OBJECTIVES: For rare diseases there may be a scarcity of health-economic evaluations and input parameters. Consequently, it may be useful to explore disease analogues for surrogate data that could potentially be used in cost-effectiveness analysis. We define disease analogues as those who display overlapping disease characteristics with a particular rare disease but have higher prevalence. Our objective was to determine the usefulness of exploring disease analogues to inform conceptual modelling and input parameters for an economic evaluation of multiple system atrophy (MSA). To our knowledge, an economic evaluation for MSA does not exist.

METHODS: Physicians specialised in neurology were consulted to establish disease analogues for MSA. They were amyotrophic lateral sclerosis, multiple sclerosis, and loss of ambulation through e.g., late-stage Parkinson’s disease or spinal cord injury. A targeted literature review in MEDLINE and EMBASE together with hand searches were conducted for economic evaluations of disease analogues.

RESULTS: The searches yielded 547 papers. 211 hits were duplicates, which left 335 papers for screening. 42, 3, 2, 1 cost-effectiveness analyses were included for multiple sclerosis, advanced Parkinson’s disease, amyotrophic lateral sclerosis, and spinal cord injury, respectively. Multiple sclerosis models were Markov models that used an expanded disability status scale to define health states (n = 30). Several of them accounted for on- and off-treatment periods or for disease progression e.g., remitting/relapsing, or secondary progression (n = 21). Markov models for advanced parkinson’s disease used Hoehn and Yahr states, a measure of clinical disability, together with on- and off-states to reflect controlled / uncontrollable motor symptoms. Amyotrophic lateral sclerosis models were Markovian. The model structure for spinal cord injury was not clear, but the study compared training strategies for practice-based cohorts.

CONCLUSIONS: Disease-analogues provided insights on model types and structures and can potentially be used for surrogate data extraction for MSA.