Edward J D Webb1, David Meads2, Ieva Eskyte3, Natalie King2, Naila Dracup2, Jeremy Chataway4, Helen L Ford5, Joachim Marti6, Sue H Pavitt7, Klaus Schmierer8,9, Ana Manzano10. 1. Leeds Institute for Health Sciences, University of Leeds, Leeds, UK. e.j.d.webb@leeds.ac.uk. 2. Leeds Institute for Health Sciences, University of Leeds, Leeds, UK. 3. School of Dentistry, University of Leeds, Leeds, UK. 4. Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, UK. 5. Leeds Teaching Hospitals NHS Trust, Leeds, UK. 6. Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois, Université de Lausanne, Lausanne, Switzerland. 7. Dental Translational and Clinical Research Unit, School of Dentistry, University of Leeds, Leeds, UK. 8. Blizard Institute (Neuroscience) Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. 9. Clinical Board Medicine (Neuroscience), The Royal London Hospital, Barts Health NHS Trust, London, UK. 10. School of Sociology and Social Policy, University of Leeds, Leeds, UK.
Abstract
BACKGROUND: Multiple sclerosis (MS) is a chronic disabling, inflammatory, and degenerative disease of the central nervous system that, in most cases, requires long-term disease-modifying treatment (DMT). The drugs used vary in efficacy and adverse effect profiles. Several studies have used attribute-based stated-preference methods, primarily to investigate patient preferences for initiating or escalating DMT. OBJECTIVES: To conduct a systematic review of attribute-based stated-preference studies in people with MS to identify common methods employed and to assess study quality, with reference to the specific challenges of this disease area. METHODS: We conducted a systematic search for studies related to attribute-based stated-preference and MS in multiple databases, including Cochrane and MEDLINE. Studies were included if they were published in a peer-reviewed journal, were on the topic of MS, and used a survey methodology that measured stated preferences for attributes of a whole. Analysis was conducted using narrative synthesis and summary statistics. Study quality was judged against the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) conjoint analysis checklist. RESULTS: We identified 16 relevant articles reporting 17 separate studies, all but one focusing on DMTs. Most studies were discrete-choice experiments. Study quality was generally high, but we recommend the following: (1) that consideration of sample sizes be improved, (2) that survey design choices be justified and documented, (3) that qualitative approaches for attribute and level selection be incorporated to better involve patients, and (4) that reporting of experimental practice be improved. The effects of DMTs on reproduction and the impact of how risk and uncertainty are presented were identified as neglected research topics. The ISPOR conjoint analysis checklist was found to be unsuitable for the assessment of study quality. CONCLUSION: Attribute-based stated preference is a useful method with which to examine the preferences of people with MS in their choice of DMT. However, further research embracing the methodological recommendations identified, particularly greater use of qualitative methods in attribute development, is needed.
BACKGROUND:Multiple sclerosis (MS) is a chronic disabling, inflammatory, and degenerative disease of the central nervous system that, in most cases, requires long-term disease-modifying treatment (DMT). The drugs used vary in efficacy and adverse effect profiles. Several studies have used attribute-based stated-preference methods, primarily to investigate patient preferences for initiating or escalating DMT. OBJECTIVES: To conduct a systematic review of attribute-based stated-preference studies in people with MS to identify common methods employed and to assess study quality, with reference to the specific challenges of this disease area. METHODS: We conducted a systematic search for studies related to attribute-based stated-preference and MS in multiple databases, including Cochrane and MEDLINE. Studies were included if they were published in a peer-reviewed journal, were on the topic of MS, and used a survey methodology that measured stated preferences for attributes of a whole. Analysis was conducted using narrative synthesis and summary statistics. Study quality was judged against the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) conjoint analysis checklist. RESULTS: We identified 16 relevant articles reporting 17 separate studies, all but one focusing on DMTs. Most studies were discrete-choice experiments. Study quality was generally high, but we recommend the following: (1) that consideration of sample sizes be improved, (2) that survey design choices be justified and documented, (3) that qualitative approaches for attribute and level selection be incorporated to better involve patients, and (4) that reporting of experimental practice be improved. The effects of DMTs on reproduction and the impact of how risk and uncertainty are presented were identified as neglected research topics. The ISPOR conjoint analysis checklist was found to be unsuitable for the assessment of study quality. CONCLUSION: Attribute-based stated preference is a useful method with which to examine the preferences of people with MS in their choice of DMT. However, further research embracing the methodological recommendations identified, particularly greater use of qualitative methods in attribute development, is needed.
Authors: Deborah Marshall; John F P Bridges; Brett Hauber; Ruthanne Cameron; Lauren Donnalley; Ken Fyie; F Reed Johnson Journal: Patient Date: 2010-12-01 Impact factor: 3.883
Authors: Gavin Giovannoni; Jeffrey A Cohen; Alasdair J Coles; Hans-Peter Hartung; Eva Havrdova; Krzysztof W Selmaj; David H Margolin; Stephen L Lake; Susan M Kaup; Michael A Panzara; D Alastair S Compston Journal: Neurology Date: 2016-10-12 Impact factor: 9.910
Authors: Kei Long Cheung; Ben F M Wijnen; Ilene L Hollin; Ellen M Janssen; John F Bridges; Silvia M A A Evers; Mickael Hiligsmann Journal: Pharmacoeconomics Date: 2016-12 Impact factor: 4.981
Authors: Edward J D Webb; David Meads; Ieva Eskytė; Helen L Ford; Hilary L Bekker; Jeremy Chataway; George Pepper; Joachim Marti; Yasmina Okan; Sue H Pavitt; Klaus Schmierer; Ana Manzano Journal: Patient Date: 2020-10 Impact factor: 3.883
Authors: Larry D Lynd; Natalie J Henrich; Celestin Hategeka; Carlo A Marra; Nicole Mittmann; Charity Evans; Anthony L Traboulsee Journal: Int J MS Care Date: 2018 Nov-Dec
Authors: Elisabeth G Celius; Heidi Thompson; Maija Pontaga; Dawn Langdon; Alice Laroni; Stanca Potra; Trishna Bharadia; David Yeandle; Jane Shanahan; Pieter van Galen; Nektaria Alexandri; Jürg Kesselring Journal: Patient Prefer Adherence Date: 2021-01-08 Impact factor: 2.711