Introduction
When generating evidence for treatments in rare diseases, manufacturers cannot change the cards they are dealt: small patient populations, and limited or no effective treatment comparators. Sometimes a traditional randomised controlled trial (RCT) does not resolve uncertainty around long-term clinical outcomes. This is where real-world data (RWD) and real-world evidence (RWE) become essential. However, the use of RWE to assess benefit for rare disease treatments often introduces new challenges, rather than resolving existing uncertainties.
The challenges of Rare disease evidence generation
Rare diseases present unique challenges for manufacturers. With small patient populations and a lack of established treatments for comparison, generating robust clinical evidence can be difficult. Traditional RCTs may not provide the necessary insights into long-term clinical outcomes. In such cases, RWD becomes crucial in helping manufacturers address uncertainty—especially when there are conditional HTA/payer recommendations in place.
This approach, known as coverage with evidence development, allows RWD to be collected within a specified time frame before reassessment¹. However, using RWE to assess the clinical benefit of rare disease treatments can often lead to further uncertainties, rather than resolving them.
The need for a robust RWE strategy
At the heart of managing this uncertainty and addressing HTA/payer concerns is the development of a strong RWE strategy. A well-structured plan not only strengthens confidence in the sources of RWD but also ensures that the methods used to generate RWE can effectively demonstrate the value of the orphan drug.
The case of Vimizim highlights the importance of this strategy. Initially recommended by NICE in 2015 under a managed access agreement (MAA) for the treatment of mucopolysaccharidosis type 4A, the recommendation came with the condition of RWD collection. After six years of data collection, NICE rejected the drug in 2021 due to missing and insufficient RWD. The company’s failure to adequately analyse the data, combined with concerns over high levels of missing information and inadequate propensity score matching, delayed patient access by seven years.
The cost of insufficient RWE
The Vimizim case illustrates the risks of not having a robust RWE strategy in place. While the drug was eventually recommended by NICE, the committee expressed disappointment with the company’s insufficient data analysis, noting the burden placed on healthcare staff, patients, and their families. The delays in providing necessary evidence had direct consequences on patient access.
Expanding the RWE conversation to precision medicines
Rare diseases are often associated with traditional orphan drug designations, but precision medicines targeting smaller subpopulations of common chronic diseases face similar challenges². For example, NICE rejected Rybrevant (a treatment for advanced non-small cell lung cancer with EGFR 20ins mutation) due to uncertainties around the comparative clinical benefit, even though this is a rare disease affecting only 0.4% of advanced NSCLC patients³.
The committee’s concerns were largely rooted in how the RWE was chosen and presented, particularly for the blended comparator arm. This shows that regardless of orphan drug designation, the same RWE-related uncertainties can arise, making it imperative to design and implement rigorous data collection and analysis strategies.
Mitigating bias and improving RWE outcomes
When RWE studies aim to demonstrate clinical benefit, HTA bodies and payers must carefully assess biases such as residual confounding, selection bias, and information bias. These biases are often linked to how the RWE study is designed and how the data is collected. To alleviate these concerns, manufacturers can focus on the following:
- Developing a comprehensive data landscape early in the drug’s development
- Conducting evidence gap analyses to identify and address weaknesses in the data
- Seeking early scientific advice on evidence generation plans to pressure test the strategy before engaging with HTA bodies
Conclusion
A robust Real-World Evidence strategy is essential to ensure that orphan drugs and treatments for rare diseases can successfully navigate the uncertainties in the HTA and payer landscape. Manufacturers must prioritise evidence generation, refine their data collection methods, and plan ahead to avoid the pitfalls experienced by treatments like Vimizim and Rybrevant.
For more information on the challenges orphan drugs face at HTA, visit our “Strategic approaches to achieving HTA approval for Orphan Drugs” article.
Discover more insights on rare diseases here.
Sources:
- Dayer, V. W. et al. Real-world evidence for coverage determination of treatments for rare diseases. Orphanet J. Rare Dis. 19, 47 (2024).
- Mueller, C. M., Rao, G. R. & Miller Needleman, K. I. Precision Medicines’ Impact on Orphan Drug Designation. Clin. Transl. Sci. 12, 633–640 (2019).
- Chouaid, C. et al. EGFR Exon 20 insertion: Prognostic and predictive values in advanced non-small cell lung cancer, a real-world study. J. Clin. Oncol. 39, 9062–9062 (2021).