OBJECTIVES: Fabry disease (FD) is a rare X-linked inherited multisystem disorder, caused by a deficiency of a lysosomal enzyme which can lead to progressive accumulation of glycolipids in different cells and multi-organ dysfunction over time. There are different health economic (HE) models that can be considered to simulate the clinical pathway in FD. However, including early-onset symptoms in addition to different late-onset complications of FD in HE models is a major challenge. Moreover, the availability of long-term data in FD is very limited. The present study investigates appropriate HE model approaches to capture the real-world clinical pathway in FD.

METHODS: A targeted literature search of published HE models in FD was conducted and the related modeling data from all available publications were extracted. Different features, limitations, and benefits of models were evaluated.

RESULTS: Eight studies met the inclusion criteria, consisting of two cost-minimization analyses, two budget impact analyses, one cost–consequence analysis, and three cost-effectiveness analyses. Among cost-minimization/consequence/effectiveness analyses, four reported the model type. Markov (100%) was the most common HE-model type, whereas microsimulation, decision tree, and partition survival models were not used in studies.

CONCLUSIONS: Regarding the progression of FD symptoms over time, microsimulation models are an attractive option; however, the lack of proper data for this type of model is a substantial challenge and may explain why no study used this model type to simulate the clinical pathway in FD. Partition survival models are limited in their ability to include multiple health states in FD, including renal disease, cardiovascular disease, cerebrovascular disease, gastrointestinal complications, and pain. In conclusion, the Markov model with or without a decision tree is the most appropriate HE simulation that can handle challenges such as early-/late-onset complications, lack of data in rare disease, and multiple health states in FD.