Issues, Challenges and Opportunities for Economic Evaluation in Rare Diseases

Background and objectives
Orphan drugs have surged in recent decades, but economic evaluation in rare diseases remains challenging. The main research aim set out to explore issues, challenges and opportunities for economic evaluation in rare disease.

Methods
A comprehensive umbrella review was undertaken to identify issues and challenges for economic evaluation of orphan drugs, though opportunities emerged as well. The findings were further evaluated in an early health technology assessment of multiple system atrophy (rare disease), which was disseminated as a user-friendly Shiny app. In addition, cost-effectiveness modelling using Markov and partitioned survival models was conducted to further explore opportunities and corroborate challenges.

Results
The most obvious finding to emerge from the umbrella review was the scarcity of health-economic parameters. It was, moreover, a challenge for cost-effectiveness modelling in multiple system atrophy, e.g., initially for disability scales and later for clinical progression milestones used to inform health states, where health-economic parameters became increasingly scarce. Not surprisingly, a limited quantity of economic evaluations was identified in the umbrella review. Similarly, the evidence synthesis for multiple system atrophy found no economic evaluations despite a wealth of economic evaluations for disease analogues.

Discussion
Missing health-economic parameters make model development challenging. However, the very first economic evaluation was developed in multiple system atrophy. Early modelling in an iterative modelling framework should guide data collection efforts, e.g., using comprehensive and flexible models. This is important, because timely preparation and data generation is key to address missing health-economic parameters, which cause much difficulty when constructing economic evaluations.

Conclusions
To conclude, demonstrating the value of orphan drugs in rare diseases is notoriously difficult, because of pertinent challenges such as dealing with data scarcities for health-economic parameters. Solutions are not plentiful and rarely forthcoming; however, opportunities were identified, but they need further development and refinement by future researchers.