UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model
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 mi...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2014-01-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/4/1/e004073.full |
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| author | Jacqueline Palace Martin Duddy Thomas Bregenzer Mike Boggild Joel Oger Helen Tremlett Charles Dobson Fheng Zhu |
| author_facet | Jacqueline Palace Martin Duddy Thomas Bregenzer Mike Boggild Joel Oger Helen Tremlett Charles Dobson Fheng Zhu |
| author_sort | Jacqueline Palace |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-93191531e5134004af2ac005ac16a350 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-93191531e5134004af2ac005ac16a3502025-02-11T14:45:10ZengBMJ Publishing GroupBMJ Open2044-60552014-01-014110.1136/bmjopen-2013-004073UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov modelJacqueline Palace0Martin Duddy1Thomas Bregenzer2Mike Boggild3Joel Oger4Helen Tremlett5Charles Dobson6Fheng Zhu7Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UKNeurology Department, The Newcastle upon Tyne Hospitals, Newcastle, UKBiostatistics Unit, PAREXEL International, Berlin, GermanyNeurology Department, The Townsville Hospital, Townsville, Queensland, AustraliaDivision of Neurology, University of British Columbia, Vancouver, British Columbia, Canada1 Department of Medicine (Neurology), University of British Columbia, Vancouver, Canada9 Department of Health, Leeds, UKDepartment of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, CanadaObjectives 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.https://bmjopen.bmj.com/content/4/1/e004073.full |
| spellingShingle | Jacqueline Palace Martin Duddy Thomas Bregenzer Mike Boggild Joel Oger Helen Tremlett Charles Dobson Fheng Zhu UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model BMJ Open |
| title | UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model |
| title_full | UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model |
| title_fullStr | UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model |
| title_full_unstemmed | UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model |
| title_short | UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model |
| title_sort | uk multiple sclerosis risk sharing scheme a new natural history dataset and an improved markov model |
| url | https://bmjopen.bmj.com/content/4/1/e004073.full |
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