Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking.
Objective:
To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters.
Methods:
A total of 177 patients from the original Avonex-Steroids-Azathioprine study were included. Participants underwent 3-month clinical follow-ups. Cox models were used to model the associations between clinical and MRI markers at baseline or after 12 months with sustained disability progression (SDP) over the 12-year observation period.
Results:
At baseline, T2 lesion number, T1 and T2 lesion volumes, corpus callosum (CC), and thalamic fraction were the best predictors of SDP (hazard ratio (HR) = 1.7–4.6; p ⩽ 0.001–0.012). At 12 months, Expanded Disability Status Scale (EDSS) and its change, number of new or enlarging T2 lesions, and CC volume % change were the best predictors of SDP over the follow-up (HR = 1.7–3.5; p ⩽0.001–0.017). A composite score was generated from a subset of the best predictors of SDP. Scores of ⩾4 had greater specificity (90%–100%) and were associated with greater cumulative risk of SDP (HR = 3.2–21.6; p < 0.001) compared to the individual predictors.
Conclusion:
The combination of established MRI and clinical indices with MRI volumetric predictors improves the prediction of SDP over long-term follow-up and may provide valuable information for therapeutic decisions.
KalincikTVaneckovaMTyblovaM. Volumetric MRI markers and predictors of disease activity in early multiple sclerosis: A longitudinal cohort study. PLoS ONE2012; 7(11): e50101.
2.
GiorgioABattagliniMRoccaMA. Location of brain lesions predicts conversion of clinically isolated syndromes to multiple sclerosis. Neurology2013; 80(3): 234–241.
3.
UherTHorakovaDKalincikT. Early magnetic resonance imaging predictors of clinical progression after 48 months in clinically isolated syndrome patients treated with intramuscular interferon beta-1a. Eur J Neurol2015; 22(7): 1113–1123.
4.
DobsonRRudickRATurnerB. Assessing treatment response to interferon-beta: Is there a role for MRI?Neurology2014; 82(3): 248–254.
5.
RioJCastilloJRoviraA. Measures in the first year of therapy predict the response to interferon beta in MS. Mult Scler2009; 15(7): 848–853.
6.
RomeoMMartinelliVRodegherM. Validation of 1-year predictive score of long-term response to interferon-beta in everyday clinical practice multiple sclerosis patients. Eur J Neurol2015; 22(6): 973–980.
7.
SormaniMPRioJTintoreM. Scoring treatment response in patients with relapsing multiple sclerosis. Mult Scler2013; 19(5): 605–612.
8.
BermelRAYouXFouldsP. Predictors of long-term outcome in multiple sclerosis patients treated with interferon beta. Ann Neurol2013; 73(1): 95–103.
FisherERudickRASimonJH. Eight-year follow-up study of brain atrophy in patients with MS. Neurology2002; 59(9): 1412–1420.
11.
O’RiordanJIThompsonAJKingsleyDP. The prognostic value of brain MRI in clinically isolated syndromes of the CNS: A 10-year follow-up. Brain1998; 121(Pt 3): 495–503.
12.
RudickRALeeJCSimonJ. Defining interferon beta response status in multiple sclerosis patients. Ann Neurol2004; 56(4): 548–555.
13.
RudickRALeeJCSimonJ. Significance of T2 lesions in multiple sclerosis: A 13-year longitudinal study. Ann Neurol2006; 60(2): 236–242.
14.
PopescuVAgostaFHulstHE. Brain atrophy and lesion load predict long term disability in multiple sclerosis. J Neurol Neurosurg Psychiatry2013; 84(10): 1082–1091.
15.
MinnebooAUitdehaagBMJongenP. Association between MRI parameters and the MS severity scale: A 12 year follow-up study. Mult Scler2009; 15(5): 632–637.
16.
ProsperiniLDe AngelisFDe AngelisR. Sustained disability improvement is associated with T1 lesion volume shrinkage in natalizumab-treated patients with multiple sclerosis. J Neurol Neurosurg Psychiatry2015; 86(2): 236–238.
17.
Perez-MirallesFCSastre-GarrigaJVidal-JordanaA. Predictive value of early brain atrophy on response in patients treated with interferon beta. Neurol Neuroimmunol Neuroinflamm2015; 2(4): e132.
18.
FilippiMPreziosaPCopettiM. Gray matter damage predicts the accumulation of disability 13 years later in MS. Neurology2013; 81(20): 1759–1767.
19.
RoccaMAMesarosSPaganiE. Thalamic damage and long-term progression of disability in multiple sclerosis. Radiology2010; 257(2): 463–469.
20.
MinagarABarnettMHBenedictRH. The thalamus and multiple sclerosis: Modern views on pathologic, imaging, and clinical aspects. Neurology2013; 80(2): 210–219.
21.
HavrdovaEZivadinovRKrasenskyJ. Randomized study of interferon beta-1a, low-dose azathioprine, and low-dose corticosteroids in multiple sclerosis. Mult Scler2009; 15(8): 965–976.
22.
CalabreseMRinaldiFMattisiI. The predictive value of gray matter atrophy in clinically isolated syndromes. Neurology2011; 77(3): 257–263.
23.
ZivadinovRHavrdovaEBergslandN. Thalamic atrophy is associated with development of clinically definite multiple sclerosis. Radiology2013; 268(3): 831–841.
24.
GoodinDSTraboulseeAKnappertzV. Relationship between early clinical characteristics and long term disability outcomes: 16 year cohort study (follow-up) of the pivotal interferon beta-1b trial in multiple sclerosis. J Neurol Neurosurg Psychiatry2012; 83(3): 282–287.
25.
HorakovaDDwyerMGHavrdovaE. Gray matter atrophy and disability progression in patients with early relapsing-remitting multiple sclerosis: A 5-year longitudinal study. J Neurol Sci2009; 282(1–2): 112–119.
26.
KalincikTHorakovaDDolezalO. Interferon, azathioprine and corticosteroids in multiple sclerosis: 6-year follow-up of the ASA cohort. Clin Neurol Neurosurg2012; 114(7): 940–946.
27.
BergslandNHorakovaDDwyerMG. Subcortical and cortical gray matter atrophy in a large sample of patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol2012; 33(8): 1573–1578.
28.
VaneckovaMKalincikTKrasenskyJ. Corpus callosum atrophy—A simple predictor of multiple sclerosis progression: A longitudinal 9-year study. Eur Neurol2012; 68(1): 23–27.
29.
HorakovaDKalincikTDolezalO. Early predictors of non-response to interferon in multiple sclerosis. Acta Neurol Scand2012; 126(6): 390–397.
30.
GoodkinDECookfairDWendeK. Inter- and intrarater scoring agreement using grades 1.0 to 3.5 of the Kurtzke Expanded Disability Status Scale (EDSS). Multiple Sclerosis Collaborative Research Group. Neurology1992; 42(4): 859–863.
31.
TrappBDPetersonJRansohoffRM. Axonal transection in the lesions of multiple sclerosis. N Engl J Med1998; 338(5): 278–285.
32.
HavrdovaEGalettaSHutchinsonM. Effect of natalizumab on clinical and radiological disease activity in multiple sclerosis: A retrospective analysis of the Natalizumab Safety and Efficacy in Relapsing-Remitting Multiple Sclerosis (AFFIRM) study. Lancet Neurol2009; 8(3): 254–260.
33.
DevonshireVHavrdovaERadueEW. Relapse and disability outcomes in patients with multiple sclerosis treated with fingolimod: Subgroup analyses of the double-blind, randomised, placebo-controlled FREEDOMS study. Lancet Neurol2012; 11(5): 420–428.
34.
KalincikTHorakovaDSpelmanT. Switch to natalizumab versus fingolimod in active relapsing-remitting multiple sclerosis. Ann Neurol2015; 77: 425–435.
35.
HeASpelmanTJokubaitisV. Comparison of switch to fingolimod or interferon beta/glatiramer acetate in active multiple sclerosis. JAMA Neurol2015; 72(4): 405–413.
