1. Basic Treatment Principles in MS Start Early/Switch Early
Bassem I Yamout, MD, FAAN
Professor of Clinical Neurology
Head, Multiple Sclerosis Center Clinical Research
American University of Beirut Medical Center
Florian Deisenhammer
Dept. of Neurology
Innsbruck Medical University, Germany
On behalf of the ParadigMS Board Members

2. What you see clinically is only the tip of the iceberg
MRI
Pathology
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3. A. Immune Attack leading to Demyelination
Activated T cells
A. Immune Attack leading to Demyelination
Differentiation of Astrocytes and activation of Microglia
Myelin specific
Ab + Complement
Microglia products NO
ROS
Glutamate
MMPs
Cytokines

4. A. Immune Attack leading to Demyelination
Activated T cells
A. Immune Attack leading to Demyelination
Differentiation of Astrocytes and activation of Microglia
Myelin specific
Ab + Complement
Microglia products NO
ROS
Glutamate
MMPs
Cytokines
B. Loss of Axonal Trophic Support
Disturbed axon-glia interaction
Mitochondrial dysfunction
CD8 + CTL + Perforin

5. A. Immune Attack leading to Demyelination
Differentiation of Astrocytes and activation of Microglia
Microglia products
Activated T cells NO
Myelin specific
Ab + Complement
ROS
Glutamate
MMPs
Cytokines
A. Immune Attack leading to Demyelination
B. Loss of Axonal Trophic Support
Disturbed axon-glia interaction
CD8 + CTL + Perforin
Mitochondrial dysfunction
C. Axonal Transection and Wallerian Degeneration
N-type Ca-channel® Ca++ influx ® Ca overload ® Cytoskeleton disintegration ® Apoptosis

6. Pathological Events in MS
Axonal Transection is irreversible and most abundant in area of inflammation
Trapp et al., NEJM 1998

7. Natural History Study for MS Association of early relapses (almost all for the 1st year)
Median time from onset of MS to DSS3
Median time from onset of MS to DSS6
Number of attacks in the first two years
Number of attacks in the first two years
Weinshenker BG al. Brain 1989, Ebers et al. JNNP (suppl.) 2001
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8. Relationship between the number of T2 lesions detected at presentation with a CIS and outcome 14 years later
Brex t al. NEJM 2002
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9. Why treat or escalate early?
Permanent axonal loss correlates with ongoing inflammation
We have to prevent further damage, and this is best done as early as possible if the disease is active
“What is lost by delaying treatment
cannot be regained at a later stage”
Early suppression of active inflammation may help to minimise cumulative axonal loss
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10. Early Treatment of RRMS: The Current Evidence
Wait or start? Prognostic markers to help us make this choice?
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11. BENEFIT: Early treatment significantly delayed CDMS onset by 750 days over 5 years
Patients at risk
n = 176
n = 292
116
223
33 95
CDMS (%) 10 20 30 40 50 60
Delayed treatment
Year 1
Year 2
Year 3
Year 5
Year 4 BL
+ 750 days
40th percentile
Early treatment
Log rank: P=0.003
Risk reduction* of 37% over 5 years (Hazard ratio= 0.63)
57%
46%
*By proportional hazards regression adjusted for age/gender/steroids/onset of disease/T2-lesions/Gd-lesions

12. Effect of early treatment on cognitive performance
Primary analysis* At Year 5: P=0.0045
Sensitivity analysis** At Year 5 LOCF: P<0.001
Improvement
Early treatment
Delayed treatment
p=0.064*
*The PASAT is a subtest of the Multiple Sclerosis Functional Composite (MSFC)
No significant difference between the two treatment groups for the other Multiple Sclerosis Functional Composite (MSFC) subscales (25-Foot Walk, 9-Hole Peg Test) or the overall MSFC.
**Non-parametric analysis
covariance adjusted for baseline
LOCF = last observation carried forward
Early and sustained effect of early vs. delayed treatment in follow-up study
Kappos et al Lancet Neurology, 2009
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13. Preventing SPMS
IFNB delays the time from first visit to onset of SPMS Data from an Italian RR-MS cohort (n=1,504) follow for up to 7 years
20.2%
8.0%
*Propensity score-adjusted survival curves for end point
Kappos et al Lancet Neurology, 2009

14. The 2 Extremes: Benign MS does exist but is a retrospective diagnosis
28 patients with EDSS 0-2 and
disease duration>10 years had:
25/27 had an EDSS≤3 10 years later
None developed SPMS
2/27 were unemployed
All reported satisfactory or better QOL
Pittock et al. Ann Neurol; 2004
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15. The 2 Extremes: Benign MS does exist but is a retrospective diagnosis
Is it possible to predict benign multiple sclerosis? Ottawa-Canada, Trieste-Italy
A retrospective study of patients with the following inclusion criteria: clinically definite EDSS score ≤2 or ≤1 at 10 years from onset of first symptoms; clinical assessments performed at 10±1 and 20±1 years from onset of MS symptoms. Results: Of 175 patients enrolled, patients with EDSS score ≤2 or ≤1 at 10 years 71.9% and 81.6%, remained benign at 20 years respectively. There were significantly more patients (p=0.033) treated with disease modifying drugs (DMD) in the NLB group. In a logistic regression analysis EDSS ≤1 at 10 years was able to predict a benign course at 20 years with better than 80% specificity. Discussion and conclusions: We found a higher percentage of benign patients at 20 years compared to previous studies, possibly due to a higher percentage of patients treated with DMD in our population. However, EDSS ≤2 at 10 years had a better predictive value than EDSS score ≤3 at 10 years, which was neither sensitive nor specific for predicting continuing to be benign at 20 years. We propose that a better definition of benign use stricter EDSS cut-offs (≤2 or even ≤1) at 10 years, in order to enhance the specificity.
A. Sartori, M. Abdoli, M.S. Freedman; ECTRIMS 2015
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16. Effect of baseline characteristics on the risk of attaining EDSS 3.0
The 2 Extremes: Aggressive MS requires high efficacy DMD early on
Time from onset of MS to EDSS 6.0 according to initial relapses: EDMUS Lyon
Effect of baseline characteristics on the risk of attaining EDSS 3.0
Variable
Median years to EDSS 6.0
95% CI
P value
Initial course
Relapsing-remitting*
Progressive**
23.1
7.1
20.1–26.1
6.3–7.9
Reference
<0.001
Recovery from the 1st relapse
Complete
Incomplete
27.1
13.0
23.5–30.7
9.7–16.3
Time from onset of MS to 2nd neurological episode
<2 years
2–5 years
>5 years
17.1
20.1
27.9
14.2–19.9
15.7–24.5
23.9–31.9
0.02
Number of relapses during 1st 5 years
n=1
n=2
n≥3
25.3
21.9
24.7
21.9–28.6
15.3–28.6
16.9–32.4
0.01
Number of relapses during the initial course and incomplete recovery from the first relapse Predict a more aggressive course of the disease
Presence of OCB, >10 lesions on MRI, Non-optic neuritis presentation and older age were predictive of an aggressive course and future disability
Confavreux et al. Brain 2003
Tintore et al. Brain 2015

17. Switching Therapy When to switch ? Switch to what?
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18. When to switch? Intolerable side-effects: Neutralizing antibodies:
adverse reaction: injection site reaction, infusion reaction, infections
persistent symptoms: flu-like symptoms, headache, nausea
laboratory abnormalities: increased liver enzymes, severe autoimmune hypothyroidism
Neutralizing antibodies:
anti-IFN-β (high-titre), anti-natalizumab
Risk of life-threatening infection:
JC virus (pertinent for natalizumab use)
Unacceptable disease activity:
definition of suboptimal response:
clinical activity: relapse rate, cognitive decline, increased EDSS (transition to progression) ?
MRI activity: appearance of 2 or more T2 lesions, persistence of active lesions?
a mix of clinical and MRI parameters?
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19. MRI Predicting Treatment Effects
N=152, RRMS, observation over 2 years (months 12-36).
MRI determined in the first 12 months of treatment
Probability of remaining free of progression
Rio et al, Mult Scler 2008; Rio et al Nat Rev Neurol et al 2009
Time since treatment onset (months)
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20. Prediction of Disease Activity from 1 year MRI
370 patients treated with IFNB and followed for 4 years
MRI performed at 1 year
At 4-year follow-up:
Risk of disability worsening in those with increased MRI activity at 1 year :
HR=5.31 (P<0.001)
N = 370
Relapse
Sustained EDSS progression
Relapse & sustained EDSS progression
CEL=contrast-enhancing lesion.
Prosperini L et al. Mult Scler. 2014
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21. MRI to monitor treatment response to IFN-beta A systematic review
Pooled analysis of those with ≥2 new T2 lesions
Relapse or sustained
EDSS progression
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22. MRI lesions as a surrogate for relapses in MS: a meta-analysis of randomized trials
Sormani et al. Lancet Neurol 2013
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23. MRI lesions as a surrogate for relapses in MS: a meta-analysis of randomized trials
Patients
The effect of a treatment on relapses can be accurately predicted by the effect of that therapy on MRI lesions
Sormani et al. Lancet Neurol 2013
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24. Progression Probability (%)
Scoring treatment response in patients with relapsing MS: The Modified Rio Score
Modified Rio Score
Criterion
Relapse=0; New T2 lesions ≤4 1
Relapse=0; New T2 lesions >4 OR
Relapse=1; New T2 lesions ≤4 2
Relapse=1; New T2 lesions >4
Relapse ≥2; New T2 lesions ≤4 3
Relapse ≥2; New T2 lesions >4
100 80 60 40 20
Progression Probability (%)
Years 1 2 3
Score ≥2 Score=1
Score=0
Modified Rio Score
Assessment Window
Risk of progression = 65%†
P<0.001 vs Score of 0
Risk of progression = 33%†
P=0.13 vs Score of 0
Risk of progression = 24%
*Data taken from the PRISMS Trial; †compared to modified Rio score of 0
Sormani et al. Lancet Neurol 2013
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25. Combining clinical and MRI predictors
1280 patients with RRMS on IFNB from 9 MAGNIMS centers were followed for 3 years.
MRI and clinical assessment were performed at 1 year
Treatment failure defined as EDSS progression or switching of treatment for inefficacy
was assessed after a period of at least 3 years
17%
27%
48%
Sormani et al. Neurology 2016
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26. Ideal predictors of treatment response in MS: The future
Proteomics
Metabolomics
A Clinical and radiological
characteristics
Variables
A B C D
C Others
A An
B Bn
C Cn
D Dn 1 2 N
% R to treament 1
…………………………….
% R to treament N
% R to treament 1
Prediction
of response
Patients
…………………………….
B Transcriptomics
% R to treament N
% R to treament 1
…………………………….
% R to treament N
D Genetic polymorphisms
Genes
SNP a
SNP d
“Pharmacogenomics in multiple sclerosis:
Getting the right medicine to the patient”
Manuel Comabella
Therapy 2008; 5(5):
Non-
responder
SNP f
Responder

27. Basic switch principles and suggestions for switching
Switching because of side-effects or poor adherence generally involves changing between first-line agents (IFNβ, GA, Teriflunomide, DMF).
Switching from first- to second-line agents is suggested for patients with significant breakthrough activity.
There is currently no Class I evidence to support the administration of any monotherapy in patients with breakthrough disease, except for the CARE-MS II study which showed the superiority of Alemtuzumab to INFB in patients with breakthrough disease on INFB or GA
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28. TOP-MSBase study: Escalation to natalizumab vs interferon beta/
glatiramer acetate in active RRMS patients
>1 relapse in prior year
TOP
Natalizumab
IFN/ GA
12-week confirmed disability progression over the 4 years after treatment transition
GA/IFN
1.00
0.75
0.50
0.25
0.00 10 20 30 40 50
Months
Natalizumab
IFN/GA
26% risk reduction with switch to natalizumab†
HR=0.74; 95% CI: 0.55–0.97; P<0.036
MSBase
ARR in the first year after treatment transition
Proportion of patients without confirmed disability progression
Annualised relapse rate
66% reduction
P <0.0001
(n=497)
(n=607)
Spelman T et al. Ann Clin Transl Neurol. 2015

29. TRUST: The German experience
TRUST is an ongoing prospective multicenter cohort study in 200 German centers
The study enrolls patients with ongoing natalizumab therapy for at least 12 months
427 patients have been enrolled as of August 2015
92%
92% of patients were on BRACE before switch
Ziemssen et al. Presented at the AAN 2016
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30. TOP: Multinational real world evidence
The Tysabri Observational Program (TOP) is a 10 year multinational prospective observational study that provides real world data on patients initiating Tysabri
This analysis was conducted on patients switching to natalizumab.
Butzkueven et al. Presented at the AAN 2016
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31. TRANSFORMS Trial -61% vs IFNβ-1a IM ARR
p<0.001
ARR
(n = 149)
(n = 160)
IFNβ-1a IM
Fingolimod
Retrospective review of the US administrative claims data from the PharmMetrics Plus database.
264 patients switching from BIFN to GA or fingolimod were identified and matched using propensity scoring
Baseline ARR were similar in both groups ( GA: 0.49, Fingolimod: 0.46)
In a subgroup analysis of patients with highly active disease despite IFNβ treatment in the year preceding enrollment, fingolimod reduced ARR by 61% relative to IFNβ-1a
Cohen et al. J Neurol, 2013

32. Alemtuzumab: CARE-MS II
2 year study of interferon beta 1a 44 μg vs intravenous alemtuzumab 12 mg/d x5d at baseline and x3d at 12 m
667 RRMS patients with at least one relapse on IFNB or GA
Coles et al. Lancet,2012

33. Lateral Switching between first line treatments
2 year study of interferon beta 1a 44 μg vs intravenous alemtuzumab 12 mg/d x5d at baseline and x3d at 12 m
667 RRMS patients with at least one relapse on IFNB or GA
IFN-β/IFN-β
IFN-β/GA
GA/IFN-β
IFN-β or GA/ MTX
IFN-β or GA/ NTZ
Pre-treatment mARR
1.1 ± 0.6
1.2 ± 0.7
1.1 ± 0.7
1.6 ± 0.7
1.3 ± 0.5
Treatment 1 mARR
0.9 ± 0.8
0.82 ± 0.6
1.3 ± 0.8
0.94 ± 0.4
Treatment 1 pFFR
13% 7%
18% 0%
Treatment 2 mARR
0.27 ± 0.4
0.25 ± 0.4
0.16± 0.3
0.34± 0.4
0.04± 0.1
Treatment 2 pFFR
61%
64%
73%
42%
81%
Conclusion: In patients with RRMS who have a poor response, switching to another first line DMD may reduce the clinical activity of the disease
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34. Non-aggressive RRMS patients Aggressive RRMS patients
MENACTRIMS Algorithm for MS treatment
Non-aggressive RRMS patients
Aggressive RRMS patients
IFN B
GA*
Ter
DMF
Patients with contraindications or AE to IFN-B, GA, TER, DMF
≥ 2 disabling relapses in past year AND active MRI
Low
Concern
Fingolimod, Natalizumab Alemtuzumab
(Based on risk stratification)
Fingolimod
Suboptimal Response: Consider Therapy Escalation
Fingolimod, Natalizumab Alemtuzumab
(Based on risk stratification)
Fingolimod, Natalizumab Alemtuzumab
(Based on risk stratification)
Natalizumab Alemtuzumab
(Based on risk stratification)
Suboptimal Response: Consider Therapy Escalation
Rescue Therapy: Rituximab – Cyclophosphamide – Mitoxantrone – Autologous hematopoietic stem cell transplantation
Yamout et al. CMRO, 2015

35. Conclusion: 2 windows of opportunity
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36. Thank You!

37. Prognostic Factors help predicting course
CLINICAL
Gender, age at onset,
multifocal presentation,
pyramidal and cerebellar
systems involved, partial
recovery from relapses, high
relapse rate during
the first two years
from onset
MRI
T1 lesion load,
persistence of ‘activity’
(increased T2 LV, Gd+),
brain and GM atrophy,
spinal cord lesions
CSF MARKERS
IgG OB, increased
lymphocyte count,
markers of neurodegeneration
( proteins, tau,
NFL [high/low]),
IL-1β
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