Treating ms in 2014 giovannoni gg4

Treating MS in 2014

Professor Gavin Giovannoni

Blizard Institute, Barts and The London School of Medicine and Dentistry

Disclosures Professor Giovannoni has received personal compensation for participating on Advisory Boards in relation to clinical trial design, trial steering committees and data and safety monitoring committees from: Abbvie, Bayer-Schering Healthcare, Biogen-Idec, Canbex, Eisai, Elan, Fiveprime, Genzyme, Genentech, GSK, GW Pharma, Ironwood, Merck-Serono, Novartis, Pfizer, Roche, Sanofi-Aventis, Synthon BV, Teva, UCB Pharma and Vertex Pharmaceuticals.

Regarding www.ms-res.org survey results in this presentation: please note that no personal identifiers were collected as part of these surveys and that by completing the surveys participants consented for their anonymous data to be analysed and presented by Professor Giovannoni.

Professor Giovannoni would like to acknowledge and thank Biogen-Idec, Genzyme and Novartis for making available data slides on natalizumab, alemtuzumab and fingolimod for this presentation.

http://www.ms-res.org/







Is the MS dogma wrong?

immune activation innate and adaptive responses

focal inflammation

BBB breakdown

oligodendrocyte toxicity & demyelination

Acute axonal transection and loss

“autoimmune endophenotype”

axonal plasticity & remyelination

delayed neuroaxonal loss and gliosis

Gd-enhancement

T2 & T1 lesions

brain & spinal cord atrophy

release of soluble markers

Clinical Attack

Disease Progression

Clinical Recovery

- biology

- clinical outcomes

- biomarkers

VIRUS (EBV, HERVs)

Charcot Project: viral aetiology

HIV and lower risk of MS: beginning to unravel a mystery using a record-linked database study

Nexø et al. Epidemiology 2013; 24:331-2

Treatment of HIV and Risk of Multiple Sclerosis

Gold et al. JNNP August 4, 2014 as 10.1136/jnnp-2014-307932.

Raltegravir → RRMS (INSPIRE STUDY) ClinicalTrials.gov ID: NCT01767701

Trial activity targeting progressive pathology

MRI Events

1st clinical attack

Time (Years)

Subclinical disease

Inflammation

Brain volume loss

Neuroaxonal loss

Dis

eas

e S

eve

rity

SPMS RRMS

1st MRI lesion

Relapses

CIS RIS R-SPMS

RIS = radiologically isolated syndrome; CIS = clinically isolated syndrome, RRMS = relapsing-remitting MS; R-SPMS = relapsing secondary progressive MS; SPMS = secondary progressive MS; PPMS = primary progressive MS

SPMS: Natalizumab, Siponimod, DMF

Late SPMS: SMART STUDY fluoxetine, amiloride, riluzole

Early SPMS: oxcarbazepine

CIS: PHENYTOIN RRMS: ? DE-FLAMES STUDY

PPMS

PPMS: Fingolimod, Ocrelizumab, Laquinimod

SP&PPMS: Ibudilast

www.ms-res.org

Questions: DMT perspective

To make an informed decision you need to ask and understand the following questions:

1. Are you sure they have MS?

2. What types of MS do they have?

3. What prognostic group do they fall into?

4. What is the risk of them not having any treatment?

5. Do they have active MS?

6. Are they eligible for treatment with a DMT?

7. Do they understand the difference between the treatment strategies of maintenance & escalation vs. induction therapy?

8. Will they be adherent on treatment?

9. What is your therapeutic target for them?

What constitutes a useful diagnostic test or set of criteria?

TARGET DISORDER

PRESENT ABSENT

DIAGNOSTIC

TEST RESULT

+ a b a + b

- c d c + d

a + c b + d a + b + c + d

From these we determine the sensitivity and specificity as follows:

SENSITIVITY = a/(a+c) > 80%

SPECIFICITY = d/(b+d) > 80%

Neurobiol Aging 1998; 19:109-116.

A clinico-pathoanatomical study of multiple sclerosis diagnosis

SENSITIVITY = True+ve /(True+ve + False-ve)

Eye Department, Hvidovre Hospital, Denmark.

• Neuropathological examination of 518 consecutive patients with clinically definite MS revealed a correct diagnosis in 485 cases (94%).

• Clinical diagnosis had been established by a neurologist in all cases.

• Erroneous diagnosis included a variety of other neurological disorders.

• Also investigated was a randomly selected series of 33 patients with a clinical diagnosis of probable MS:

– post mortem confirmation of MS was obtained in circa 66%.

– The remainder the error pattern was similar to the above.

Engell T. Acta Neurol Scand. 1988 Jul;78(1):39-44.

Kleinschmidt-DeMasters,et al. N Engl J Med. 2005 Jul 28;353(4):369-74.

PML complicating treatment with natalizumab and IFNb-1a for MS

A clinico-pathoanatomical study of multiple sclerosis diagnosis

SPECIFICITY = True-ve /(True-ve + False+ve) ?

~25% of cases of MS are undiagnosed in life (asymptomatic or benign cases)

Engell T. Acta Neurol Scand. 1989 May;79(5):428-30.

Other diagnoses - MRI white matter changes

• ADEM

• NMO

• Ageing

• Behcet’s syndrome

• Cerebrovascular disease

• Decompression sickness

• Fat embolism

• HIV encephalitis

• HTLV1-associated myelopathy

• Hydrocephalus

• Irradiation

• Leukodystrophies

• Migraine

• Mitochondrial encephalopathy

• MND

• Neurosarcoidosis

• Phenylketonuria

• PML

• SSPE

• SLE/APL

• Trauma

Miller DH. (1997)

Module Identifier

Question: What types of MS do they have?

Lublin FD, Reingold SC. Defining the clinical course of multiple sclerosis: results of an international survey. National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis. Neurology. 1996 Apr;46(4):907-11.

RRMS R-SPMS/NR-SPMS PPMS RPMS

relapsing forms of MS vs. non-relapsing MS

Question: What prognostic group do you fall into?

Good prognosis Poor prognosis

Young

Female sex

Optic neuritis

Isolated sensory symptom

Full recovery from attack

Long interval to second

relapse

No disability after 5 years

Normal MRI / low lesion load

CSF negative for OCBs

Older age of onset

Male sex

“Multifocal“ onset

Efferent system affected (motor,

cerebellar, bladder)

High relapse rate in the first 2-5 years

Substantial disability after 5 years

Abnormal MRI with large lesion load

CSF positive for OCBs

Adapted from Miller et al., Lancet Neurology 2005: 4; 281-288

Question: What prognostic group do you fall into?

Favourable

Indeterminate

Poor

time Aim of

treatment

Question: What is the risk of not having any treatment?

MS is one of the most common causes of neurological disability in young adults2

Natural history studies indicate that it takes a median time of 8, 20 and 30 years to reach the irreversible disability

levels of EDSS 4, 6 and 7, respectively3

Up to 75% increased annualized divorce rate4

Life expectancy is reduced by 5-10 years5

7.5x greater than suicide rate than the general population6

2 out of 3 patients with RRMS were unemployed due to the disease7

Utilit

y

EDSS Status

EDSS and utilitya show a significant inverse relationship1,b

aUtility measures are derived from EQ-5D using the EuroQoL instrument. bAdapted from Orme et al 2007. Error bars depict 95% confidence intervals. Half points on EDSS are not shown on graph axis, except at EDSS 6.5.

1.Orme M et al. Value In Health. 2007;10:54-60. 2.WHO. 2008.[TK] 3. Confavreaux, Compston. 2005.[TK] 4. Coles et al. 2001.[TK] 5. Confavreaux, Vukusic. 2006.[TK] 6. Sadovnick et al. Neurology 1991;41:1193-6.

7. Morales-Gonzales. Mult Scler. 2004;10:47-54.

Consequences of increasing EDSS scores: loss of employment1

0

10

20

30

40

50

60

70

80

90

Work Capacity by Disability Level

0.0/1.0 2.0 3.0 4.0 5.0 6.0 6.5 7.0 8.0/9.0

EDSS Score

Pro

po

rtio

n o

f P

ati

en

ts ≤

65

Ye

ars

Old

Wo

rkin

g (

%)

The proportion of patients employed or on long-term sick leave is calculated as a percentage of patients aged 65 or younger.

1. Kobelt G et al. J Neurol Neurosurg Psychiatry. 2006;77:918-926;

2. Pfleger CC et al. Mult Scler. 2010;16:121-126.

Spain

Sweden

Switzerland

United Kingdom

Netherlands

Italy

Germany

Belgium

Austria

~10 yrs2

www.ms-res.org

Question: Do you have active MS?

vs.

1

2

3

Clinical

MRI

Biomarkers

Question: Are they eligible for treatment with a DMT?

MSer

Neurologist

Payers

Regulator

Relapsing-MS

Active Inactive Highly-active Rapidly-evolving severe

Active Inactive HA RES

Treatment Selection & treating-2-target

Choosing therapy

X Y Z

Define the Individual’s MS

No

Treatment failure? Yes

• Patient’s preferences?

• Your choice?

Individual measures:

• Evidence of disease activity?

• Tolerability/safety?

• Adherence?

• Drug or inhibitory markers?

Monitoring

• MS prognosis

• Life style and goals

• Shared goals for therapy

Rebaseline

Rebaseline:

• IFNβ, natalizumab, fingolimod,

teriflunomide, DMF=3-6 months

• Glatiramer acetate=9 months

• Alemtuzumab=24 months

DMF=dimethyl fumarate.

Gd

T2

CU

R

DP

15% vs 47% Δ 32%

13% vs 68% Δ 55%

6% vs 37% Δ 31%

Effect of natalizumab on clinical and radiological disease activity in MS: a retrospective analysis of the

Natalizumab Safety and Efficacy in Relapsing-Remitting MS (AFFIRM) study

Havrdova et al. Lancet Neurol. 2009 Mar;8(3):254-60.

Treatment Ladder

1st-line A

1st-line B

1st-line C

1st-line D

1st-line E

2nd-line N

2nd-line M

3rd-line y

3rd-line X

MS is an autoimmune disease hypothesis

15-20 year experiment

“hit hard and early ”

Question: Do you understand the difference between the treatment strategies of maintenance and escalation and induction therapy?

What is your treatment philosophy? maintenance-escalation vs. induction

survival analysis

In MS, patients with long gaps in treatment are at greater risk of relapse than more adherent patients1

Lower adherence to MS therapy is associated with a higher risk of relapse2

Treatment gaps and poor adherence are associated with increased relapse rates

Good adherence

is the key to

optimizing

outcomes

1. Al-Sabbagh A et al. J Neurol 2008;255(Suppl. 2):S79 2. Steinberg SC et al. Clin Drug Invest 2010;30:89-100. Copyright © 2010, Adis Data Information BV MPR, Medication Possession Ratio

Comparison of relapse risk ratios by level of adherence in patients with MS2

80 <80 <75 <70 <65 <60 0.90

0.95

1.00

1.05

1.10

1.15

Rel

apse

ris

k ra

tio

MPR (%)

Forgetfulness is a primary cause of non-adherence

Pain at injection site

Not confident in treatment benefits

Other

Headache

Skin reaction

Depression

Financial reasons

Forgot to administer

Flu-like symptoms

Injection anxiety

Dosing schedule difficult/inconvenient

Weakness

Did not pick up medicine

Nobody available to administer

Pregnancy/planned pregnancy

Did not feel need for injection

Tired of taking injections

Fatigue

50%

20%

17%

15%

13%

12%

10%

10%

10%

9%

8%

6%

5%

4%

3%

2%

2%

1%

0 20 40 60 Patients (%)

Re

aso

ns

for

mis

sin

g o

ne

or

mo

re in

ject

ion

s

Psychological factors

– forgetfulness and

complacency – impact

adherence

Observational GAP study

Devonshire V et al. Eur J Neurol 2011;18:69-77 Patients could have reported more than one reason for non-adherence. When counting injection-related reasons for non-adherence, each patient was counted only once. GAP, Global Adherence Project

No evident disease activity: NEDA

Gd, gadolinium. 1. Havrdova E, et al. Lancet Neurol 2009; 8:254–260; 2. Giovannoni G, et al. Lancet Neurol 2011; 10:329–337.

Treat-2-target

No evidence of disease activity defined as:1,2

× No relapses

× No sustained disability progression

× No MRI activity

× No new or enlarging T2 lesions

× No Gd-enhancing lesions

Bermel et al. Ann Neuol 2012.

Predictors of long-term outcome in

MSers treated with interferon beta-1a

MRI to monitor treatment response to IFNβ: a meta-analysis

Dobson et al. Neurology 2013.

Study or Subgroup Odds Ratio

IV, Random, 95% CI

Kinkel 2008

Prosperini 2009

Total (95% CI) 9.86 (2.33, 41.70)


IV, Random, 95% CI

Kinkel 2008

Pozzilli 2005

Prosperini 2009

Sormani 2011

Total (95% CI) 2.69 (0.72, 10.04)

0.01 0.1 1 10 100 Disease Less Likely Disease More Likely

One New T2 Lesion

Favors Experimental Favors Control

100 10 1 0.1 0.01

Two or More New T2 Lesions


IV, Random, 95% CI

Kinkel 2008

Rio 2008

Total (95% CI) 5.46 (2.48, 12.04)

MRI to monitor treatment response to IFNβ: a meta-analysis


IV, Random, 95% CI

Kinkel 2008

Pozzilli 2005

Tomassini 2006

Total (95% CI) 3.34 (1.36, 8.22)

0.01 0.1 1 10 100 Disease Less Likely Disease More Likely

One New Gd+ Lesion

0.01 0.1 1 10 100

Disease Less Likely Disease More Likely

Two or More New Gd+ Lesions

Dobson et al. Neurology 2013.

Strongest predictor of disability progression on

IFNβ therapy is progression itself

Disease activity during 2 years of treatment and prediction of disability progression* at 6 years

Group Sensitivity (%)

(CI) Specificity (%)

(CI)

A. An increase of at least one EDSS step confirmed at 6 months 85 (64–95) 93 (86–97)

B. Occurrence of any relapse 80 (58–92) 51 (41–61)

C. Occurrence of two or more relapses 45 (26–66) 81 (72–82)

D. A decrease in relapse rate less than 30% compared with 2 years before therapy

40 (22–61) 86 (77–91)

E. A decrease in relapse rate less than 50% compared with 2 years before therapy

40 (–61) 81 (72–88)

F. No decrease or identical relapse rate compared with 2 years before therapy

35 (18–57) 88 (79–93)

G. Definition A or B 90 (70–97) 48 (38–58)

H. Definition A or E 85 (64–95) 76 (66–83)

I. Definition A and B 75 (53–89) 97 (91–99)

J. Definition A and E 40 (22–61) 99 (94–99)

*EDSS score ≥6.0 or increase in at least 3 EDSS steps.

Río J et al. Ann Neurol. 2006;59:344-352.

NEDA is a sensitive outcome

1.87

5.29

2.75

2.92

3.41

1.64

2.29

0 1 2 3 4 5 6

Dimethyl fumarate (DEFINE)

Natalizumab (AFFIRM)

Cladribine (CLARITY)

Fingolimod (FREEDOMS)

sc IFN β-1a (DoF)

Teriflunomide (TEMSO)

Alemtuzumab (CARE MS II)

Increase in proportion of NEDA patients relative to comparator

Patients with RRMS over 2 years. Increase in proportion of patients with NEDA versus placebo (except CARE MS II)

All data from post hoc analyses of randomized controlled trials in patients with RRMS. Table adapted from Bevan CJ and Cree BA. JAMA Neurol 2014;71:269-70, with the exception of: TEMSO. Freedman et al. Neurology 2012;78 [Meeting

Abstract s 1]: PD5.007; sc IFN b1-a sc. Data on file; CARE MS II. Coles AJ et al. Lancet 2012;380:1829-39

versus sc IFN b-1a

Slide courtesy Prof. Mark Freedman, EFNS-ENS Istanbul 2014

The modified Rio score can predict disability progression and response to IFN-β therapy

*No qualifying relapses or confirmed EDSS progression; †Percentage calculated using total number of patients with a particular modified Rio score at Week 48; ‡No clinical activity, gadolinium-enhancing lesions, or new/enlarging T2 lesions. EDSS, Expanded Disability Status Scale

Outcomes after 1 year of IFN-β treatment Modified Rio score

≤5 new T2 lesions and 0 relapses 0

≤5 new T2 lesions and 1 relapse, or >5 new T2 lesions and 0 relapses 1

≤5 new T2 lesions and ≥2 relapses, or >5 new T2 lesions and 1 relapse 2

>5 new T2 lesions and ≥2 relapses 3

Higher modified Rio score predicts greater risk of progression1

Modified Rio score at Week 48 (REGARD)

Clinical activity-free* at Week 96 n (%)†2

Disease activity-free at Week 96 n (%)‡2

Yes No Yes No

0 (n=156) 121 (77.6) 35 (22.4) 53 (34.0) 103 (66.0)

1 (n=42) 3 (7.1) 39 (92.9) 0 42 (100)

2 (n=5) 0 5 (100) 0 5 (100)

Total (N=203) 124 79 53 150

Wo

rse

nin

g d

ise

ase

1. Sormani MP et al. Mult Scler J 2013;19:605-12 2. Freedman M et al. Mult Scler J 2013;19(Suppl. 1):262 [P610]


*As measured by modified Rio score. EDSS, Expanded Disability Status Scale; RRMS, relapsing–remitting MS; tiw, three times weekly

Faster disability progression seen in patients with worse Rio-defined disease activity*

Kaplan–Meier cumulative incidence curves of time to confirmed EDSS progression by modified Rio score in patients with RRMS receiving sc IFN β-1a 44 µg tiw

156 42

155 41

151 39

144 33

138 27

No. of patients at risk: Rio score 0 Rio score 1

Baseline Week 24 0.0

0.1

0.2

Cu

mu

lati

ve in

cid

en

ce

0.3

0.4

0.5

Week 48 Week 72 Week 96

O (n=156) 1 (n=42)

Rio score group

Time to 3-month EDSS confirmed progression

Freedman M et al. Mult Scler J 2013;19(Suppl. 1):262 [P610]


Relapses

Unreported relapses

Clinical disease progression

Subclinical relapses: focal MRI activity

Focal gray and white matter lesions not detected by MRI

Brain atrophy

Spinal fluid neurofilament levels

MS Iceberg

Clinical activity

Focal MRI activity

Hidden focal and diffuse MRI activity

Microscopic or biochemical pathology

Biomarkers

Control Multiple sclerosis

Brain atrophy occurs across all stages of the disease

De Stefano, et al. Neurology 2010

n= 963 MSers

Treatment effect on disability predicted by effect on T2-lesion load and brain atrophy

Meta-analysis of treatment effect on EDSS worsening (y) vs effects on MRI lesions

and brain atrophy, individually or combined, in 13 placebo-controlled RRMS trials

(13,500 patients)

Sormani MP et al. Ann Neurol. 2014;75:43-49.

-1.0%

-0.8%

-0.6%

-0.4%

-0.2%

0.0% Years 0-2

-0.82%

-0.80%

P=0.822†

Placebo (N=315) Natalizumab (N=627)

Year 0-1* Year 1-2

-0.40%

-0.56%

-0.43%

-0.24%

P=0.004†

P=0.002†

†Difference between treatments; ‡Change from baseline; Miller DH et al. Neurology 2007;68:1390-1401.

AFFIRM Study: natalizumab and brain atrophy

Mean

(S

E)

perc

en

tag

e c

han

ge i

n B

PF

Fingolimod has an early and sustained effect on the rate of brain atrophy compared with placebo and IFNb-1a IM

FREEDOMS, 2 years

Fingolimod 0.5 mg (n = 356)

Placebo (n = 329)

***

*

**

6 0 12 24

Time (months)

0

-0.4

-0.8

-1.2

-1.6

-2.0

−38%

vs placebo p<0.001

Ch

ange

in m

ean

BV

fro

m

bas

elin

e (%

)

TRANSFORMS, 1 year

0 12

Time (months)

0.0

-0.4

-0.6

-1.0

IFNb-1a IM (n = 359)

Fingolimod 0.5 mg (n = 368)

−40%

vs IFNb-1a IM p<0.001

*** -0.2

-0.8

Ch

ange

in m

ean

BV

fro

m

bas

elin

e (%

)

ITT population with evaluable MRI images. Note: n numbers for FREEDOMS data reflect the number of patients with available data at 24 months. *p<0.05; **p<0.01; ***p<0.001 vs comparator; p-values are for comparisons over Months 0-6, Months 0-12, Months 0-24 BV, brain volume; ITT, intent-to-treat. Gilenya™ Prescribing Information 19 April 2012. Reproduced with permission. Kappos L et al. N Engl J Med 2010; 362: 387-401, and Cohen JA et al. N Engl J Med 2010; 362: 402-415. Copyright © 2011 Massachusetts Medical Society. All rights reserved

Reduction in brain atrophy on alemtuzumab

Case studies

38-year-old teacher with relapsing–remitting MS under the care of a hospital in central London Glatiramer acetate treatment for 3 years (good adherence and tolerance) Relapse with a mild left sensory loss Referred to me for a second opinion Switched to interferon β (intramuscular interferon β-1a; www.msdecisions.org.uk) Mild persistent flu-like side effects and lymphopenia 12/12’s neutralizing antibodies screen negative Volunteers for new research programme, which included a gadolinium-enhanced MRI protocol

Teacher

38-year-old teacher with relapsing–remitting MS As a result of fatigue and cognitive problems she is forced to take

early retirement Although fully functional she develops depression and anxiety In her spare time she spends a lot of time on the web and becomes

an expert patient Widely read

Net savvy; regular follower of www.ms-res.org

Teacher X

Teacher X

Rheumatoid arthritis End-stage joint disease

Conclusions

MS is a bad disease – Mortality, disability, unemployment, divorce, suicide

cognitive impairment, etc.

Era of individualised profiling – Prognosis, risk, treatment and monitoring

New treatment paradigm – Therapeutic ladder

– Maintenance vs. induction therapy

– Improved risk mitigation tools

– New treatment paradigm of treat-2-target of NEDA or no evidence of disease activity

– Future target to prevent organ damage

Treating ms in 2014 giovannoni gg4

Health & Medicine

Transcript of Treating ms in 2014 giovannoni gg4