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Published on: December 9, 2015
UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model
Jacqueline Palace1, Thomas Bregenzer, Helen Tremlett
1Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK.
Objectives:
In 2002, the UK's National Institute for Health and Care Excellence concluded that the multiple sclerosis (MS) disease modifying therapies; interferon-β and glatiramer acetate, were not cost effective over the short term but recognised that reducing disability over the longer term might dramatically improve the cost effectiveness. The UK Risk-sharing Scheme (RSS) was established to ensure cost-effective provision by prospectively collecting disability-related data from UK-treated patients with MS and comparing findings to a natural history (untreated) cohort. However, deficiencies were found in the originally selected untreated cohort and the resulting analytical approach. This study aims to identify a more suitable natural history cohort and to develop a robust analytical approach using the new cohort.
Design:
The Scientific Advisory Group, recommended the British Columbia Multiple Sclerosis (BCMS) database, Canada, as providing a more suitable natural history comparator cohort. Transition probabilities were derived and different Markov models (discrete and continuous) with and without baseline covariates were applied.
Setting:
MS clinics in Canada and the UK.
Participants:
From the BCMS database, 898 'untreated' patients with MS considered eligible for drug treatment based on the UK's Association of British Neurologists criteria.
Outcome Measure:
The predicted Expanded Disability Status Scale (EDSS) score was collected and assessed for goodness of fit when compared with actual outcome.
Results:
The BCMS untreated cohort contributed 7335 EDSS scores over a median 6.4 years (6357 EDSS 'transitions' recorded at consecutive visits) during the period 1980-1995. A continuous Markov model with 'onset age' as a binary covariate was deemed the most suitable model for future RSS analysis.
Conclusions:
A new untreated MS cohort from British Columbia has been selected and will be modelled using a continuous Markov model with onset age as a baseline covariate. This approach will now be applied to the treated UK RSS MS cohort for future price adjustment calculations.
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