Primary Progressive MS. Predicting Progression. Alan J Thompson Director, UCL Institute of Neurology Queen Square

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1 Primary Progressive MS Predicting Progression Alan J Thompson Director, UCL Institute of Neurology Queen Square

2 Disclosures Alan J Thompson UCL Institute of Neurology Queen Square London, UK In compliance with the Continuing Medical Education (CME) guidelines of the European Accreditation Council for Continuing Medical Education (EACCME), I declare receipt of honoraria/consultation fees from Eisai London Research Labs (advisory board member); receipt of fees and support for travel from Novartis Pharma (PPMS Steering Group member); receipt of honoraria and support for travel from Sanofi- Aventis, Serono Symposium (invited lectures); to be a consultant for DignaBiotech; to be a member of company advisory board, board of directors or other similar group for Patrick Berthoud Trust (trustee), National Hospital Development Foundation (trustee), MSIF International Medical and Scientific Board (chairman); to benefit from a relationship with a commercial enterprise as Editor-in-Chief, Multiple Sclerosis (honorarium from Sage Publications); member, editorial board for Lancet Neurology (free subscription from Elsevier); editorial board for Current Medical Literature-MS (free subscription from Remedica)

3 Primary Progressive MS Rel/Rem MS 90% Disability Secondary progressive (60%) Primary progressive (10-15%) Progressive relapsing (rare) Progressive from onset Occasional plateaus Temporary, minor improvements allowed Lublin & Reingold 1996

4 Natural History studies Age of onset 40 years (similar to SPMS) Equal sex ratio Variable course - 25% needed assistance to walk at 7.5 years - 25% were walking unaided at 25 years Tremlett et al Neurology 2005 Kremenchutsky et al Brain 2006 Confavreux et al Brain 2006

5 Sex and age at onset in the primary-progressive and relapsing populations (A) Primary -progressive from onset n=352 (B) Relapsing from onset n=2485 Tremlett et al. Neurology 2005

6 Clinical Characteristics Age of onset usually mid-forties Sex ratio equal male and female Tendency to progress in same system Rate of progression similar to SPMS Presentation Paraparesis - 83% Hemiparesis 6% Cerebellar syndrome 9% Brainstem syndrome 1% Visual loss 1% Cognition 1% (MAGNIMS Stevenson et al 2000)

7 Onset symptoms - PPMS versus relapsing onset MS Tremlett et al. Neurology 2005

8 PRIMARY PROGRESSIVE MS Relatively rare but important group Challenging to diagnose with confidence - lacks hallmark of MS Potentially important model of disease progression Considerable individual variability

9 Primary progressive MS: What can be learned from the PROMiSe Trial? (Glatiramer( Acetate in PPMS) Jerry S. Wolinsky,, Lillian Pardo, Yafit Stark, Batya Zak, Shaul Kadosh,, David Ladkani and The PROMiSe Study Group University of Texas Health Science Center Houston TEVA Neurosciences TEVA Pharmaceutical Industries

10 Can you predict disability and thereby identify those more appropriate for therapeutic intervention or enrolment into clinical trials? Clinical studies MRI studies (Disability and Cognition)

11 Clinical features and natural history of PPMS Gender Cottrell et al Brain 1999; 122: Males hatched Time from onset to death was shorter for men (----)

12 Clinical features and natural history of PPMS - Clinical presentation Cottrell et al Brain 1999; 122: Brain stem Motor Sensory cerebellar systems one two three Survival analysis to DSS 10

13 Survival analysis determined by reaching EDSS within ( ) or after (-----) 5 years Cottrell et al Brain 1999; 122:

14 Conclusions Adverse influences Shorter time to reach DSS 3 Three or more neurological systems at onset No apparent influence Age at onset, gender and type of presentation

15 The natural history of primary progressive MS in British Columbia First reported in 2005: 352/2837 (12%) had PPMS Updated in 2009: 552/5779 (10%) had PPMS

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17 Kaplan-Meier curves showing time to (left) and age at (right) sustained EDSS 6.0 by age at disease onset. Patients with a younger age at onset took longer to reach EDSS 6.0, but these patients were also younger when reading EDSS 6.0 Koch et al. Neurology 2009

18 Kaplan-Meier curves showing time to (left) and age at (right) sustained EDSS 6.0 by sensory onset symptoms. Sensory onset symptoms were associated with both a longer time to and a higher age at EDSS 6.0 Koch et al. Neurology 2009

19 IMAGING STUDIES

20 Primary progressive MS

21 Key Questions in Progression in MS What MRI changes correlate with disability? What MRI features predict disability? Insights into underlying mechanisms of progression

22 Primary progressive MS Two studies Established PPMS followed over a long period (10 years) Small cohort of early PPMS patients studied with non-conventional techniques over 5 years Two questions What MRI changes correlate with on-going progression Can we predict progression in PPMS

23 MAGNIMS Study of PPMS 145 patients with PPMS; 5 European centres : Amsterdam, Barcelona, Bordeaux, London, Milan Evaluated at one, two, five and 10 years MRI measures T1, T2 lesion loads Atrophy measures of brain and cervical cord Clinical measures EDSS MS Functional Composite (9HPT,TWT,PASAT)

24 MAGNIMS: Baseline, Years 1 & 2 Increase in T2 lesion load; year I (14.6%), year 2 (23.3%) Decrease in brain volume; year 1 (1.3%), year 2 (1.7%) Decrease in cervical cord area (5.2% and 6.8%) Some worsening in clinical measures No correlation between clinical and MRI changes No predictor of change Baseline EDSS correlated with brain and cord atrophy Stevenson et al 1999, 2000; Ingle et al 2002

25 MAGNIMS 5 year data Involved 122 of initial cohort of 145 patients Mean age 54.7 years Mean disease duration 12.9 years EDSS: 5.6 to 6.1

26 Variability over 5 years EDSS / T2 lesion load

27 Predictors of Progression Clinical change at 5 years was predicted by At baseline: Male gender Low brain volume Two year change in T2 - number of new lesions and increased load Cord volume (reduced)

28 MAGNIMS 10 Years (5 European centres) Baseline 2 yrs 5 yrs 10 years Number of 145 patients (70%) Assess ment Imaging EDSS EDSS EDSS Imaging EDSS MSFC

29 RESULTS Clinical progression over ten years predicted by: Baseline: Male gender (0.039), shorter disease duration (0.02) Poorer score on TWT (0.001), NHPT (0.014) Lower brain volume (0.08) Over 2 years: EDSS deterioration (0.006) Reduction in brain volume (0.031) Greater number of T2 lesions (0.039)

30 Early PPMS 50 patients with PPMS Within five years of symptom onset EDSS Scanned over two sessions at baseline MRI and clinical assessment every six months for three years and at five years

31 MRI data acquired Axonal loss/oedema Neuronal viability/ membrane synthesis T1 Inflammation/gliosis T2 Inflammation Spectroscopy Triple dose Gd Atrophy T1 relaxation Neuronal/axonal viability Tissue loss MTR Myelin/oedema DTI Tissue microstructure

32 Brain Enhancement 42% patients with early PPMS (< 5 years) had at least one enhancing lesion on their baseline scan Number of enhancing lesions associated with - younger age (r=0.5, p= ) - higher T2 load ( r= 0.5, p=0.02)

33 Enhancement associated with higher disability and greater abnormality on MRI EDSS MSFC T2 load T1 load Partial Brain Volume Enhancing (18) Non-enhancing (24) P values 6.0 (range 3.5) 4.3 (range 3.5) p=0.011* -1.5 (SD 1.8) -0.4 (SD 1.1) p=0.004** 22.5ml (SD 25.0ml) 9.0ml (SD 20.1ml) p=0.005** 7.3ml (SD 10.0ml) 3.2ml (10.0ml) p=0.001** 248.3ml (SD 23.8ml) 264.1ml (SD 19.5ml) p=0.049*

34 Brain atrophy Coronal T1 WI

35 Baseline atrophy in early PPMS White matter most affected Controls (n=45) mean (range) BPF* 0.83 ( ) WMF* 0.28 ( ) GMF 0.55 ( ) Patients (n=41) mean (range) -6.2% -3.5% 0.79 ( ) 0.26 ( ) 0.52 ( ) *all differences significant at p<0.001 level allowing for age using general linear modelling

36 Results over 12 months 0-12 months BPF - SPM P < % P = WMF - SPM % P < GMF - SPM %

37 MTR MRI-visible FREE WATER POOL Magnetization transfer Free protons axon myelin MRI-invisible BOUND WATER POOL Macromolecular protons Evidence suggests that molecules associated with myelin dominate this exchange process in WM MTR map High magnetization transfer = BRIGHT Low magnetization transfer = DARK

38 MTR in early PPMS Controls Patients p NABT mean < NABT peak height < NABT peak location < NAWM mean < NAWM peak height < NAWM peak location < NAGM mean < NAGM peak height < NAGM peak location < Estimated means using General Lineal Model allowing for age and gender

39 Which MR measures correlated with clinical outcome over 3 years? Progression on EDSS over three years was associated with Rate of decrease in GM MTR mean (p=0.032) and PL (p=0.008) Rate of T2 lesion load increase (p=0.024)

40 29 Mean Grey matter MTR at baseline Grey matter MTR was the strongest predictor of progression over 3 years stable mild progression marked progression

41 Radiological measures as markers for clinical progression in early PPMS MTR Volume T2 lesion load GM WM GM WM Changes over time Y Y Y N Y Rate of change correlates with clinical change Y N N N Y Predicts future clinical change Y N N N Y

42 Conclusions MRI provides valuable insights into progression in PPMS Both grey and white matter make a contribution (possibly independently) The combination of grey matter MTR and focal T2 lesions may prove to be the strongest predictor of disability in PPMS

43 Grey matter damage predicts evolution of PPMS at 5 years Rovaris et al Brain 2006; 129:

44 Cognitive Impairment in PPMS WORSE ON Attention Verbal memory Verbal fluency Spatial reasoning MAGNIMS Camp et al. Brain 1998

45 Grey matter damage in MS Bö et al., Arch Neurol 2007 Geurts et al., JNEN 2007 Geurts & Barkhof 2008

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47 METHODS Neuropsychological test battery Premorbid IQ An extensive neuropsychological test battery was administered to 26 patients with PPMS and 31 controls. An overall cognitive z-score was obtained Clinical and sociodemographic variables were also recorded Current IQ Verbal Performance overall cognitive z-score IQ Decline Verbal Performance Memory Story recall: immediate (/56) Story recall: delayed (/56) Figure recall: immediate (/56) Figure recall: delayed (/56) Attention/Speed of information processing PASAT SDMT z-score Executive function Hayling: total of scaled scores (/23) Brixton: errors (/54)

48 RESULTS Overall cognitive performance GM MTR (PL) showed the strongest correlation with the overall cognitive z-score, explaining 63% of the variance (β= 1.02 [95%CI: 0.65, 1.4], p<0.001). Executive function GM MTR (PH) showed the strongest correlation with the Hayling test (β= [2313.9,4320.3], p<0.001) Attention and speed of information processing function NAWM volume showed the strongest correlation with the SDMT (β= 0.48 [0.27, 0.68], p<0.001) Memory T2 lesion load showed the best correlation with a poorer performance on the Delayed Recall Test (β= [-0.3, -0.03], p = 0.021) Decline in verbal IQ GM MTR (mean) showed the strongest correlation (β= [-6.44, -1.83], p=0.001)

49 2 ASSOCIATION BETWEEN IMAGING AND COGNITIVE DYSFUNCTION overall cognitive z-score Overall cognitive performance -6 β= 1.02 (0.65, 1.40), p < GM PL MTR 34 zcog values Adjusted by yearsfitted of education Regression of the overall cognitive z-score over GM PL MTR 35

50 CONCLUSIONS GM MTR showed the strongest correlation with overall cognitive performance However, T2 lesion load and GM MTR and NAWM volumes are also important for specific cognitive impairments

51 Conclusions Predictors of outcome Clinical Poor - Multisystem presentation (rare) - Rapid early progression Good - Sensory presentation - Younger age of onset (caveat) Imaging - Enhancement at baseline (possible) - Reduced GM MTR and high T2 lesion load - Early worsening in GM MTR and T2 lesion load

52 Acknowledgements The Wellcome Trust, MSIF, NIHR, MS Ttrust MS Society of GB & NI PPMS Team Olga Ciccarelli, Val Stevenson, Jaume Sastre, Gordon Ingle, Zhaleh Khaleeli, Francesco Manfredonia, Benedetta Bodini, CarmenTur. MS Team NMR Unit D Miller, X.Golay. M Ron, T Yousry, A Toosy, C Wheeler-Kingshott, MAGNIMS