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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 m...

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Autores principales: Palace, Jacqueline, Bregenzer, Thomas, Tremlett, Helen, Oger, Joel, Zhu, Fheng, Boggild, Mike, Duddy, Martin, Dobson, Charles
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3902459/
https://www.ncbi.nlm.nih.gov/pubmed/24441054
http://dx.doi.org/10.1136/bmjopen-2013-004073
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author Palace, Jacqueline
Bregenzer, Thomas
Tremlett, Helen
Oger, Joel
Zhu, Fheng
Boggild, Mike
Duddy, Martin
Dobson, Charles
author_facet Palace, Jacqueline
Bregenzer, Thomas
Tremlett, Helen
Oger, Joel
Zhu, Fheng
Boggild, Mike
Duddy, Martin
Dobson, Charles
author_sort Palace, Jacqueline
collection PubMed
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.
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spelling pubmed-39024592014-01-27 UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model Palace, Jacqueline Bregenzer, Thomas Tremlett, Helen Oger, Joel Zhu, Fheng Boggild, Mike Duddy, Martin Dobson, Charles BMJ Open Neurology 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. BMJ Publishing Group 2014-01-17 /pmc/articles/PMC3902459/ /pubmed/24441054 http://dx.doi.org/10.1136/bmjopen-2013-004073 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Neurology
Palace, Jacqueline
Bregenzer, Thomas
Tremlett, Helen
Oger, Joel
Zhu, Fheng
Boggild, Mike
Duddy, Martin
Dobson, Charles
UK multiple sclerosis risk-sharing scheme: a new natural history dataset and an improved Markov model
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
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3902459/
https://www.ncbi.nlm.nih.gov/pubmed/24441054
http://dx.doi.org/10.1136/bmjopen-2013-004073
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