Embrace the Burden! Why Burden-of-Illness Real-World Evidence Studies Are More Important Than Ever
Burden-of-illness real-world evidence studies – initiatives that establish the impact and overall cost of a particular disease from multiple perspectives – have always been important for drug developers, helping them to better understand how to optimally position a new product as a potential solution. That said, there are a number of reasons why it’s never been more critical to undertake burden-of-illness studies. Indeed, characterizing the burden of a particular disease should be viewed as an opportunity, rather than a burden.
Developing an understanding of the clinical, economic, and humanistic burden of a disease (as well as its epidemiology) provides important context for assessing the potential value of a product in development: the data represent an end as well as an important means to an end. Ultimately, documenting the current status quo of a disease from patient, physician, payer, and societal perspectives can serve as an essential baseline against which to establish the actual benefit of a drug or device after it is approved. Establishing that baseline early in product development – well before product approval – can help identify how and where a new treatment may contribute to improving disease outcomes.
So, What Are Some Key Considerations?
In many ways, establishing the burden of illness is as much art as it is science. In most cases, it is important to consider and balance a variety of factors, including:
- Strategy and stakeholders – How will the data be used and, importantly, whose burden is of interest? Burden at the societal/payer level is generally focused on financial burden, whereas the burden to an individual patient (or caregiver) is likely to be more related to symptoms, functional limitations, and quality of life. What data are of interest, and how can they be optimally captured? What level of precision is desired? What are the expectations of the stakeholders who have an interest in this information?
- Timing – How quickly will the data be needed? Over what time frame should burden be assessed? What downstream outcomes are relevant, and how should they be incorporated?
- Population – How accurately can patients in the disease category of interest be identified? Is there an overlap with other diseases/conditions?
- Data sources – Will administrative databases be adequate for providing the full picture? Are there other studies (e.g., clinical trials, registries) being undertaken that can serve as the foundation for understanding burden of illness? For example, would capturing additional data from the control arm of a clinical trial be sufficient or add insight?
What Data Are Obtainable?
Analyzable demographic, clinical, and economic data may be obtained in a particularly efficient manner through the increasing availability of longitudinal real-world datasets (e.g., data aggregated through electronic medical records or other sources). The primary advantages of retrospective data-mining are more rapid and less costly acquisition of data relative to primary (prospective) data collection. In addition to issues with data integrity and quality, a key disadvantage is the lack of humanistic data (i.e., what matters most to patients). And in view of the regulatory spotlight increasingly (and appropriately) shining on patient-focused drug development, this imposes a serious limitation to retrospective data (electronic or otherwise).
Accordingly, there remains an important place for prospectively obtained burden-of-illness data. Albeit more costly and time-consuming, an operationally efficient prospective (observational) study can be the best mechanism for simultaneously compiling high-quality clinical, economic, and patient-centric data as a critical asset that can be leveraged both immediately and over time and, in many cases, used for multiple purposes (e.g., patient recruitment for clinical trials).
When is the Best Time?
A product’s ultimate success in the marketplace is dependent on the ability of its developer to establish its clinical, economic, and humanistic value in the real-world (which can only be established once a product is approved and used in actual medical practice). Working backward from this approval/launch timeframe, drug and device companies must have both a mechanism in place for compiling real-world data as well as a pre-approval baseline against which to compare post-approval experience. Accordingly, no later than Phase III is a good rule of thumb for initiating burden-of-illness activity; however, as the findings can truly affect the role and positioning of a product even earlier in development, it’s probably never too early to start.
Fundamentally, drug and device companies must openly embrace the burden of burden of illness!