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Updated: Apr 17, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Updated Health Economics Simulation Model of the Lifetime Progression of Multiple Sclerosis in an Australian Setting
Andrew J Palmer1,2, Ting Zhao3, Glen Henson3
1Medical Sciences Precinct, Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, Tasmania, 7000, Australia. Andrew.palmer@utas.edu.au.
Background:
Multiple sclerosis (MS) is a progressive disease leading to increasing disability. Our previous simulation model estimated lifetime impacts of MS on quality of life and associated economic costs but was limited by small cohort input data and simplistic structure.
Objective:
The aim was to improve our previous model by incorporating more granular disease states, improving the accuracy of input data using a large MS cohort, and including contemporary cost and health state utility (HSU) inputs, matching the more detailed health states.
Methods:
A Markov model was developed simulating MS progression from no disability to mild, moderate, and severe disability and death under contemporary treatment patterns. State-specific probabilities of progression, death, relapse, costs, HSUs, and relapse-related disutilities were considered. Life expectancy (LE), quality-adjusted life years (QALYs), and discounted lifetime total costs (2026 Australian dollars) were calculated. Probabilistic sensitivity analysis was performed.
Results:
A typical MS cohort of 35-year-old females had a projected mean LE of 44.0 years, 27.3 and 11.3 undiscounted/discounted QALYs, respectively, and lifetime costs of $1,449,597. Compared with the Australian general population, those with MS had 6.8 years lower LE, 15.0 lower undiscounted QALYs, and $1.24 million higher costs. Our updated model showed higher LE and costs but lower QALYs compared with our previous model, due to differences in probability utilities and cost inputs.
Conclusions:
Our improved model, based on a larger cohort and updated inputs, provides a more nuanced assessment of the impact of MS on LE, QALYs, and costs, with improved face validity. It will be used for the cost-effectiveness analyses of current and future MS interventions.
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