OBJECTIVES: This study aims to critically analyze the development, limitations, and structures of health economic models for Multiple Sclerosis (MS), identifying the need for more comprehensive approaches in modeling to better capture the multifaceted nature of the disease.

METHODS: An exhaustive review of 163 health economic models and two overview articles was conducted, focusing on models published up to December 15, 2023. The methodology included a detailed search in PubMed and Google Scholar, supplemented with secondary sources. The analysis targeted parameters related to relapse/remission, EDSS (Expanded Disability Scale) progression, disability progression, quality of life (QoL), imaging parameters, cognitive function, fatigue, biomarkers, time to treatment continuation, and work productivity.

RESULTS: The majority of the 163 reviewed models (>90%)predominantly focused on relapse and remission, with a notable lack of incorporation of imaging parameters in long-term outcome modeling for Disease-Modifying Therapies (DMTs). The "gold standard" model from Tasman University emphasized EDSS progression, but does not take into account disability, fatigue, work productivity, health resources use during relapsing and remission cycles. Markov models emerged as the most common structure (>90%) featuring cycle lengths ranging from one month to three years. A key finding was the absence of models incorporating a holistic or multi-criteria perspective, highlighting a significant limitation in current approaches. Discretely Integrated Condition Event (DICE) simulation was suggested as an improvement compared to Markov models.

CONCLUSIONS: The review highlights the necessity for the development of MS models that are a more accurate representation of the disease. Current models predominantly focus on singular dimensions of MS, failing to encompass the complex dynamics affecting patient outcomes. The establishment of comprehensive, multi-criteria models is essential to reflect the real-world impact of DMTs more realistically on patients' lives. A paradigm shift for accurately modelling patient experience with remitting relapsing conditions is needed.