(Real-World) Knowledge Is Power
Why real-world data is especially important in the treatment of retinal diseases
Christopher Brittain | | 4 min read | Opinion
The importance of quality real-world data in advancing the treatment of retinal diseases really cannot be overstated. Although clinical trials, of course, remain the gold standard when it comes to ensuring that any new retinal medications are safe and effective, they are sadly not without their blind spots. Older patients, people with multiple chronic conditions, individuals from hard-to-reach communities, and individuals from some ethnic and diverse communities are just some of the groups that have been historically underrepresented in clinical trials. And yet they will still ultimately make up a proportion of the people who receive retinal treatments out in the real world. And let’s not forget that clinical trials must have a finite duration, meaning they can only tell us so much about the long-term use of a treatment.
When it comes to leading causes of vision loss, such as age-related macular degeneration, diabetic retinopathy and retinal vein occlusion, there is something of a data gap in robust long-term outcomes. Some treatments have shown huge promise in delivering positive outcomes in clinical trials, but have not yet fully realized this in day-to-day use. This can be attributed partially to the high burden of treatment – in particular, the need for frequent eye injections – which leaves many patients undertreated and not able to achieve the best possible vision outcomes. Additionally, clinical trial data sets are unlikely to provide insights into how healthcare professionals swap people from an existing treatment option to a new medication with a different mode of action.
So how do we close this gap? Real-world data has a pivotal role to play in connecting what we observe in clinical trials and what we know about day-to-day treatment outcomes for patients. As the name suggests, real-world data is intended to closely capture real-life routine practice outside of the highly controlled clinical trial setting. As a result, it encompasses the full complexity of patient demographics, comorbidities, treatment adherence, and extended use, a large transition away from the controlled inclusion and exclusion criteria of a randomized controlled trial. The data itself can take many forms and come from a wide range of sources, including surveys, patient registries, electronic health records, Health Authority adverse event reporting databases and non-interventional studies. The various information streams allow for important new insights about the long-term safety, effectiveness, and use of treatment options in practice. When taken together with what we know from clinical trials, real-world data has the potential, overall, to provide a much richer clinical picture of the current treatment landscape for retinal diseases.
Of course, collecting real-world data has its challenges – the flip side of capturing such a wide range of measures and outcomes is that the quality of data collection and sources can vary widely. Real-world data is also arguably more vulnerable to biases in selection and interpretation outside the strict controls of clinical trials. And all these challenges make statistical analyses more complicated. With the rise of remote monitoring technologies, and electronic health records, ensuring patients are fully aware and informed of how their data is going to be collected, stored, and used is also critical.
At Roche/Genentech, we embrace the challenge, investing significantly in generating robust real-world data across our ophthalmology treatments. Our program of real-world studies, investigates all aspects of treatment patterns, and long-term safety and efficacy of approved ophthalmology treatments. These are all factors that drive decisions in routine clinical practice. We also work closely with the vision loss community to ensure our real-world data studies are advancing inclusive research. Our ongoing research, for example, examines treatment response in historically underrepresented populations with macular edema, including African Americans, Hispanics, Indigenous populations and Asian Indians.
Not only do we strive to generate real-world data that will be of use to the wider ophthalmology community, but we also use those data insights to shape our own research and development programs. For example, understanding that treatment burden has been a driver of the gap between clinical trial and real-world outcomes in retinal diseases has focused our efforts on i) treatment options with the potential for longer dosing schedules that can maintain vision with fewer injections, ii) remote monitoring technologies that can help patients get the support and care they need with fewer clinic visits, and iii) providing better patient education and support to enable participation of patients from underrepresented minority groups in clinical trials.
Ultimately, as the saying goes, knowledge is power. Whether informing better treatment protocols for doctors and patients, guiding regulatory and reimbursement decisions, or helping pharmaceutical R&D scientists identify how they can make the biggest difference to patients, real-world data is the key to unlocking a brighter future for people living with retinal diseases.