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GAVIN GIOVANNONI BARTS and THE LONDON Early Clinical Predictors for Long- Term Prognosis: Goals of Therapy 1

Early clinical predictors giovannoni berlin 4 5 may 2013

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Page 1: Early clinical predictors giovannoni berlin 4 5 may 2013

GAVIN GIOVANNONI BARTS and THE LONDON

Early Clinical Predictors for Long-

Term Prognosis: Goals of Therapy

1

Page 2: Early clinical predictors giovannoni berlin 4 5 may 2013

2

Page 3: Early clinical predictors giovannoni berlin 4 5 may 2013

How serious a disease

is multiple sclerosis?

3

Page 4: Early clinical predictors giovannoni berlin 4 5 may 2013

Lifespan in MS Patients Is Shortened by 8 to 12 Years

• Survival probability of Norwegian patients with relapsing-remitting MS (RRMS)

(Hordaland County, Western Norway, 1953–2003)

4

RRMS % s

urv

ival

MS=multiple sclerosis; CI=confidence interval.

Page 5: Early clinical predictors giovannoni berlin 4 5 may 2013

Population-Based MS Mortality Studies

First Author

Population

and Time Period

Size

of Cohort

Standardized

Mortality Ratio Additional Survival Measures

GryttenTorkildsen

Mult Scler 2008

Western Norway

1953–2003 878

2.66

(95% CI: 2.31–3.06)

• Median survival time from onset: 41 years MS vs 49 years general population

− 8 years life lost in MS

Smestad

Mult Scler 2009

Oslo

1940–1980 368

2.47

(95% CI: 2.09–2.90)

• Reduction of median life expectancy vs general population

− Female: 11.2 years

− Male: 7.4 years

Bronnum-Hansen

Brain 2004

Danish MS Registry

1949–1996 9881

2.89

(95% CI: 2.81±2.98)

• Median survival time (from disease onset) vs general population:

− ≈10 years life lost in MS

Hirst

JNNP 2008

South Wales

1985–2006 373

2.79

(95% CI: 2.44 to 3.18)

• Median age of death: 63.1 years MS vs 70.6 years general population

− 7.5 years life lost in MS

Sumelahti

Mult Scler 2010

Finland

1964–1993 1595

2.8

(95% CI: 2.6–3.1)

• Survival decreases with disease progression

− SMR, 2–9.9 years after diagnosis: 2.4

− SMR, ≥10 years after diagnosis: 3.1

Wallin

Brain 2000

USA

1956–1996 2489

2.18

(Not specified)

• Healthy soldier effect speculated to have a

favorable effect on survival

Leray

Mult Scler 2007

West France

1976–2004 1879

1.3

(95% CI: 1.01–1.7)

• Mean follow-up duration=12.7 years from

clinical onset; may be basing estimate on

relatively immature dataset

5

SMR=standardized mortality ratio.

Page 6: Early clinical predictors giovannoni berlin 4 5 may 2013

The Survival Disadvantage in MS Is Greater Than in

Some Other Chronic Diseases Standardized Mortality Ratios in Chronic Diseases

6

Disease SMR (RANGE)

Cardiovascular disease1* 1.34 (1.23–1.44)

Ischemic stroke2† 1.75(1.38–2.19)

Early breast cancer3 2.0 (1.6–2.7)

Crohn’s disease4 2.8

MS5 2.8 (2.6–3.1)

MS (2–9.9 years after diagnosis)5 2.4 (1.9–2.9)

MS (≥10 years after diagnosis)5 3.1 (2.8–3.4)

Parkinson’s disease6 3.66 (3.37–3.95)

Type 2 diabetes1 4.47 (3.91–5.10)

*In patients with type 2 diabetes; †in patients with valvular heart disease in Olmsted County, Minnesota.

1. De Marco R et al Diabetes Care. 1999;22:756-761; 2. Petty GW et al. Mayo Clin Proc. 2005;80:1001-1008; 3. Hooning MJ et al. Int J Radiat Oncol Biol Phys.

2006;64:1081-1091; 4. South East England Public Health Observatory, Mortality trends. 2006; 5. Sumelahti ML et al. Mult Scler. 2010;16:1437-1442;

6. Hristova DR. Folia Medica. 2009;51:40-45.

Page 7: Early clinical predictors giovannoni berlin 4 5 may 2013

21-Year Long-term Follow-up of IFNβ-1b Study Time

From Study Randomization to Death

Early treatment (3 years) with IFNβ-1b was associated with a 47% reduction

in the risk of dying over 21 years compared with initial placebo treatment

IFNβ=interferon beta; HR=hazard ratio.

Source: Goodin et al Neurology. 2012;78:1315–1322.

At risk:

IFNβ-1b 250 µg

Placebo

124

123

124

120

121

117

118

109

104

88

HR=0.532 (95% CI: 0.314–0.902)

46.8% reduction in hazard ratio

Log rank, P=0.0173

IFNB-1b 250 µg

Placebo

65%

70%

75%

80%

85%

90%

95%

100%

0 2 4 6 8 10 12 14 16 18 20 22

Pro

po

rtio

n o

f p

ati

en

ts w

ho

are

sti

ll a

live

Time (Years)

7

Page 8: Early clinical predictors giovannoni berlin 4 5 may 2013

Uti

lity

EDSS Status

EDSS and utility* show a significant

inverse relationship1,†

*Utility measures are derived from EQ-5D using the EuroQoL instrument; †error bars depict 95% confidence intervals. Half points on

EDSS are not shown on graph axis, except at EDSS 6.5.

EDSS=Expanded Disability Status Scale; WHO=World Health Organization; MSIF=Multiple Sclerosis International Federation.

1. Adapted from Orme M et al. Value In Health. 2007;10:54-60. 2. WHO and MSIF.

http://apps.who.int/bookorders/anglais/detart1.jsp?sesslan=1&codlan=1 &codcol=15&codcch=747. Accessed October 6, 2010.

3. Confavreaux, Compston. McAlpine’s multiple Sclerosis. 4th edn. Churchill Livingstone Elsevier; 2006. p. 183–272. 4. Compston A,

Coles A. Lancet 2008; 372:1502-1517.

• 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

The Effect of MS on Quality of Life

8

Page 9: Early clinical predictors giovannoni berlin 4 5 may 2013

The Effects of MS on Unemployment

9

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

Page 10: Early clinical predictors giovannoni berlin 4 5 may 2013

Healthcare Costs Are Linked to Disability

10

Costs are given in € (euros).

OTC=over-the-counter.

Berg J et al. Eur J Health Econ 2006;7(Suppl 2):S75−85.

Total mean annual cost per patient €53,601

Informal care

(disposable income)

(9.2)

Ambulatory care

(5.6)

Disease-modifying

drugs (10.6)

Other prescription and

OTC drugs (1.6)

Tests (0.4)

Investments (2.0)

Long-term sick leave and

early retirement (30.0)

Short-term absence

(2.0)

Services

(28.5)

Inpatient care

(10.2)

Page 11: Early clinical predictors giovannoni berlin 4 5 may 2013

The Effects of MS on Divorce and Separation

11

Pfleger CC et al. Mult Scler. 2010;16:878-882

Page 12: Early clinical predictors giovannoni berlin 4 5 may 2013

CIS Patients

n = 40

Impact of MS: Cognitive Functioning in the CIS Stage

Cognitive Test Performance in an Exploratory Study*

12

57%

7%

-20%

0%

20%

40%

60%

*40 untreated CIS patients who fulfilled the McDonald dissemination in space criterion compared to a cohort of 30 matched healthy

controls. An extensive battery of neuropsychological tests was used to explore verbal and non-verbal memory, attention, concentration,

speed of information processing, language and abstract reasoning. Cognitive impairment was present when at least 2 different

neuropsychological tests were failed.

CIS=clinically isolated syndrome.

Feuillet l et al. Mult Scler. 2007;13:3124-127.

Healthy Controls

n = 30

p < 0.0001

Deficits were found mainly in

memory, speed of information

processing, attention, and

executive functioning

Pati

en

ts f

ailin

g

≥2 c

og

nit

ive t

ests

Page 13: Early clinical predictors giovannoni berlin 4 5 may 2013

What Is Benign MS?

13

163 patients with “benign” MS

(disease duration >15 years and

EDSS <3.5):

1. 45% cognitive impairment

2. 49% fatigue

3. 54% depression

Page 14: Early clinical predictors giovannoni berlin 4 5 may 2013

Prognostic factors

14

Page 15: Early clinical predictors giovannoni berlin 4 5 may 2013

Clinical Prognostic Factors

Good Prognosis

• Optic neuritis

• Isolated sensory symptoms

• Long interval to

second relapse

• No disability after

5 years

• Normal MRI or low lesion load

Poor Prognosis

• Multifocal CIS

• Efferent systems affected

• High relapse rate in first 2–5

years

• Substantial disability after 5

years

• Abnormal MRI with large lesion

load

MRI=magnetic resonance imaging.

Miller D et al. Lancet Neurol. 2005;4:281-288.

15

Page 16: Early clinical predictors giovannoni berlin 4 5 may 2013

0

20

40

60

80

100

0 5 10 15 20

Pa

tie

nts

Co

nve

rtin

g t

o C

DM

S (

%)

Years

0 Lesions

1–3 Lesions

4–10 Lesions

>10 Lesions

Baseline Number of Brain Lesions Predicts

Conversion to CDMS

16

The data presented for years 5, 10, 14, and 20 were obtained from different publications based on the same longitudinal study.

The exact relationship between MRI findings and the clinical status of the patient is unknown.

CDMS=clinically definite MS.

Fisniku LK et al. Brain. 2008;131:808-817; Morrissey SP et al. Brain. 1993;116:135-146; O’Riordan JI et al. Brain. 1998;121:495-503;

Brex PA et al. N Engl J Med. 2002;346:158-164; Tintore M et al. Neurology. 2006;67:968-972.

Cu

mu

lati

ve

Pro

ba

bilit

y D

eve

lop

ing

CD

MS

0

0.2

0.4

0.6

0.8

1.0

0 12 24 36 48 60 72 84 96 108 120

Time Since First Attack (months)

0 Lesions

4–9 Lesions

No. of Lesions at Baseline

≥10 Lesions

1–4 Lesions

No. of Lesions at Baseline

Queen Square Study Tintore Study

Page 17: Early clinical predictors giovannoni berlin 4 5 may 2013

0

10

20

30

40

50

60

70

80

0 5 10 15 20

Pa

tie

nts

Co

nve

rtin

g t

o E

DS

S ≥

3.0

(%

)

Years

0 Lesions

1–3 Lesions

4–10 Lesions

>10 Lesions

The data presented for years 5, 10, 14, and 20 were obtained from different publications based on the same longitudinal study.

The exact relationship between MRI findings and the clinical status of the patient is unknown.

Fisniku LK et al. Brain. 2008;131:808-817; Morrissey SP et al. Brain. 1993;116:135-146; O’Riordan JI et al. Brain. 1998;121:495-503;

Brex PA et al. N Engl J Med. 2002;346:158-164; Tintore M et al. Neurology. 2006;67:968-972.

Baseline Number of Brain Lesions Predicts

Progression to EDSS Score ≥3.0

17

Cu

mu

lati

ve

Pro

ba

bilit

y R

ea

ch

ing

ED

SS

3.0

0.0

0.2

0.4

0.6

0.8

1.0

0 12 24 36 48 60 72 84 96 108 120

Time Since First Attack (months)

0 lesions

Queen Square Study Tintore Study

0 Lesions

4–9 Lesions

No. of Lesions at

Baseline

≥10 Lesions

1–4 Lesions

No. of Lesions at Baseline

Page 18: Early clinical predictors giovannoni berlin 4 5 may 2013

Presence of Infratentorial Lesions Increases the

Risk for Disability

18

Tintoré M et al. Neurology 2010; 75:1933-1938.

Basal MR

in CIS

Page 19: Early clinical predictors giovannoni berlin 4 5 may 2013

Relapses Can Result in Residual Deficits

• MS exacerbations can produce a measurable and sustained effect

on accrued impairment and disability1

• Therefore, treatments that reduce the frequency of relapses should

be beneficial

19

1. Lublin FD et al. Neurology. 2003;61:1528-1532.

27 29 30

42 44 41

0

10

20

30

40

50

30–59 60–89 ≥90

Pati

en

ts (

%)

Days After Exacerbation

Patients (%) with a ≥1.0 or ≥0.5 Change in EDSS Score After Relapse

≥1.0 EDSS Point

≥0.5 EDSS Point

Adapted from Lublin et al 2003.

Page 20: Early clinical predictors giovannoni berlin 4 5 may 2013

Treatment strategy

20

Page 21: Early clinical predictors giovannoni berlin 4 5 may 2013

Theoretical Model: Treat Early and Aggressively

21

Time

Disease Onset

Treatment

at diagnosis

Natural course

of disease

Later intervention

Intervention

at diagnosis

Dis

ab

ilit

y

Later

treatment

Page 22: Early clinical predictors giovannoni berlin 4 5 may 2013

Prognostic Factors on Treatment

Response to Therapy

22

Page 23: Early clinical predictors giovannoni berlin 4 5 may 2013

Breakthrough Disease After Treatment Initiation

• Patients with breakthrough disease can be identified with

• Clinical measures

• Relapses

• EDSS progression

• MRI measures

• T2 and Gd+ lesions

• Biological markers

• IFNβ neutralizing antibodies (NAbs)/lack of MxA induction

• Anti-natalizumab Abs

23

Gd+=gadolinium-enhancing; MxA=myxovirus protein; Ab=antibody.

Page 24: Early clinical predictors giovannoni berlin 4 5 may 2013

Relapse on IFNβ Therapy Increases Risk of

Sustained Disability Progression

• Risk is not much greater for 2 or more relapses

• Sensitivity is only 50%

24 SE=standard error.

Bosca I et al. Mult Scler. 2008;14:636-639.

HR SE P Value 95% CI

No relapses

(reference=1) 1

One relapse 3.41 1.47 0.005 1.46–7.98

Two or more relapses 4.37 1.74 0.000 1.90–9.57

HR of EDSS Increase in Patients with No Relapses, 1 Relapse, and 2 or More Relapses During the First

2 Years of IFN Treatment

Page 25: Early clinical predictors giovannoni berlin 4 5 may 2013

One New T2 Lesion

2 or More New T2 Lesions

Dobson et al. unpublished data.

MRI to Monitor Treatment Response to IFNβ: a

Systematic Review

25

Page 26: Early clinical predictors giovannoni berlin 4 5 may 2013

MRI to Monitor Treatment Response to IFNβ: a

Systematic Review (cont.)

26

One New Gd+ Lesion

2 or More Gd+ Lesions

Dobson et al. unpublished data.

Page 27: Early clinical predictors giovannoni berlin 4 5 may 2013

Predictors of Long-term Outcome in Multiple Sclerosis

Patients Treated with IFNβ

27

Bermel RA et al. Ann Neurol. 2013;73:95-103.

Page 28: Early clinical predictors giovannoni berlin 4 5 may 2013

Predictors of Long-term Outcome in Multiple Sclerosis

Patients Treated with IFNβ (cont.)

28

Bermel RA et al. Ann Neurol. 2013;73:95-103.

Page 29: Early clinical predictors giovannoni berlin 4 5 may 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

29

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 (22-61) 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 ≥6.0 or increase in at least three EDSS steps.

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

Page 30: Early clinical predictors giovannoni berlin 4 5 may 2013

Clinical Importance of Neutralizing Antibodies Against

IFNβ in Patients with RRMS

30

Sorensen PS et al. Lancet. 2003;362:1184-1191.

Page 31: Early clinical predictors giovannoni berlin 4 5 may 2013

Mean Change in EDSS

31

Malluci S et al. Neurology. 2004;62:2031-2037.

Page 32: Early clinical predictors giovannoni berlin 4 5 may 2013

The Incidence and Significance of Anti-Natalizumab

Antibodies: Results from AFFIRM and SENTINEL

Ab−=antibody negative; Ab+=antibody positive.

Calabresi P et al. Neurology. 2007;69:1391-1403. 32

Placebo

Ab–

Transiently Ab+

Persistently Ab+

315

568

20

37

296

550

19

32

283

538

18

26

264

526

16

25

248

506

16

24

240

487

16

22

229

480

15

22

216

470

14

16

208

460

14

16

200

449

14

15

Number at Risk

0 12 24 36 48 60 72 84 96 108 120

Week

0

0.1

0.2

0.3

0.4

0.5

Cu

mu

lati

ve

Pro

po

rtio

n o

f P

ati

en

ts

wit

h S

us

tain

ed

Dis

ab

ilit

y P

rog

res

sio

n

(ED

SS

)

17%

Placebo

Ab–

Transiently Ab+

Persistently Ab+

17%

29%

34%*†

*P≤0.05 vs Ab– patients; †P=0.66 vs placebo

Page 33: Early clinical predictors giovannoni berlin 4 5 may 2013

The Incidence and Significance of Anti-Natalizumab

Antibodies: Results from AFFIRM and SENTINEL (cont.)

33

Values are n (%).

*P<0.05 vs persistently Ab+; †P<0.01 vs persistently Ab+; ‡P<0.001 vs persistently Ab+.

Calabresi P et al. Neurology. 2007;69:1391-1403.

Ab–

(n=568)

Transiently Ab+

(n=20)

Persistently Ab+

(n=37)

Natalizumab monotherapy

Headache 4 (24)† 0* 19 (7)

Urticaria <1 (4)‡ 5 (1) 14 (5)

Nausea 1 (8)‡ 0 16 (6)

Rigors <1 (1)‡ 0 11 (4)

Natalizumab add-on therapy (n=515) (n=32) (n=38)

Rigors <1 (1)‡ 0‡ 29 (11)

Nausea 1 (7)‡ 0* 18 (7)

Headache 4 (20)* 3 (1) 13 (5)

Pruritus ≤1 (4)† 3 (1) 11 (4)

Flushing ≤1 (3)‡ 0 13 (5)

Urticaria ≤1 (2)‡ 0 13 (5)

Tachycardia 0‡ 0 11 (4)

Dizziness 3 (15) 0 8 (3)

Pyrexia <1 (3)† 0 8 (3)

Incidence of Common Infusion-Related Adverse Events by Antibody Status in AFFIRM and SENTINEL

Page 34: Early clinical predictors giovannoni berlin 4 5 may 2013

Emerging concepts in MS

NEDA; no evidence of disease activity

TTT; treat-to-target

Page 35: Early clinical predictors giovannoni berlin 4 5 may 2013

Treat-2-target

No Evidence of Disease Activity

Page 36: Early clinical predictors giovannoni berlin 4 5 may 2013

Treat-2-Target Proposed NEDA* Treatment Algorithm for

Relapsing MS

36

NEDA=no evidence of disease

activity.

Page 37: Early clinical predictors giovannoni berlin 4 5 may 2013

Conclusions

• MS is a bad disease

• Disability (physical and cognitive)

• High societal costs (unemployment, healthcare costs, divorce)

• Survival compromised

• Treat early and aggressively

• Prognostic factors

• Clinical findings, MRI activity, OCBs, and other emerging biomarkers

• Treatment response markers

• Clinical (relapses and disability progression)

• MRI (T2 and Gd+ lesions)

• NAbs (efficacy and safety)

• Treat-2-Target

• NEDA

37

OCB=oligoclonal band.