Correlates and trajectories of relapses in relapsing-remitting multiple sclerosis.
Multiple sclerosis
Patient-reported outcome measure
Rasch
Relapse
Trajectories of Outcome in Neurological Conditions-MS
Journal
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
ISSN: 1590-3478
Titre abrégé: Neurol Sci
Pays: Italy
ID NLM: 100959175
Informations de publication
Date de publication:
17 Nov 2023
17 Nov 2023
Historique:
received:
02
02
2023
accepted:
21
10
2023
medline:
17
11
2023
pubmed:
17
11
2023
entrez:
17
11
2023
Statut:
aheadofprint
Résumé
In people with relapsing-remitting multiple sclerosis (pwRRMS), data from studies on non-pharmacological factors which may influence relapse risk, other than age, are inconsistent. There is a reduced risk of relapses with increasing age, but little is known about other trajectories in real-world MS care. We studied longitudinal questionnaire data from 3885 pwRRMS, covering smoking, comorbidities, disease-modifying therapy (DMT), and patient-reported outcome measures, as well as relapses during the past year. We undertook Rasch analysis, group-based trajectory modelling, and multilevel negative binomial regression. The regression cohort of 6285 data sets from pwRRMS over time showed that being a current smoker was associated with 43.9% greater relapse risk; having 3 or more comorbidities increased risk and increasing age reduced risk. Those diagnosed within the last 2 years showed two distinct trajectories, both reducing in relapse frequency but 25.8% started with a higher rate and took 4 years to reduce to the rate of the second group. In the cohort with at least three data points completed, there were three groups: 73.7% followed a low stable relapse rate, 21.6% started from a higher rate and decreased, and 4.7% had an increasing then decreasing pattern. These different trajectory groups showed significant differences in fatigue, neuropathic pain, disability, health status, quality of life, self-efficacy, and DMT use. These results provide additional evidence for supporting pwRRMS to stop smoking and underline the importance of timely DMT decisions and treatment initiation soon after diagnosis with RRMS.
Sections du résumé
BACKGROUND AND AIMS
OBJECTIVE
In people with relapsing-remitting multiple sclerosis (pwRRMS), data from studies on non-pharmacological factors which may influence relapse risk, other than age, are inconsistent. There is a reduced risk of relapses with increasing age, but little is known about other trajectories in real-world MS care.
METHODS
METHODS
We studied longitudinal questionnaire data from 3885 pwRRMS, covering smoking, comorbidities, disease-modifying therapy (DMT), and patient-reported outcome measures, as well as relapses during the past year. We undertook Rasch analysis, group-based trajectory modelling, and multilevel negative binomial regression.
RESULTS
RESULTS
The regression cohort of 6285 data sets from pwRRMS over time showed that being a current smoker was associated with 43.9% greater relapse risk; having 3 or more comorbidities increased risk and increasing age reduced risk. Those diagnosed within the last 2 years showed two distinct trajectories, both reducing in relapse frequency but 25.8% started with a higher rate and took 4 years to reduce to the rate of the second group. In the cohort with at least three data points completed, there were three groups: 73.7% followed a low stable relapse rate, 21.6% started from a higher rate and decreased, and 4.7% had an increasing then decreasing pattern. These different trajectory groups showed significant differences in fatigue, neuropathic pain, disability, health status, quality of life, self-efficacy, and DMT use.
CONCLUSIONS
CONCLUSIONS
These results provide additional evidence for supporting pwRRMS to stop smoking and underline the importance of timely DMT decisions and treatment initiation soon after diagnosis with RRMS.
Identifiants
pubmed: 37976012
doi: 10.1007/s10072-023-07155-3
pii: 10.1007/s10072-023-07155-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Multiple Sclerosis Society
ID : C009-16.1
Pays : United Kingdom
Investigateurs
Carolyn Young
(C)
David Rog
(D)
Basil Sharrack
(B)
Cris Constantinescu
(C)
Seema Kalra
(S)
Tahir Majeed
(T)
Helen Santander
(H)
Tim Harrower
(T)
Oliver Leach
(O)
Richard Nicholas
(R)
Helen Ford
(H)
John Woolmore
(J)
Chris Kipps
(C)
Clare Johnston
(C)
John Thorpe
(J)
David Paling
(D)
Yasser Falah
(Y)
Cathy Ellis
(C)
Ashwin Pinto
(A)
C Oliver Hanemann
(CO)
Siddharthan Chandran
(S)
Andrea Malaspina
(A)
Jo Kitley
(J)
Jacqueline Palace
(J)
Tracy Fuller
(T)
Pat Mottram
(P)
Helen Terrett
(H)
Antonio Scalfari
(A)
Informations de copyright
© 2023. The Author(s).
Références
McDonald WI, Compston A, Edan G, Goodkin D, Hartung H-P, Lublin FD, McFarland HF, Paty DW, Polman CH, Reingold SC, Sandberg-Wollheim M, Sibley W, Thompson A, Van Den Noort S, Weinshenker BY, Wolinsky JS (2001) Recommended diagnostic criteria for multiple sclerosis: guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol 50:121–127. https://doi.org/10.1002/ana.1032
doi: 10.1002/ana.1032
pubmed: 11456302
Simbrich A, Thibaut J, Khil L, Berger K, Riedel O, Schmedt N (2019) Drug-use patterns and severe adverse events with disease-modifying drugs in patients with multiple sclerosis: a cohort study based on German claims data. Neuropsychiatr Dis Treat 15:1439–1457. https://doi.org/10.2147/ndt.S200930
doi: 10.2147/ndt.S200930
pubmed: 31213818
pmcid: 6549763
Nazareth TA, Rava AR, Polyakov JL, Banfe EN, Waltrip Ii RW, Zerkowski KB, Herbert LB (2018) Relapse prevalence, symptoms, and health care engagement: patient insights from the multiple sclerosis in America 2017 survey. Mult Scler Relat Disord 26:219–234. https://doi.org/10.1016/j.msard.2018.09.002
doi: 10.1016/j.msard.2018.09.002
pubmed: 30368080
Tremlett H, Zhao Y, Joseph J, Devonshire V (2008) Relapses in multiple sclerosis are age- and time-dependent. J Neurol Neurosurg Psychiatry 79(12):1368–1374. https://doi.org/10.1136/jnnp.2008.145805
doi: 10.1136/jnnp.2008.145805
pubmed: 18535026
Miller DH (2004) Biomarkers and surrogate outcomes in neurodegenerative disease: lessons from multiple sclerosis. NeuroRx: J Amer Soc Exp NeuroTher 1(2):284–294. https://doi.org/10.1602/neurorx.1.2.284
doi: 10.1602/neurorx.1.2.284
Koch MW, Mostert J, Zhang Y, Wolinsky JS, Lublin FD, Strijbis E, Cutter G (2021) Association of age with contrast-enhancing lesions across the multiple sclerosis disease spectrum. Neurology 97(13):e1334–e1342. https://doi.org/10.1212/wnl.0000000000012603
doi: 10.1212/wnl.0000000000012603
pubmed: 34376508
pmcid: 8589289
Schwehr NA, Kuntz KM, Butler M, Enns EA, Shippee ND, Kingwell E, Tremlett H, Carpenter AF (2020) Age-related decreases in relapses among adults with relapsing-onset multiple sclerosis. Mult Scler 26(12):1510–1518. https://doi.org/10.1177/1352458519866613
doi: 10.1177/1352458519866613
pubmed: 31354041
von Wyl V, Décard BF, Benkert P, Lorscheider J, Hänni P, Lienert C, Kuhle J, Derfuss T, Kappos L, Yaldizli Ö (2020) Influence of age at disease onset on future relapses and disability progression in patients with multiple sclerosis on immunomodulatory treatment. Eur J Neurol 27(6):1066–1075. https://doi.org/10.1111/ene.14191
doi: 10.1111/ene.14191
Petruzzo M, Reia A, Maniscalco GT, Luiso F, Lanzillo R, Russo CV, Carotenuto A, Allegorico L, Palladino R, Brescia Morra V, Moccia M (2021) The Framingham cardiovascular risk score and 5-year progression of multiple sclerosis. Eur J Neurol 28(3):893–900. https://doi.org/10.1111/ene.14608
doi: 10.1111/ene.14608
pubmed: 33091222
Kowalec K, McKay KA, Patten SB, Fisk JD, Evans C, Tremlett H, Marrie RA (2017) Comorbidity increases the risk of relapse in multiple sclerosis: a prospective study. Neurology 89(24):2455–2461. https://doi.org/10.1212/wnl.0000000000004716
doi: 10.1212/wnl.0000000000004716
pubmed: 29117961
pmcid: 5729795
Salter A, Kowalec K, Fitzgerald KC, Cutter G, Marrie RA (2020) Comorbidity is associated with disease activity in MS: findings from the CombiRx trial. Neurology 95(5):e446–e456. https://doi.org/10.1212/wnl.0000000000010024
doi: 10.1212/wnl.0000000000010024
pubmed: 32554770
pmcid: 9629214
Diržiuvienė B, Mickevičienė D (2022) Comorbidity in multiple sclerosis: emphasis on patient-reported outcomes. Mult Scler Relat Disord 59:103558. https://doi.org/10.1016/j.msard.2022.103558
doi: 10.1016/j.msard.2022.103558
pubmed: 35123292
Abbaszadeh S, Tabary M, Aryannejad A, Abolhasani R, Araghi F, Khaheshi I, Azimi A (2021) Air pollution and multiple sclerosis: a comprehensive review. Neurol Sci 42(10):4063–4072. https://doi.org/10.1007/s10072-021-05508-4
doi: 10.1007/s10072-021-05508-4
pubmed: 34341860
Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, Fujihara K, Havrdova E, Hutchinson M, Kappos L, Lublin FD, Montalban X, O’Connor P, Sandberg-Wollheim M, Thompson AJ, Waubant E, Weinshenker B, Wolinsky JS (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302. https://doi.org/10.1002/ana.22366
doi: 10.1002/ana.22366
pubmed: 21387374
pmcid: 3084507
Mills RJ, Young CA (2011) The relationship between fatigue and other clinical features of multiple sclerosis. Mult Scler 17(5):604–612. https://doi.org/10.1177/1352458510392262
doi: 10.1177/1352458510392262
pubmed: 21135018
Buron MD, Chalmer TA, Sellebjerg F, Barzinji I, Danny B, Christensen JR, Christensen MK, Hansen V, Illes Z, Jensen HB, Kant M, Papp V, Petersen T, Prakash S, Rasmussen PV, Schäfer J, Theódórsdóttir Á, Weglewski A, Sorensen PS, Magyari M (2020) Initial high-efficacy disease-modifying therapy in multiple sclerosis: a nationwide cohort study. Neurology 95(8):e1041–e1051. https://doi.org/10.1212/wnl.0000000000010135
doi: 10.1212/wnl.0000000000010135
pubmed: 32636328
Üstün T, Kostanjsek N, Chatterji S, Rehm J (2010) Measuring health and disability manual for WHO Disability Assessment Schedule. World Health Org Geneva
Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, Bonsel G, Badia X (2011) Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res 20(10):1727–1736. https://doi.org/10.1007/s11136-011-9903-x
doi: 10.1007/s11136-011-9903-x
pubmed: 21479777
pmcid: 3220807
Devlin NJ, Shah KK, Feng Y, Mulhern B, van Hout B (2018) Valuing health-related quality of life: an EQ-5D-5L value set for England. Health Econ 27(1):7–22. https://doi.org/10.1002/hec.3564
doi: 10.1002/hec.3564
pubmed: 28833869
McNamara S, Schneider PP, Love-Koh J, Doran T, Gutacker N (2023) Quality-adjusted life expectancy norms for the English population. Value Health 26(2):163–169. https://doi.org/10.1016/j.jval.2022.07.005
doi: 10.1016/j.jval.2022.07.005
pubmed: 35965226
Mills RJ, Young CA, Pallant JF, Tennant A (2010) Development of a patient reported outcome scale for fatigue in multiple sclerosis: the Neurological Fatigue Index (NFI-MS). Health Qual Life Outcomes 8:22. https://doi.org/10.1186/1477-7525-8-22
doi: 10.1186/1477-7525-8-22
pubmed: 20152031
pmcid: 2834659
Galer BS, Jensen MP (1997) Development and preliminary validation of a pain measure specific to neuropathic pain: the Neuropathic Pain Scale. Neurology 48(2):332–338. https://doi.org/10.1212/wnl.48.2.332
doi: 10.1212/wnl.48.2.332
pubmed: 9040716
Young CA, Mills RJ, Woolmore J, Hawkins CP, Tennant A (2012) The unidimensional self-efficacy scale for MS (USE-MS): developing a patient based and patient reported outcome. Mult Scler 18(9):1326–1333. https://doi.org/10.1177/1352458512436592
doi: 10.1177/1352458512436592
pubmed: 22492132
Pomeroy IM, Tennant A, Mills RJ, Young CA (2020) The WHOQOL-BREF: a modern psychometric evaluation of its internal construct validity in people with multiple sclerosis. Qual Life Res 29(7):1961–1972. https://doi.org/10.1007/s11136-020-02463-z
doi: 10.1007/s11136-020-02463-z
pubmed: 32193839
pmcid: 7295715
Rasch G (1980) Probabilistic models for some intelligence and attainment tests. The University of Chicago Press, Chicago
McLennan D, Noble S, Noble M, Plunkett E, Wright G, Gutacke N (2019) The English Indices of Deprivation 2019. Technical report. Ministry of Housing, Communities and Local Government
Horton M, Rudick RA, Hara-Cleaver C, Marrie RA (2010) Validation of a self-report comorbidity questionnaire for multiple sclerosis. Neuroepidemiology 35(2):83–90. https://doi.org/10.1159/000311013
doi: 10.1159/000311013
pubmed: 20551692
Jones BL, Nagin DS (2013) A note on a Stata plugin for estimating group-based trajectory models. Sociol Methods Res 42(4):608–613. https://doi.org/10.1177/0049124113503141
doi: 10.1177/0049124113503141
Jasielski P, Piędel F, Rocka A, Petit V, Rejdak K (2020) Smoking as a risk factor of onset and relapse of multiple sclerosis - a review. Neurol Neurochir Pol 54(3):243–251. https://doi.org/10.5603/PJNNS.a2020.0032
doi: 10.5603/PJNNS.a2020.0032
pubmed: 32285433
McKay KA, Jahanfar S, Duggan T, Tkachuk S, Tremlett H (2017) Factors associated with onset, relapses or progression in multiple sclerosis: a systematic review. Neurotoxicology 61:189–212. https://doi.org/10.1016/j.neuro.2016.03.020
doi: 10.1016/j.neuro.2016.03.020
pubmed: 27045883
Ribbons KA, McElduff P, Boz C, Trojano M, Izquierdo G, Duquette P, Girard M, Grand’Maison F, Hupperts R, Grammond P, Oreja-Guevara C, Petersen T, Bergamaschi R, Giuliani G, Barnett M, Van Pesch V, Amato M-P, Iuliano G, Fiol M, Slee M, Verheul F, Cristiano E, Fernandez-Bolanos R, Saladino M-L, Rio ME, Cabrera-Gomez J, Butzkueven H, Van Munster E, Den Braber-Moerland L, La Spitaleri D, Lugaresi A, Shaygannejad V, Gray O, Deri N, Alroughani R, Lechner-Scott J (2015) Male sex is independently associated with faster disability accumulation in relapse-onset MS but not in primary progressive MS. PLoS ONE 10(6):e0122686. https://doi.org/10.1371/journal.pone.0122686
doi: 10.1371/journal.pone.0122686
pubmed: 26046348
pmcid: 4457630
Vandebergh M, Andlauer TFM, Zhou Y, Mallants K, Held F, Aly L, Taylor BV, Hemmer B, Dubois B, Goris A (2021) Genetic variation in WNT9B increases relapse hazard in multiple sclerosis. Ann Neurol 89(5):884–894. https://doi.org/10.1002/ana.26061
doi: 10.1002/ana.26061
pubmed: 33704824
pmcid: 8252032
Gasperi C, Hapfelmeier A, Daltrozzo T, Schneider A, Donnachie E, Hemmer B (2021) Systematic assessment of medical diagnoses preceding the first diagnosis of multiple sclerosis. Neurology. https://doi.org/10.1212/wnl.0000000000012074
doi: 10.1212/wnl.0000000000012074
pubmed: 33903190
Wilson IB, Cleary PD (1995) Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA 273(1):59–65
doi: 10.1001/jama.1995.03520250075037
pubmed: 7996652