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Pryde SJ, Williams O, O'Hare MP, Murdock C, Pedlow K. Exploring access to community neurorehabilitation for people with progressive neurological conditions: a qualitative study. Disabil Rehabil 2024:1-14. [PMID: 38632940 DOI: 10.1080/09638288.2024.2338198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 03/28/2024] [Indexed: 04/19/2024]
Abstract
PURPOSE Community neurorehabilitation enables people with progressive neurological conditions (PNCs) to manage their symptoms to live an active, fulfilling life; however, it is not accessible to all. This study explored the factors influencing access to community neurorehabilitation in Northern Ireland from the perspective of people with PNCs and their carers. METHODS Eleven people living with a PNC and three carers took part in virtual focus groups. Data was thematically analysed using the framework method. RESULTS Access to neurorehabilitation was described as a staged journey, driven by people with PNCs, and impacted by interactions with others. Four themes were identified: the person in the driving seat, describing the value of person-centred care and the need for proactivity; the traffic lights, depicting the role and influence of health care professionals (HCPs); the need for direction; and roadworks and roadblocks, identifying additional barriers to access. In addition, six fundamentals of good access were identified. CONCLUSIONS This study adds depth to our understanding of the complexity, and the roles and needs of people with PNCs and HCPs, in accessing community neurorehabilitation. Further research is needed to determine how best to empower people to access rehabilitation.
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Affiliation(s)
- Shona J Pryde
- School of Health Sciences, Ulster University, Londonderry, UK
- Physiotherapy Department, Belfast Health and Social Care Trust, Belfast, UK
| | | | | | - Carolyn Murdock
- School of Health Sciences, Ulster University, Londonderry, UK
| | - Katy Pedlow
- School of Health Sciences, Ulster University, Londonderry, UK
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Jia Y, Qiao X, Zhao J, Li H, Hu S, Hu M. Disease Burden and Costs Associated with Multiple Sclerosis in China: A Cross-sectional Analysis of Nationwide Survey Data. Neurosci Bull 2024; 40:533-538. [PMID: 37917312 PMCID: PMC11003946 DOI: 10.1007/s12264-023-01135-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 09/23/2023] [Indexed: 11/04/2023] Open
Affiliation(s)
- Yusheng Jia
- Department of Health Economics, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Xuanqi Qiao
- Department of Health Economics, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Jin Zhao
- Department of Health Economics, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Hainan Li
- Department of Health Economics, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Shanlian Hu
- Department of Health Economics, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Min Hu
- Department of Health Economics, School of Public Health, Fudan University, Shanghai, 200032, China.
- National Health Commission Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
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3
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Spelman T, Herring WL, Acosta C, Hyde R, Jokubaitis VG, Pucci E, Lugaresi A, Laureys G, Havrdova EK, Horakova D, Izquierdo G, Eichau S, Ozakbas S, Alroughani R, Kalincik T, Duquette P, Girard M, Petersen T, Patti F, Csepany T, Granella F, Grand'Maison F, Ferraro D, Karabudak R, Jose Sa M, Trojano M, van Pesch V, Van Wijmeersch B, Cartechini E, McCombe P, Gerlach O, Spitaleri D, Rozsa C, Hodgkinson S, Bergamaschi R, Gouider R, Soysal A, Castillo-Triviño, Prevost J, Garber J, de Gans K, Ampapa R, Simo M, Sanchez-Menoyo JL, Iuliano G, Sas A, van der Walt A, John N, Gray O, Hughes S, De Luca G, Onofrj M, Buzzard K, Skibina O, Terzi M, Slee M, Solaro C, Oreja-Guevara, Ramo-Tello C, Fragoso Y, Shaygannejad V, Moore F, Rajda C, Aguera Morales E, Butzkueven H. Comparative effectiveness and cost-effectiveness of natalizumab and fingolimod in rapidly evolving severe relapsing-remitting multiple sclerosis in the United Kingdom. J Med Econ 2024; 27:109-125. [PMID: 38085684 DOI: 10.1080/13696998.2023.2293379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023]
Abstract
AIM To evaluate the real-world comparative effectiveness and the cost-effectiveness, from a UK National Health Service perspective, of natalizumab versus fingolimod in patients with rapidly evolving severe relapsing-remitting multiple sclerosis (RES-RRMS). METHODS Real-world data from the MSBase Registry were obtained for patients with RES-RRMS who were previously either naive to disease-modifying therapies or had been treated with interferon-based therapies, glatiramer acetate, dimethyl fumarate, or teriflunomide (collectively known as BRACETD). Matched cohorts were selected by 3-way multinomial propensity score matching, and the annualized relapse rate (ARR) and 6-month-confirmed disability worsening (CDW6M) and improvement (CDI6M) were compared between treatment groups. Comparative effectiveness results were used in a cost-effectiveness model comparing natalizumab and fingolimod, using an established Markov structure over a lifetime horizon with health states based on the Expanded Disability Status Scale. Additional model data sources included the UK MS Survey 2015, published literature, and publicly available sources. RESULTS In the comparative effectiveness analysis, we found a significantly lower ARR for patients starting natalizumab compared with fingolimod (rate ratio [RR] = 0.65; 95% confidence interval [CI], 0.57-0.73) or BRACETD (RR = 0.46; 95% CI, 0.42-0.53). Similarly, CDI6M was higher for patients starting natalizumab compared with fingolimod (hazard ratio [HR] = 1.25; 95% CI, 1.01-1.55) and BRACETD (HR = 1.46; 95% CI, 1.16-1.85). In patients starting fingolimod, we found a lower ARR (RR = 0.72; 95% CI, 0.65-0.80) compared with starting BRACETD, but no difference in CDI6M (HR = 1.17; 95% CI, 0.91-1.50). Differences in CDW6M were not found between the treatment groups. In the base-case cost-effectiveness analysis, natalizumab dominated fingolimod (0.302 higher quality-adjusted life-years [QALYs] and £17,141 lower predicted lifetime costs). Similar cost-effectiveness results were observed across sensitivity analyses. CONCLUSIONS This MSBase Registry analysis suggests that natalizumab improves clinical outcomes when compared with fingolimod, which translates to higher QALYs and lower costs in UK patients with RES-RRMS.
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Affiliation(s)
- T Spelman
- MSBase Foundation, Melbourne, VIC, Australia
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - W L Herring
- Health Economics, RTI Health Solutions, NC, USA
- Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - C Acosta
- Value and Access, Biogen, Baar, Switzerland
| | - R Hyde
- Medical, Biogen, Baar, Switzerland
| | - V G Jokubaitis
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - E Pucci
- Neurology Unit, AST-Fermo, Fermo, Italy
| | - A Lugaresi
- Dipartamento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - G Laureys
- Department of Neurology, University Hospital Ghent, Ghent, Belgium
| | - E K Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - D Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - G Izquierdo
- Department of Neurology, Hospital Universitario Virgen Macarena, Seville, Spain
| | - S Eichau
- Department of Neurology, Hospital Universitario Virgen Macarena, Seville, Spain
| | - S Ozakbas
- Izmir University of Economics, Medical Point Hospital, Izmir, Turkey
| | - R Alroughani
- Division of Neurology, Department of Medicine, Amiri Hospital, Sharq, Kuwait
| | - T Kalincik
- Neuroimmunology Centre, Department of Neurology, Royal Melbourne Hospital, Melbourne, Australia
- CORe, Department of Medicine, University of Melbourne, Melbourne, Australia
| | - P Duquette
- CHUM and Universite de Montreal, Montreal, Canada
| | - M Girard
- CHUM and Universite de Montreal, Montreal, Canada
| | - T Petersen
- Aarhus University Hospital, Arhus C, Denmark
| | - F Patti
- Department of Medical and Surgical Sciences and Advanced Technologies, GF Ingrassia, Catania, Italy
- UOS Sclerosi Multipla, AOU Policlinico "G Rodloico-San Marco", University of Catania, Italy
| | - T Csepany
- Department of Neurology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - F Granella
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Department of General Medicine, Parma University Hospital, Parma, Italy
| | | | - D Ferraro
- Department of Neuroscience, Azienda Ospedaliera Universitaria, Modena, Italy
| | | | - M Jose Sa
- Department of Neurology, Centro Hospitalar Universitario de Sao Joao, Porto, Portugal
- Faculty of Health Sciences, University Fernando Pessoa, Porto, Portugal
| | - M Trojano
- School of Medicine, University of Bari, Bari, Italy
| | - V van Pesch
- Cliniques Universitaires Saint-Luc, Brussels, Belgium
- Université Catholique de Louvain, Belgium
| | - B Van Wijmeersch
- University MS Centre, Hasselt-Pelt and Noorderhart Rehabilitation & MS, Pelt and Hasselt University, Hasselt, Belgium
| | | | - P McCombe
- University of Queensland, Brisbane, Australia
- Royal Brisbane and Women's Hospital, Herston, Australia
| | - O Gerlach
- Academic MS Center Zuyd, Department of Neurology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - D Spitaleri
- Azienda Ospedaliera di Rilievo Nazionale San Giuseppe Moscati Avellino, Avellino, Italy
| | - C Rozsa
- Jahn Ferenc Teaching Hospital, Budapest, Hungary
| | - S Hodgkinson
- Immune Tolerance Laboratory Ingham Institute and Department of Medicine, UNSW, Sydney, Australia
| | | | - R Gouider
- Department of Neurology, LR18SP03 and Clinical Investigation Center Neurosciences and Mental Health, Razi University Hospital -, Mannouba, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
| | - A Soysal
- Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases, Istanbul, Turkey
| | - Castillo-Triviño
- Hospital Universitario Donostia and IIS Biodonostia, San Sebastián, Spain
| | - J Prevost
- CSSS Saint-Jérôme, Saint-Jerome, Canada
| | - J Garber
- Westmead Hospital, Sydney, Australia
| | - K de Gans
- Groene Hart Ziekenhuis, Gouda, Netherlands
| | - R Ampapa
- Nemocnice Jihlava, Jihlava, Czech Republic
| | - M Simo
- Department of Neurology, Semmelweis University Budapest, Budapest, Hungary
| | - J L Sanchez-Menoyo
- Department of Neurology, Galdakao-Usansolo University Hospital, Osakidetza Basque Health Service, Galdakao, Spain
- Biocruces-Bizkaia Health Research Institute, Spain
| | - G Iuliano
- Ospedali Riuniti di Salerno, Salerno, Italy
| | - A Sas
- Department of Neurology and Stroke, BAZ County Hospital, Miskolc, Hungary
| | - A van der Walt
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, The Alfred Hospital, Melbourne, Australia
| | - N John
- Monash University, Clayton, Australia
- Department of Neurology, Monash Health, Clayton, Australia
| | - O Gray
- South Eastern HSC Trust, Belfast, United Kingdom
| | - S Hughes
- Royal Victoria Hospital, Belfast, United Kingdom
| | - G De Luca
- MS Centre, Neurology Unit, "SS. Annunziata" University Hospital, University "G. d'Annunzio", Chieti, Italy
| | - M Onofrj
- Department of Neuroscience, Imaging, and Clinical Sciences, University G. d'Annunzio, Chieti, Italy
| | - K Buzzard
- Department of Neurosciences, Box Hill Hospital, Melbourne, Australia
- Monash University, Melbourne, Australia
- MS Centre, Royal Melbourne Hospital, Melbourne, Australia
| | - O Skibina
- Department of Neurology, The Alfred Hospital, Melbourne, Australia
- Monash University, Melbourne, Australia
- Department of Neurology, Box Hill Hospital, Melbourne, Australia
| | - M Terzi
- Medical Faculty, 19 Mayis University, Samsun, Turkey
| | - M Slee
- Flinders University, Adelaide, Australia
| | - C Solaro
- Department of Neurology, ASL3 Genovese, Genova, Italy
- Department of Rehabilitation, ML Novarese Hospital Moncrivello
| | - Oreja-Guevara
- Department of Neurology, Hospital Clinico San Carlos, Madrid, Spain
| | - C Ramo-Tello
- Department of Neuroscience, Hospital Germans Trias i Pujol, Badalona, Spain
| | - Y Fragoso
- Universidade Metropolitana de Santos, Santos, Brazil
| | | | - F Moore
- Department of Neurology, McGill University, Montreal, Canada
| | - C Rajda
- Department of Neurology, University of Szeged, Szeged, Hungary
| | - E Aguera Morales
- Department of Medicine and Surgery, University of Cordoba, Cordoba, Spain
- Maimonides Biomedical Research Institute of Cordoba (IMIBIC)
| | - H Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
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Heather A, Goodwin E, Green C, Morrish N, Ukoumunne OC, Middleton RM, Hawton A. Multiple sclerosis health-related quality of life utility values from the UK MS register. Mult Scler J Exp Transl Clin 2023; 9:20552173231178441. [PMID: 37324245 PMCID: PMC10265354 DOI: 10.1177/20552173231178441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 05/11/2023] [Indexed: 06/17/2023] Open
Abstract
Background New interventions for multiple sclerosis (MS) commonly require a demonstration of cost-effectiveness using health-related quality of life (HRQoL) utility values. The EQ-5D is the utility measure approved for use in the UK NHS funding decision-making. There are also MS-specific utility measures - e.g., MS Impact Scale Eight Dimensions (MSIS-8D) and MSIS-8D-Patient (MSIS-8D-P). Objectives Provide EQ-5D, MSIS-8D and MSIS-8D-P utility values from a large UK MS cohort and investigate their association with demographic/clinical characteristics. Methods UK MS Register data from 14,385 respondents (2011 to 2019) were analysed descriptively and using multivariable linear regression, with self-report Expanded Disability Status Scale (EDSS) scores. Results The EQ-5D and MSIS-8D were both sensitive to differences in demographic/clinical characteristics. An inconsistency found in previous studies whereby mean EQ-5D values were higher for an EDSS score of 4 rather than 3 was not observed. Similar utility values were observed between MS types at each EDSS score. Regression showed EDSS score and age were associated with utility values from all three measures. Conclusions This study provides generic and MS-specific utility values for a large UK MS sample, with the potential for use in cost-effectiveness analyses of treatments for MS.
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Affiliation(s)
- A Heather
- PenCHORD (The Peninsula Collaboration for Health Operational Research and Data Science), Department of Health and Community Sciences, University of Exeter, Exeter, UK
| | - E Goodwin
- Health Economics Group, Department of Health and Community Sciences, University of Exeter,
Exeter, UK
| | - C Green
- Health Economics Group, Department of Health and Community Sciences, University of Exeter,
Exeter, UK
- Department for Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Solna, Sweden
- Biogen UK & Ireland, Berkshire, UK
| | - N Morrish
- Health Economics Group, Department of Health and Community Sciences, University of Exeter,
Exeter, UK
| | - OC Ukoumunne
- NIHR Applied Research Collaboration South West Peninsula, Department of Health and Community Sciences, University of Exeter, Exeter, UK
| | | | - A Hawton
- Health Economics Group, Department of Health and Community Sciences, University of Exeter,
Exeter, UK
- NIHR Applied Research Collaboration South West Peninsula, Department of Health and Community Sciences, University of Exeter, Exeter, UK
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Pipek LZ, Mahler JV, Nascimento RFV, Apóstolos-Pereira SL, Silva GD, Callegaro D. Cost, efficacy, and safety comparison between early intensive and escalating strategies for multiple sclerosis: A systematic review and meta-analysis. Mult Scler Relat Disord 2023; 71:104581. [PMID: 36848839 DOI: 10.1016/j.msard.2023.104581] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/07/2023] [Accepted: 02/14/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND The optimal treatment strategy of multiple sclerosis (MS) is a matter of debate. The classical approach is the escalating (ESC) strategy, which consists of starting with low- to moderate-efficacy disease-modifying drugs (DMDs) and upscale to high-efficacy DMDs when noting some evidence of active disease. Another approach, the early intensive (EIT) strategy, is starting with high-efficiency DMDs as first-line therapy. Our goal was to compare effectiveness, safety, and cost of ESC and EIT strategies. METHODS We searched MEDLINE, EMBASE and SCOPUS until September 2022, for studies comparing EIT and ESC strategies in adult participants with relapsing-remitting MS and a minimum follow-up of 5 years. We examined the Expanded Disability Severity Scale (EDSS), the proportion of severe adverse events, and cost in a 5-year period. Random-effects meta-analysis summarized the efficacy and safety and an EDSS-based Markov model estimated the cost. RESULTS Seven studies with 3,467 participants showed a 30% reduction in EDSS worsening in 5 years (RR 0.7; [0.59-0.83]; p < 0.001) in the EIT group vs in the ESC group. Two studies with 1,118 participants suggested a similar safety profile for these strategies (RR 1.92; [0.38-9.72]; p = 0.4324). EIT with natalizumab in extended interval dosing, rituximab, alemtuzumab, and cladribine demonstrated cost-effectiveness in our model. DISCUSSION EIT presents higher efficacy in preventing disability progression, a similar safety profile, and can be cost-effective within a 5-year timeline.
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Affiliation(s)
- Leonardo Zumerkorn Pipek
- Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, SP, BR, Av. Dr. Arnaldo, 455 - Cerqueira César, São Paulo, SP 01246-903, Brazil.
| | - João Vitor Mahler
- Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, SP, BR, Av. Dr. Arnaldo, 455 - Cerqueira César, São Paulo, SP 01246-903, Brazil
| | | | | | - Guilherme Diogo Silva
- Department of Neurology Hospital of Clinics, University of São Paulo, São Paulo, Brazil
| | - Dagoberto Callegaro
- Department of Neurology Hospital of Clinics, University of São Paulo, São Paulo, Brazil
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Vudumula U, Patidar M, Gudala K, Karpf E, Adlard N. Evaluating the impact of early vs delayed ofatumumab initiation and estimating the long-term outcomes of ofatumumab vs teriflunomide in relapsing multiple sclerosis patients in Spain. J Med Econ 2023; 26:11-18. [PMID: 36472139 DOI: 10.1080/13696998.2022.2151270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVES To evaluate the impact of early (at first-line) vs delayed (3-year delay) ofatumumab initiation and long-term clinical, societal, and economic outcomes of ofatumumab vs teriflunomide in relapsing multiple sclerosis (RMS) patients from a Spanish societal perspective. METHODS A cost-consequence analysis was conducted using an Expanded Disability Status Scale (EDSS)-based Markov model. Inputs were sourced from ASCLEPIOS I and II trials and published literature. RESULTS At the end of 10 years, compared with first-line teriflunomide treatment, early first-line ofatumumab initiation was projected to result in 35.6% fewer patients progressing to EDSS ≥ 7 and 27.8% fewer relapses. The ofatumumab cohort required 7.3% reduced informal care time and had 19% fewer disability-adjusted life years (DALYs) than the teriflunomide cohort. A 3-year delay in ofatumumab treatment (3-year teriflunomide + 7-year ofatumumab) was projected to result in 32.2% more patients progressing to EDSS ≥ 7, 20.2% more relapses, 5.4% increased informal care time, and 16.6% more DALYs compared with early ofatumumab initiation. Early ofatumumab initiation was associated with total annual cost savings (excluding disease-modifying-therapies' acquisition costs) of €35,328 ($34,549; conversion factor 1€= $1.02255) and €24,373 ($23,836) per patient vs teriflunomide and 3-year delayed ofatumumab initiation, respectively. CONCLUSIONS This study highlights the benefits of early initiation of high-efficacy therapy such as ofatumumab vs its delayed initiation for improving the outcomes in RMS patients (having characteristics similar to those of patients included in the ASCLEPIOS trials). Ofatumumab treatment was projected to provide improved long-term clinical, societal, and economic outcomes vs teriflunomide treatment in RMS patients from a Spanish societal perspective.
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Affiliation(s)
| | - Mausam Patidar
- Patient Access Services, Novartis Healthcare Pvt. Ltd, Hyderabad, India
| | - Kapil Gudala
- Patient Access Services, Novartis Healthcare Pvt. Ltd, Hyderabad, India
| | | | - Nicholas Adlard
- Health Economics and Outcomes Research, Novartis Pharma AG, Basel, Switzerland
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Economic burden of multiple sclerosis in Slovakia - from 2015 to 2020. BMC Health Serv Res 2022; 22:1467. [PMID: 36461018 PMCID: PMC9717442 DOI: 10.1186/s12913-022-08883-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 11/24/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is a chronic, inflammatory disease of the central nervous system, commonly diagnosed during young adulthood. The proportion of direct and indirect costs of MS vary across settings. The International Multiple Sclerosis Study, involving 1152 patients with MS from 19 countries, reported the average annual costs per patient to be €41,212, with direct medical costs of €21,093, direct non-medical costs of €2110, and €16,318 marked as indirect costs. However, there are no precise data on the economic burden of MS in Slovakia. Therefore, the main objective of this study is to assess the economic impact of MS in Slovakia by identifying and measuring the direct medical costs and indirect costs of this disease. METHODS We conducted a retrospective prevalence-based cost-of-illness analysis for MS in Slovakia sourced from the third-party payer and societal perspective. Patient co-payments and out-of-pocket expenses were not included in our study. We analysed all available costs and healthcare resources utilised in a 6-years period, from 2015 to 2020. For each year, all costs (in euro) were specified as total and the average annual cost per patient. RESULTS The estimated total economic burden of MS in Slovakia in 2020 was €57,347,523, with direct medical costs estimated to be €53,348,337 and indirect costs standing at €3,999,186. The total annual cost per patient in 2020 was €6682. Over the 6 years, the total diagnostic and treatment cost of patients with MS was estimated to be €283,974,236. With an average year-by-year increase of 5%, the total direct costs of MS had significantly grown during the examined 6 years. The total cost due to the MS-associated loss of productivity in these 6 years was €16,633,798. The average year-by-year increase of indirect costs of MS was 20%. CONCLUSIONS Our study revealed the substantial health and economic burden of MS, with the average annual cost per patient to be approximately €6,682 in 2020. We provide the first extensive assessment of the burden of MS on Slovakian patients, the healthcare system, and society. It indicates the need for a detailed analysis of the employment of patients with MS to assess disability and work performance and the development of allied health policies.
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8
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Vitturi BK, Rahmani A, Dini G, Montecucco A, Debarbieri N, Bandiera P, Battaglia MA, Manacorda T, Persechino B, Buresti G, Ponzio M, Inglese M, Durando P. Spatial and temporal distribution of the prevalence of unemployment and early retirement in people with multiple sclerosis: A systematic review with meta-analysis. PLoS One 2022; 17:e0272156. [PMID: 35901070 PMCID: PMC9333213 DOI: 10.1371/journal.pone.0272156] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 07/14/2022] [Indexed: 11/24/2022] Open
Abstract
Background We aimed to summarise the prevalence of unemployment and early retirement among people with MS and analyze data according to a spatio-temporal perspective. Methods We undertook a systematic search of PubMed/MEDLINE, Scopus, SciVerse ScienceDirect, and Web of Science. We included any peer-reviewed original article reporting the prevalence of unemployment and early retirement in the working-age population with MS. We excluded articles off-topic, with other study designs, whose study sample were unlikely to be representative of the MS population and in case of unavailability of the full text or essential information. A random-effects meta-analysis was used to measure overall prevalence estimates of unemployment and early retirement. We used meta-regression and subgroup analysis to evaluate potential moderators of prevalence estimates and the leave-one-out method for sensitivity analyses. Results Our research identified 153 studies across 29 countries encompassing 188436 subjects with MS. The pooled overall effect size for unemployment and early retirement was 35.6% (95% CI 32.8–38.4; I2 = 99.31) and 17.2% (95% CI 14.6–20.2; I2 = 99.13), respectively. The prevalence of unemployment varied according to the year of publication (p < 0.001) and there was a statistically significant decrease in the prevalence of unemployment over time (p = 0.042). Regarding early retirement, only seven (31.8%) estimates obtained from studies that were published before 2010 were below the overall effect size in comparison to 27 (60.0%) estimates extracted from data published between 2010 and 2021 (p = 0.039). There was a significant difference in prevalence according to countries (p < 0.001). Psychiatric illness was an important clinical feature responsible for patients leaving the workforce in regions with a high MS prevalence. Conclusions Unemployment and early retirement due to MS remain highly prevalent, despite a slight decline in the last decade. The prevalence of unemployment and early retirement varies globally.
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Affiliation(s)
| | - Alborz Rahmani
- Department of Health Sciences, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Occupational Medicine Unit, Genoa, Italy
| | - Guglielmo Dini
- Department of Health Sciences, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Occupational Medicine Unit, Genoa, Italy
| | - Alfredo Montecucco
- Department of Health Sciences, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Occupational Medicine Unit, Genoa, Italy
| | - Nicoletta Debarbieri
- IRCCS Ospedale Policlinico San Martino, Occupational Medicine Unit, Genoa, Italy
| | - Paolo Bandiera
- Italian Multiple Sclerosis Association (AISM), Genoa, Italy
| | - Mario Alberto Battaglia
- Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy
- Department of Life Science, University of Siena, Siena, Italy
| | - Tommaso Manacorda
- Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy
| | | | | | - Michela Ponzio
- Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy
| | - Matilde Inglese
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI) and Center of Excellence for Biomedical Research (CEBR), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Paolo Durando
- Department of Health Sciences, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Occupational Medicine Unit, Genoa, Italy
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9
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Wilkinson H, McGraw C, Chung K, Kyratsis Y. "Can I exercise? Would it help? Would it not?": exploring the experiences of people with relapsing remitting multiple sclerosis engaging with physical activity during a relapse: a qualitative study. Disabil Rehabil 2022:1-12. [PMID: 35727957 DOI: 10.1080/09638288.2022.2084774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
PURPOSE Physical activity (PA) has been found to be beneficial for people with multiple sclerosis (pwMS) outside of the relapse period. However, little is known about how people experience PA during a relapse. This study investigates the experiences of pwMS engaging with PA during a relapse. MATERIALS AND METHODS The study followed an interpretivist approach, adopting a qualitative exploratory design. Semi-structured interviews were conducted with a purposive sample of 15 adults following a recent relapse. Transcripts were analysed in NVivo using framework analysis. RESULTS The experiences of participants were synthesised in three overarching themes: "on the road to recovery", "getting active but fearing repercussions", and "self-directed versus guided recovery". Barriers to PA included: feeling unwell, physical limitations, concerns about causing deterioration, worries that others would recognise their disability, and lack of professional support. Facilitators included: awareness of the benefits of PA, access to exercise resources, individualised advice and support from practitioners, and PA pitched at the right level. CONCLUSIONS Relapses can disrupt normal PA routines, making it challenging to return to PA. This article makes recommendations for supporting people to undertake PA, the timing and form of support, along with suggestions for further research exploring the safety of PA during a relapse. Implications for rehabilitationPeople with RRMS find it difficult to be physically active during a relapse.There are complex personal, social and environmental reasons why people find it hard to engage with physical activity (PA).Improved timely advice and customised support during a relapse can help reduce fears and enhance confidence with returning to PA.Physical activity recommendations should be tailored to individual's abilities to make them achievable, giving a sense of accomplishment and boosting motivation.
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Affiliation(s)
- Holly Wilkinson
- The National Hospital for Neurology and Neurosurgery, London, UK.,School of Health Sciences, City, University of London, London, UK
| | - Caroline McGraw
- School of Health Sciences, City, University of London, London, UK
| | - Karen Chung
- The National Hospital for Neurology and Neurosurgery, London, UK
| | - Yiannis Kyratsis
- Department of Organization Science, Faculty of Social Sciences, VU Amsterdam, Amsterdam, The Netherlands
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10
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Li V, Leurent B, Barkhof F, Braisher M, Cafferty F, Ciccarelli O, Eshaghi A, Gray E, Nicholas JM, Parmar M, Peryer G, Robertson J, Stallard N, Wason J, Chataway J. Designing Multi-arm Multistage Adaptive Trials for Neuroprotection in Progressive Multiple Sclerosis. Neurology 2022; 98:754-764. [PMID: 35321926 PMCID: PMC9109150 DOI: 10.1212/wnl.0000000000200604] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 03/10/2022] [Indexed: 11/24/2022] Open
Abstract
There are few treatments shown to slow disability progression in progressive multiple sclerosis (PMS). One challenge has been efficiently testing the pipeline of candidate therapies from preclinical studies in clinical trials. Multi-arm multistage (MAMS) platform trials may accelerate evaluation of new therapies compared to traditional sequential clinical trials. We describe a MAMS design in PMS focusing on selection of interim and final outcome measures, sample size, and statistical considerations. The UK MS Society Expert Consortium for Progression in MS Clinical Trials reviewed recent phase II and III PMS trials to inform interim and final outcome selection and design measures. Simulations were performed to evaluate trial operating characteristics under different treatment effect, recruitment rate, and sample size assumptions. People with MS formed a patient and public involvement group and contributed to the trial design, ensuring it would meet the needs of the MS community. The proposed design evaluates 3 experimental arms compared to a common standard of care arm in 2 stages. Stage 1 (interim) outcome will be whole brain atrophy on MRI at 18 months, assessed for 123 participants per arm. Treatments with sufficient evidence for slowing brain atrophy will continue to the second stage. The stage 2 (final) outcome will be time to 6-month confirmed disability progression, based on a composite clinical score comprising the Expanded Disability Status Scale, Timed 25-Foot Walk test, and 9-Hole Peg Test. To detect a hazard ratio of 0.75 for this primary final outcome with 90% power, 600 participants per arm are required. Assuming one treatment progresses to stage 2, the trial will recruit ≈1,900 participants and last ≈6 years. This is approximately two-thirds the size and half the time of separate 2-arm phase II and III trials. The proposed MAMS trial design will substantially reduce duration and sample size compared to traditional clinical trials, accelerating discovery of effective treatments for PMS. The design was well-received by people with multiple sclerosis. The practical and statistical principles of MAMS trial design may be applicable to other neurodegenerative conditions to facilitate efficient testing of new therapies.
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Affiliation(s)
- Vivien Li
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Baptiste Leurent
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Frederik Barkhof
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Marie Braisher
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Fay Cafferty
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Olga Ciccarelli
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Arman Eshaghi
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Emma Gray
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jennifer M Nicholas
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Mahesh Parmar
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Guy Peryer
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jenny Robertson
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Nigel Stallard
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - James Wason
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
| | - Jeremy Chataway
- From the Florey Institute of Neuroscience and Mental Health (V.L.), University of Melbourne; Department of Neurology (V.L.), Royal Melbourne Hospital, Australia; Department of Medical Statistics (B.L., J.M.N.) and International Statistics and Epidemiology Group (B.L.), London School of Hygiene and Tropical Medicine, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam (F.B.), VU University Medical Center, Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre (M.B., O.C.), and NMR Unit, Department of Neuroinflammation (A.E.), Faculty of Brain Sciences, UCL Queen Square Institute of Neurology; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology (F.C., M.P., J.C.), and Department of Computer Science, Centre for Medical Image Computing (A.E.), University College London; National Institute for Health Research (F.B., O.C., J.C.), University College London Hospitals Biomedical Research Centre; UK Multiple Sclerosis Society (E.G., G.P., J.R.), London; Faculty of Medicine and Health Sciences (G.P.), University of East Anglia, Norwich; Statistics and Epidemiology, Division of Health Sciences (N.S.), Warwick Medical School, University of Warwick, Coventry; and Population Health Sciences Institute (J.W.), Newcastle University, UK
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11
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Spelman T, Herring WL, Zhang Y, Tempest M, Pearson I, Freudensprung U, Acosta C, Dort T, Hyde R, Havrdova E, Horakova D, Trojano M, De Luca G, Lugaresi A, Izquierdo G, Grammond P, Duquette P, Alroughani R, Pucci E, Granella F, Lechner-Scott J, Sola P, Ferraro D, Grand'Maison F, Terzi M, Rozsa C, Boz C, Hupperts R, Van Pesch V, Oreja-Guevara C, van der Walt A, Jokubaitis VG, Kalincik T, Butzkueven H. Comparative Effectiveness and Cost-Effectiveness of Natalizumab and Fingolimod in Patients with Inadequate Response to Disease-Modifying Therapies in Relapsing-Remitting Multiple Sclerosis in the United Kingdom. PHARMACOECONOMICS 2022; 40:323-339. [PMID: 34921350 PMCID: PMC8866337 DOI: 10.1007/s40273-021-01106-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 10/12/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND Patients with highly active relapsing-remitting multiple sclerosis inadequately responding to first-line therapies (interferon-based therapies, glatiramer acetate, dimethyl fumarate, and teriflunomide, known collectively as "BRACETD") often switch to natalizumab or fingolimod. OBJECTIVE The aim was to estimate the comparative effectiveness of switching to natalizumab or fingolimod or within BRACETD using real-world data and to evaluate the cost-effectiveness of switching to natalizumab versus fingolimod using a United Kingdom (UK) third-party payer perspective. METHODS Real-world data were obtained from MSBase for patients relapsing on BRACETD in the year before switching to natalizumab or fingolimod or within BRACETD. Three-way-multinomial-propensity-score-matched cohorts were identified, and comparisons between treatment groups were conducted for annualised relapse rate (ARR) and 6-month-confirmed disability worsening (CDW6M) and improvement (CDI6M). Results were applied in a cost-effectiveness model over a lifetime horizon using a published Markov structure with health states based on the Expanded Disability Status Scale. Other model parameters were obtained from the UK MS Survey 2015, published literature, and publicly available UK sources. RESULTS The MSBase analysis found a significant reduction in ARR (rate ratio [RR] = 0.64; 95% confidence interval [CI] 0.57-0.72; p < 0.001) and an increase in CDI6M (hazard ratio [HR] = 1.67; 95% CI 1.30-2.15; p < 0.001) for switching to natalizumab compared with BRACETD. For switching to fingolimod, the reduction in ARR (RR = 0.91; 95% CI 0.81-1.03; p = 0.133) and increase in CDI6M (HR = 1.30; 95% CI 0.99-1.72; p = 0.058) compared with BRACETD were not significant. Switching to natalizumab was associated with a significant reduction in ARR (RR = 0.70; 95% CI 0.62-0.79; p < 0.001) and an increase in CDI6M (HR = 1.28; 95% CI 1.01-1.62; p = 0.040) compared to switching to fingolimod. No evidence of difference in CDW6M was found between treatment groups. Natalizumab dominated (higher quality-adjusted life-years [QALYs] and lower costs) fingolimod in the base-case cost-effectiveness analysis (0.453 higher QALYs and £20,843 lower costs per patient). Results were consistent across sensitivity analyses. CONCLUSIONS This novel real-world analysis suggests a clinical benefit for therapy escalation to natalizumab versus fingolimod based on comparative effectiveness results, translating to higher QALYs and lower costs for UK patients inadequately responding to BRACETD.
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Affiliation(s)
- Timothy Spelman
- Department of Neuroscience, Central Clinical School Alfred Hospital, Monash University, Melbourne, VIC, Australia
| | | | - Yuanhui Zhang
- RTI Health Solutions, Research Triangle Park, NC, USA
| | | | | | | | - Carlos Acosta
- Value and Market Access, Biogen International GmbH, Neuhofstrasse 30, 6340, Baar, Switzerland.
| | - Thibaut Dort
- Value and Market Access, Biogen International GmbH, Neuhofstrasse 30, 6340, Baar, Switzerland
| | | | - Eva Havrdova
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, General University Hospital and Charles University, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, General University Hospital and Charles University, Prague, Czech Republic
| | - Maria Trojano
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari, Bari, Italy
| | - Giovanna De Luca
- Multiple Sclerosis Centre, Neurology Unit, SS Annunziata Hospital, University "G. d'Annunzio", Chieti-Pescara, Italy
| | - Alessandra Lugaresi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy
| | | | - Pierre Grammond
- Centre de Réadaptation Déficience Physique Chaudière-Appalache, Lévis, Canada
| | | | | | | | | | | | - Patrizia Sola
- Azienda Ospedaliero Universitaria Policlinico/OCB, Neurology Unit, Modena, Italy
| | - Diana Ferraro
- Department of Biomedical, Metabolic and Neurosciences, University of Modena and Reggio Emilia, Modena, Italy
| | | | | | - Csilla Rozsa
- Jahn Ferenc Teaching Hospital, Budapest, Hungary
| | - Cavit Boz
- Karadeniz Technical University, Trabzon, Turkey
| | | | | | | | - Anneke van der Walt
- Department of Neuroscience, Central Clinical School Alfred Hospital, Monash University, Melbourne, VIC, Australia
| | - Vilija G Jokubaitis
- Department of Neuroscience, Central Clinical School Alfred Hospital, Monash University, Melbourne, VIC, Australia
| | - Tomas Kalincik
- CORe, Department of Medicine, University of Melbourne, Melbourne, Australia
- MS Centre, Royal Melbourne Hospital, Melbourne, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School Alfred Hospital, Monash University, Melbourne, VIC, Australia
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12
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Picariello F, Freeman J, Moss-Morris R. Defining routine fatigue care in Multiple Sclerosis in the United Kingdom: What treatments are offered and who gets them? Mult Scler J Exp Transl Clin 2022; 8:20552173211072274. [PMID: 35096412 PMCID: PMC8796089 DOI: 10.1177/20552173211072274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 12/17/2021] [Indexed: 11/17/2022] Open
Abstract
Background Fatigue is common and disabling in Multiple Sclerosis (MS). A recent meta-analytic systematic review reported 113 trials of exercise and behavioural interventions for fatigue, yet patients consistently describe fatigue being under-treated. The extent of the research-to-practice gap is yet to be documented. Objective To describe what fatigue treatments people with MS (pwMS) in the United Kingdom (UK) have been offered. Methods A cross-sectional survey of pwMS on the UK MS Register (UKMSR). Data on fatigue treatments offered were collected using an online questionnaire developed with patient input and summarised using descriptive statistics. Sociodemographic, MS-related, and psychological factors associated with treatment offered were evaluated using a logistic regression model. Results 4,367 respondents completed the survey, 90.3% reported experiencing fatigue. Of these, 30.8% reported having been offered at least one type of pharmacological/non-pharmacological treatment for fatigue. Pharmacological treatments were more commonly offered (22.4%) compared to non-pharmacological treatments (12.6%; 2.9% exercise and 5.9% behavioural therapy). In the logistic regression model, older age, working, shorter time since MS diagnosis, and lower fatigue were associated with lower odds of having been offered treatment for fatigue. Conclusion This study accentuates the extent of the unmet need for fatigue treatment in MS in the UK.
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Affiliation(s)
| | - Jennifer Freeman
- School of Health Professions, Faculty of Health, University of Plymouth, Plymouth, UK of Great Britain and Northern Ireland
| | - Rona Moss-Morris
- Health Psychology Section, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK of Great Britain and Northern Ireland
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13
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Oliva Ramirez A, Keenan A, Kalau O, Worthington E, Cohen L, Singh S. Prevalence and burden of multiple sclerosis-related fatigue: a systematic literature review. BMC Neurol 2021; 21:468. [PMID: 34856949 PMCID: PMC8638268 DOI: 10.1186/s12883-021-02396-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/03/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is a chronic, demyelinating disease of the central nervous system that results in progressive and irreversible disability. Fatigue is one of the most common MS-related symptoms and is characterized by a persistent lack of energy that impairs daily functioning. The burden of MS-related fatigue is complex and multidimensional, and to our knowledge, no systematic literature review has been conducted on this subject. The purpose of this study was to conduct a systematic literature review on the epidemiology and burden of fatigue in people with multiple sclerosis (pwMS). METHODS Systematic searches were conducted in MEDLINE, Embase, and Evidence-Based Medicine Reviews to identify relevant studies of fatigue in pwMS. English-language records published from 2010 to January 2020 that met predefined eligibility criteria were included. We initially selected studies that reported quality of life (QoL) and economic outcomes according to categories of fatigue (e.g., fatigued vs non-fatigued). Studies assessing associations between economic outcomes and fatigue as a continuous measure were later included to supplement the available data. RESULTS The search identified 8147 unique records, 54 of which met the inclusion criteria. Of these, 39 reported epidemiological outcomes, 11 reported QoL, and 9 reported economic outcomes. The supplementary screen for economic studies with fatigue as a continuous measure included an additional 20 records. Fatigue prevalence in pwMS ranged from 36.5 to 78.0%. MS-related fatigue was consistently associated with significantly lower QoL. Results on the economic impact of fatigue were heterogeneous, but most studies reported a significant association between presence or severity of fatigue and employment status, capacity to work, and sick leave. There was a gap in evidence regarding the direct costs of MS-related fatigue and the burden experienced by caregivers of pwMS. CONCLUSION Fatigue is a prevalent symptom in pwMS and is associated with considerable QoL and economic burden. There are gaps in the evidence related to the direct costs of MS-related fatigue and the burden of fatigue on caregivers. Addressing fatigue over the clinical course of the disease may improve health and economic outcomes for patients with MS.
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Affiliation(s)
| | - Alexander Keenan
- Health Economics and Market Access, Janssen Research & Development, LLC, Titusville, NJ, USA.
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Schriefer D, Haase R, Ness NH, Ziemssen T. Cost of illness in multiple sclerosis by disease characteristics - A review of reviews. Expert Rev Pharmacoecon Outcomes Res 2021; 22:177-195. [PMID: 34582300 DOI: 10.1080/14737167.2022.1987218] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Introduction: In light of the increasing number of economic burden studies and heterogeneity in methodology and reporting standards, there is a need for robust evidence synthesis on an umbrella review level.Areas covered: We performed the first review of reviews of cost-of-illness studies in multiple sclerosis. Focusing on disaggregated costs by disease characteristics (disability level, relapse, disease course), we also characterized the underlying methodological evidence base of individual (primary) studies.Expert Commentary: We identified 17 reviews encompassing 111 unique primary studies, and a high degree of overlap across reviews. Costs were substantial, rising with disability level, relapse episodes, and disease progression. Disability was the key cost driver. Compared to mild disability, total costs for moderate disability were 1.4-2.3-fold higher and 1.8-2.9-fold higher for severe disability. With escalating disability, the share of costs outside the health system (indirect costs, informal care) increasingly outweighed the share of direct medical costs. Of all 111 primary studies, 72% gathered resource use/loss data by patient self-report. Associated costs were mostly reported by disability level (75%), followed by relapse (48%) and disease course (21%). In conclusion, although heterogeneity can make in-depth comparisons of costs across studies impossible, important patterns are broadly apparent.
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Affiliation(s)
- Dirk Schriefer
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
| | - Rocco Haase
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
| | | | - Tjalf Ziemssen
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
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15
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Annual Cost Burden by Level of Relapse Severity in Patients with Multiple Sclerosis. Adv Ther 2021; 38:758-771. [PMID: 33245532 PMCID: PMC7854428 DOI: 10.1007/s12325-020-01570-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 11/11/2020] [Indexed: 12/19/2022]
Abstract
Introduction The severity of relapses varies in multiple sclerosis (MS) and may lead to a differential cost burden. This study aimed to characterize the direct healthcare costs associated with relapses in patients with MS by the level of relapse severity. Methods This retrospective analysis used claims data extracted from the MarketScan® Databases from January 1, 2013 to March 31, 2017 (study period January 1, 2012 to March 31, 2018). Adult patients with at least one diagnosis of MS and 12 months of continuous enrollment prior to the first MS diagnosis to 12 months after the index date were included. On the basis of the severity of the relapse, patients were stratified into three cohorts: severe relapse (SR), mild/moderate relapse (MMR), and no relapse (NR). All-cause and MS-related costs were analyzed during the 12-month follow-up period. Group differences were assessed using descriptive and multivariate statistical analyses. Results In total, 8775 patients with MS were analyzed: 6341 (72%) in the NR cohort, 1929 (22%) in the MMR cohort, and 505 (6%) in the SR cohort. Overall, patients were mostly female (76%), mean age was 50 years, and 25% were on a disease-modifying therapy. Mean (standard deviation [SD]) all-cause and MS-related costs among patients with a relapse were higher vs patients without a relapse (all-cause $66,489 [$56,264] vs $41,494 [$48,417]; MS-related $48,700 [$43,364] vs $24,730 [$33,821]). Among patients with a relapse, the mean (SD) all-cause costs were $87,979 [$65,991] vs $60,863 [$51,998] and MS-related costs were $69,586 ($51,187) vs $43,233 [$39,292] for patients in the SR vs MMR cohorts, respectively. A similar trend for increase in cost by relapse severity was observed in the adjusted analysis. Conclusion Total annual all-cause and MS-related costs increased with severity of the relapses. High-efficacy treatments might reduce the severity of the relapses, thereby reducing the cost of care in patients with MS.
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16
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Topcu G, Buchanan H, Aubeeluck A, Ülsever H. Informal carers' experiences of caring for someone with Multiple Sclerosis: A photovoice investigation. Br J Health Psychol 2020; 26:360-384. [PMID: 33128428 DOI: 10.1111/bjhp.12482] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 07/23/2020] [Indexed: 11/27/2022]
Abstract
OBJECTIVES This study explores the lived experiences of carers of people with Multiple Sclerosis (MS), specifically in relation to their quality of life (QoL), through the use of images and narratives, with the aim of gaining a nuanced insight into the complex nature of QoL in the MS caregiving context. DESIGN Real-time qualitative design using the photovoice method. METHODS Twelve MS carers (aged 30-73 years) took photographs of objects/places/events that represented enhancement or compromise to their QoL and composed written narratives for each photograph based on their experiences of caregiving. In total, 126 photographs and their corresponding narratives were analysed using content analysis. RESULTS Seven inter-related themes were identified. MS caregiving-related challenges, sense of loss (e.g., loss of activities), emotional impact (e.g., feeling lonely), urge to escape, and sense of anxiety over the unpredictability of MS carer role were discussed in relation to the negative experiences that compromised their QoL. The themes precious moments (e.g., time spent with loved ones or hobbies) and helpful support (e.g., family and pets) encompassed participants' positive experiences that enhanced their QoL. CONCLUSIONS Findings demonstrated the multi-faceted and complex nature of MS caregiver's QoL and highlighted that although the experiences of MS carers were mostly negative, there were also some positive aspects to caregiving, that helped enhance carers' QoL by ameliorating these negative experiences. These findings can be used to inform support programmes and enhance service provision for MS carers.
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Affiliation(s)
- Gogem Topcu
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
| | - Heather Buchanan
- Division of Rehabilitation, Ageing and Well-being, School of Medicine, University of Nottingham, Nottingham, UK
| | - Aimee Aubeeluck
- School of Health Sciences, University of Nottingham, Nottingham, UK
| | - Hatice Ülsever
- Department of Psychology, Cyprus International University, Nicosia, North Cyprus
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Das J, Sharrack B, Snowden JA. Autologous hematopoietic stem-cell transplantation in neurological disorders: current approach and future directions. Expert Rev Neurother 2020; 20:1299-1313. [PMID: 32893698 DOI: 10.1080/14737175.2020.1820325] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Autologous hematopoietic stem-cell transplantation (AHSCT) has become increasingly popular in recent years as an effective treatment of immune-mediated neurological diseases. Treatment-related mortality has significantly reduced primarily through better patient selection, optimization of transplant technique, and increased center experience. AREA COVERED Multiple sclerosis is the main indication, but people with neuromyelitis optica spectrum disorder, stiff-person spectrum disorder, chronic inflammatory demyelinating polyneuropathy, myasthenia gravis, and other immune-mediated neurological disorders also have been treated. The review herein discusses the use of AHSCT in these neurological disorders, the importance of patient selection and transplant technique optimization and future directions. EXPERT OPINION Phase II and III clinical trials have confirmed the safety and efficacy of AHSCT in multiple sclerosis and recent phase II clinical trials have also suggested its safety and efficacy in chronic inflammatory demyelinating polyneuropathy and neuromyelitis optica spectrum disorder, with the evidence in other neurological disorders limited to individual case reports, small case series, and registry data. Therefore, further randomized controlled clinical trials are required to assess its safety and efficacy in other neurological conditions. However, in rare neurological conditions, pragmatic treatment trials or registry-based studies may be more realistic options for gathering efficacy and safety data.
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Affiliation(s)
- Joyutpal Das
- Clinical Neurosciences, Manchester Academic Health Science Centre, Salford Royal NHS Foundation Trust , Salford, UK.,Cardiovascular medicine, University of Manchester , Manchester, UK.,Department of Neuroscience, NIHR Translational Neuroscience BRC, Sheffield Teaching Hospitals NHS Foundation Trust, University of Sheffield , Sheffield, UK
| | - Basil Sharrack
- Department of Neuroscience, NIHR Translational Neuroscience BRC, Sheffield Teaching Hospitals NHS Foundation Trust, University of Sheffield , Sheffield, UK
| | - John A Snowden
- Department of Hematology, Sheffield Teaching Hospitals NHS Foundation Trust , Sheffield, UK
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18
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The increasing economic burden of multiple sclerosis by disability severity in Australia in 2017: Results from updated and detailed data on types of costs. Mult Scler Relat Disord 2020; 44:102247. [DOI: 10.1016/j.msard.2020.102247] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 05/08/2020] [Accepted: 05/27/2020] [Indexed: 11/19/2022]
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Paz-Zulueta M, Parás-Bravo P, Cantarero-Prieto D, Blázquez-Fernández C, Oterino-Durán A. A literature review of cost-of-illness studies on the economic burden of multiple sclerosis. Mult Scler Relat Disord 2020; 43:102162. [DOI: 10.1016/j.msard.2020.102162] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 02/04/2020] [Accepted: 04/26/2020] [Indexed: 11/16/2022]
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Müller S, Heidler T, Fuchs A, Pfaff A, Ernst K, Ladinek G, Wilke T. Real-World Treatment of Patients with Multiple Sclerosis per MS Subtype and Associated Healthcare Resource Use: An Analysis Based on 13,333 Patients in Germany. Neurol Ther 2020; 9:67-83. [PMID: 31832974 PMCID: PMC7229080 DOI: 10.1007/s40120-019-00172-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Indexed: 01/26/2023] Open
Abstract
INTRODUCTION The aim of this study was to describe the real-word treatment and associated healthcare resource use (HCRU) of multiple sclerosis (MS) patients, as stratified by different MS subtypes. METHODS All patients with MS continuously insured by two German statutory healthcare insurance funds from 2011 to 2015 were enrolled. These patients were categorized into four subgroups according to their MS type as follows: clinically isolated syndrome (CIS); relapsing remittent MS (RRMS); primary progressive MS (PPMS); and secondary progressive MS (SPMS). Sociodemographic characteristics, treatments, and HCRU for 2015 were analyzed. Treatment cascades for treatment-naïve patients were also determined. RESULTS A total of 13,333 patients with MS were identified. The largest proportion of patients had RRMS (41.9%), followed by PPMS (17.1%). Mean age of the enrolled patients was 50.2 years, and 70.7% were female. Among all patients, 38.3% of those with CIS, 22.4% with PPMS, 69.6% with RRMS, and 33.9% with SPMS received a prescription of a disease-modifying immunomodulatory agent, with interferon beta-1a being the most frequently prescribed agent. Likewise, 14.5, 18.5, 19.9, and 21.5% of patients with CIS, PPMS, RRMS, and SPMS, respectively, received a flare-up treatment with glucocorticoids. MS-associated overall costs, including indirect costs for MS-associated days absent from work, were € 16,433, with costs related to MS medication (€ 8770; 53.4%) being the main driver of costs in all subgroups. MS-associated costs according to MS subtypes were € 12,427 for CIS patients, € 14,459 for PPMS patients, € 20,583 for RRMS patients, and € 17,554 for SPMS patients. CONCLUSION Among the four MS subtypes, RRMS patients most often received a disease-modifying immunomodulatory treatment. Consequently, healthcare costs were highest for patients with this MS subtype. Contrary to the treatment guideline, a substantial percentage of patients with CIS, RRMS, and SPMS did not receive any disease-modifying immunomodulatory treatment.
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Affiliation(s)
- Sabrina Müller
- Institute for Pharmacoeconomics and Medication Logistics (IPAM), University of Wismar, Alter Holzhafen 19, 23966, Wismar, Germany.
| | - Tobias Heidler
- GWQ PLUS, Tersteegenstrasse 28, 40474, Düsseldorf, Germany
| | - Andreas Fuchs
- AOK PLUS, Rosa-Luxemburg-Straße 30, 04103, Leipzig, Germany
| | - Andreas Pfaff
- AOK Baden-Württemberg, Presselstraße 19, 70191, Stuttgart, Germany
| | - Kathrin Ernst
- AOK Baden-Württemberg, Presselstraße 19, 70191, Stuttgart, Germany
| | - Gunter Ladinek
- Roche Pharma AG, Emil-Barell-Str.1, 79639, Grenzach-Wyhlen, Germany
| | - Thomas Wilke
- Institute for Pharmacoeconomics and Medication Logistics (IPAM), University of Wismar, Alter Holzhafen 19, 23966, Wismar, Germany
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Saini A, Bach K, Poliakov I, Knox KB, Levin MC. Magnetic Resonance Imaging of Spinal Cord Lesions in Patients with Multiple Sclerosis in Saskatchewan, Canada. Int J MS Care 2020; 23:47-52. [PMID: 33880079 DOI: 10.7224/1537-2073.2019-081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background Spinal cord lesions (SCLs) contribute to disability in multiple sclerosis (MS). Data in Saskatchewan, Canada, concerning SCLs and their association with disability levels in patients with MS are lacking. The study objectives were to identify clinicodemographic profiles of patients with MS with respect to spinal cord magnetic resonance imaging (MRI) involvement; determine the frequency of individuals with MRI SCLs; and explore differences between patients with MS with and without SCLs with respect to disability and disease-modifying therapy status. Methods A monocentric, cross-sectional, retrospective review of prospectively collected data from 532 research-consented patients seen at Saskatoon MS Clinic was performed. Data were collected from a database and electronic medical records. Results Of the 356 patients (66.9%) with an SCL, 180 (50.6%) had only cervical cord lesions. Median Expanded Disability Status Scale (EDSS), ambulation, and pyramidal scores of patients with SCLs were higher than those of patients without SCLs. Of patients with EDSS scores of at least 6, those with SCLs were younger than those without SCLs (P = .01). Patients with SCLs were 55% less likely to have been on continuous disease-modifying therapy since diagnosis than patients without SCLs (adjusted odds ratio, 0.45; 95% CI, 0.25-0.81; P = .008). Conclusions Prevalence and association with disability of SCLs in patients with MS are comparable with existing literature. Patients with MS with SCLs have higher levels of disability and attain EDSS scores of at least 6 at a younger age.
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Cost of disease modifying therapies for multiple sclerosis: Is front-loading the answer? J Neurol Sci 2019; 404:19-28. [DOI: 10.1016/j.jns.2019.07.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 07/03/2019] [Accepted: 07/09/2019] [Indexed: 01/10/2023]
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Filser M, Schreiber H, Pöttgen J, Ullrich S, Lang M, Penner IK. The Brief International Cognitive Assessment in Multiple Sclerosis (BICAMS): results from the German validation study. J Neurol 2018; 265:2587-2593. [PMID: 30171410 DOI: 10.1007/s00415-018-9034-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 08/21/2018] [Accepted: 08/22/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND Recent research has convincingly shown that the ability to work mainly depends on the cognitive status in multiple sclerosis (MS). An international committee of experts recommended a brief neuropsychological battery to evaluate cognitive performance in MS. BICAMS comprises three tests, the Symbol Digit Modalities Test (SDMT), the learning trials of the California Verbal Learning Test II (CVLT-II), and the Brief Visuospatial Memory Test-Revised (BVMT-R). OBJECTIVE To validate BICAMS on a sample of German MS patients and healthy controls (HCs). METHODS According to the international guidelines for validation, examiner's instructions were standardized and translated into German. Due to the availability of better normative data for future applications in routine clinical care and classification of individual performance degree, the Rey Auditory Verbal Learning Test (RAVLT) (German version: Verbaler Lern- und Merkfähigkeits-Test, VLMT) was chosen instead of CVLT-II. 172 MS patients and 100 HCs entered the study. BICAMS was administered at baseline and retest (after 3-4 weeks). RESULTS The groups did not differ in age, gender or education. Mean age of MS patients was 43.33 years (SD 11.64); 68% were female and 86.9% had relapsing-remitting MS. Patients performed significantly worse than HCs on the SDMT (p < 0.01) and on BVMT-R (p < 0.05) but not on VLMT. In addition, BICAMS was shown to be reliable over time: r = 0.71 for BVMT-R, r = 0.72 for VLMT and r = 0.85 for SDMT. SDMT z-score proved to be a good predictor for the ability to work in a full-time (p < 0.001) as well as in a part-time job (p < 0.001). VLMT z-score turned out to be a significant predictor only for the ability to work in a part-time job, while BVMT-R z-score showed no significant predictive value. CONCLUSION In this German validation study with the VLMT, the modified BICAMS (BICAMS-M) turned out to reliably detect cognitive problems in MS patients and to monitor cognitive performance over time. SDMT revealed the best predictive value for working ability. Moreover, only the SDMT was able to predict the ability to work in a part-time or full-time job. Following these results, application of the SDMT is recommended for medical statements on working ability of MS patients.
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Affiliation(s)
- M Filser
- Cogito Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | - H Schreiber
- Neurological Practice and Neuropoint Academy, Ulm, Germany
| | - J Pöttgen
- Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - S Ullrich
- .05 Statistikberatung, Düsseldorf, Germany
| | - M Lang
- Neurological Practice and Neuropoint Academy, Ulm, Germany
| | - I K Penner
- Cogito Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany. .,Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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