a necessary precaution as the industry is working to gain accurate insights that will help tailor therapy over the coming decade.
Traditional safety and efficacy data coming out of the RCT should be augmented with targeted RWE studies that aim to investigate how a given therapy performs in specific patient subgroups that were not adequately represented in the underlying trial. Pharmaceutical firms have increasingly funded these studies as payers and prescribers demand more evidence of effectiveness and knowledge of which patients benefit most. Such efforts will help close diversity and equity gaps, support both precision medicine and the use of personalized therapies and improve health outcomes for patients, all important healthcare objectives today. Importantly, unlike localized efforts to broaden enrollment by adding a few (or even a few hundred) additional trial participants from traditionally underrepresented patient groups, focused RWE studies allow stakeholders to work at larger scales and produce statistically significant, data-driven insights in the real-world.
Dan Riskin, CEO of Verantos