Amélioration des méthodes d’évaluation de la prévention en
population âgée
Nicola ColeyCERPOP
Equipe Vieillissement – Axe MAINTAIN
8,7 millions de cas de demence en Europe� La maladie d’Alzheimer (MA) représente 50 à 70% des cas
� Augmentation exponentielle de la prévalence avec l’âge
� 46,8 millions de cas dans le monde en 2015 → 131 millions en 2050
Winblad B et al. Lancet Neurol. 2016
(ADI World Alzheimer Report 2015)
� 7ème cause de mortalité mondiale en 2019 (OMS)
La maladie d’Alzheimer (MA)
Maladie neurodégénérative progressive
Atrophie cérébrale, plaques amyloïdes, dégénérescence neurofibrillaire
Perte progressive des fonctions cognitives (notamment mémoire)
Limitations dans les activités (instrumentales) de la vie quotidienne -> perte d’autonomie
Troubles d’humeur et comportement
Aucun traitement curatif
Longue période de latence (stade pré clinique): apparition des altérations physiopathologiques bien avant les symptômes
cliniques
Jack CR Jr. Lancet Neurol. 2013;12(2):207-16
Prévention
possible?
Timeline of AD research milestones
1906
Alois
Alzheimer
first
describes
the disease
1968
Development
of cognitive
measurement
scales
1984-6
Beta-
amyloid
& tau
identified
1987
First AD
drug trial
1993
First
symptomatic
treatment
approved
1998
First
prevention
trials
(inc.MCI)
2011
New AD
diagnostic
criteria
incorporating
biomarkers
2002
Last
symptomatic
treatment
approved
Many failed phase 2-3
trials
Vers la prévention
Revue systématique et méta analyses
Livingston G et al. Dementia prevention, intervention, and care. Lancet. 2020
• Niveau d’éducation (7%)
• Perte d’audition (8%)
• Lésions cérébrales traumatiques (3%)
• Hypertension (2%)
• Consomption élevée d’alcool (1%)
• Obésité (1%)
• Tabagisme (5%)
• Dépression (4%)
• Isolement sociale (4%)
• Sédentarité (2%)
• Pollution de l’air (2%)
• Diabète (1%)
40% des cas de démence attribuables à 12
facteurs de risque potentiellement modifiables :Enfance
Milieu de vie
Age avancée
Réflexion méthodologique:How to measure intervention effects in the new generation of 1° and 2° prevention trials?
Symtomatic AD trials
Co-primary outcome approach using gold-standard measures of cognition and function (lack of « hard » clinical endpoints)
Secondary prevention trials (MCI/prodromal AD)
Same co-primary outcome approach as in symptomatic trials?
Conversion to dementia?
Biomarkers?
Primary prevention trials
Biomarkers?
Incident dementia?
Cognitive decline?
• Power
issues
• Limited
functional
decline
• Lack of
standardisation/
validation
• Cost
• Invasiveness
• Sensitivity to
change?
• Clinical
relevance?
Towards validating new endpoints
Suitability of a single primary endpoint measuring both cognition and function in secondary prevention/early AD trials
Determining the clinical relevance of a cognitive composite score for primary prevention trials
Utility of dementia risk scores as primary outcome measures for early prevention trials
CDR-sum of boxes: scores range from 0-18
Cognitive
items
Functional
items
Tractenberg, J
Neuropsych Clinl
Neurosci 2005Hughes, Br J Psychiatry 1982; Morris, Neurology 1993
CDR-SB as a single primary endpoint
Analysis of 667 subjects with very early or mild-moderate AD from the REAL.FR study
CDR-SB measures
cognition & function
simultaneously
Similar rates of
change across
different disease
stages, with limited
floor/ceiling effects
Low variability in
change over time:
smaller trial sample
sizes
Little missing data
CDR-SB responsiveness & consequences for trial design
Coley N, Andrieu S, Jaros M, Weiner M, Cedarbaum J, Vellas B.
Alzheimers Dement. 2011;7(6):602-610
Impact
Replication of results in the US ADNI studyCedarbaum JM, Jaros M, Hernandez C, Coley N, Andrieu S, Grundman M, Vellas B. AlzheimersDement. 2013; 9(1 Suppl):S45-55
EMA and FDA guidance recommend single primary endpoint measuring cognition and function simultaneously for prodromal AD trials, citing both studies
Food and Drug Administration. Guidance for Industry. Alzheimer's disease: developing drugs for the treatment of early stage disease, 2013.European Medicines Agency, Committee for Medicinal Products for Human Use (CHMP). Guideline on the clinical investigation of medicines for the treatment of Alzheimer’s disease, 2018.
CDR-SB now widely used as the sole clinical primary outcome measure in prodromal and mild dementia AD trials (approx. 20 trials registered in clinicaltrials.gov)
Outcomes in prevention trials
Type de critère de jugement principal:
Incidence de démence/MA
Déclin cognitif/performance cognitive
Biomarqueur
Chronologie des essais de prévention publiésType de critère de jugement et
résultat principal
Intervention pharmacologique non spécifique
Intervention pharmacologique spécifique
Intervention nutritionnelle
Entrainement cognitif
Exercice physique
Intervention multidomaine
Andrieu S, Coley N et al. Lancet Neurol. 2015
Revue de la littérature en 2015
Essais de prévention (randomisés et contrôlés)- de la MA- de la démence de toute
cause- du déclin cognitif
Analysis of the primary endpoints usedin the 51 prevention trials11 measured incident dementia
36 measured cognitive function/decline
Global cognition
Global test (e.g. MMSE)
Composite measure
Domain-specific cognitive function
4 measured biomarkers
• Most studies used their own individual
battery of tests
• Clinical relevance of most results unclear
Andrieu S, Coley N et al. Lancet Neurol. 2015
Composite cognitive scores• Increasingly popular primary outcome measures for
preclinical/prevention trials
• Combination of several sensitive cognitive tests into a single score
– More sensitive to change than individual tests/existing global cognitive scores
• Theory-driven and data-driven development suggest similar important domains
– episodic memory, orientation, executive function, language
15
Composite cognitive scores as primary outcome
measures• Supported by regulatory authorities
– “Alternatives to the ADAS like the NTB, the CDR-SB, the recently
proposed ADCS-PACC or others have been validated and may be used” EMA discussion paper on the clinical investigation of medicines for the treatment of Alzheimer´s disease and other dementias
• But not yet fully validated…
– Clinical relevance of changes on composite measures not well understood
• “The clinical relevance, the functional and long-term consequences of the subtle cognitive
changes measured by ADCS-PACC in earlier disease stages is currently unknown” (EMA)
– Long-term trajectories of cognitive decline not yet studied in treatment trials in preclinical/prevention settings 16
The GuidAge study• Multicentre, 5-year, randomised, double-blind, placebo-controlled trial of
Ginkgo biloba for AD dementia prevention
• 1414 placebo group participants included in this analysis– Age >70
– Spontaneously reported memory complaints
– MMSE>25
– CDR<1
– Free of dementia & major objective memory impairment (FCSRT score>10th percentile for age, sex &
sociocultural level)
– Free of major anxiety & depression (COVI<6, GDS<15)
• Cognitive function assessed annually in expert memory centres– Primary outcome: AD incidence (DSM-IV, NINCDS-ADRDA)
– Secondary outcome: cognitive decline (MMSE, FCSRT, TMT, verbal fluency)
Vellas B, Lancet Neurology 2012; Andrieu S, Curr Alz Res 200817
Calculation of the composite score
Spatial and temporal orientation: 10 MMSE orientation items
Episodic memory: FCSRT (free + total recall)
Language/semantic memory: Category fluency
Executive function: TMT-B
Composite score = (Zorientation + Zepidosic memory + Zverbal fluency + Zexecutive function)/4
18
Composite score change from baseline
-0.6
-0.4
-0.2
0.0
0.2
0 1 2 3 4 5
Co
mp
osi
te s
core
ch
an
ge
fro
m b
ase
lin
e
≤75 years
(N=657)
76-80 years
(N=504)
81-85 years
(N=218)
>85 years
(N=35)*
(76-80 & 81-85
vs. ≤75y)
By age (p<0.001)
*(all groups vs.
≤75y)
19
By ApoE genotype (p=0.001)
-0.6
-0.4
-0.2
0.0
0.2
0 1 2 3 4 5
Co
mp
osi
te s
core
ch
an
ge
fro
m b
ase
lin
e
ApoE Ɛ4-ve
(N=733)
ApoE Ɛ4+ve
(N=242)
*
*
By AD dementia status during follow-up (p<0.001)
-2.5
-2
-1.5
-1
-0.5
0
0.5
0 1 2 3 4 5
Time (years)
No
dementia
(N=1316)
AD
dementia
(N=73)
*
*
*
**
5-year composite score change from baseline
differed significantly by:
• Age
• ApoE genotype
• CDR progression status during follow-up
• AD dementia status during follow-up
2-year practice effects were observed in nearly all
subgroups
Coley N, Gallini A, Ousset PJ, Vellas B, Andrieu S. Alzheimers Dement. 2016;12(12):1216-1225
Prediction of future AD dementia
HR represents 5-year risk of AD dementia associated with a 1 SD decrease in
cognitive performance at baseline
– Estimated from Cox proportional hazards models
• Adjusted for age, sex, education
• Separate model for each cognitive test
Composite score MMSE CDR-SB
HR [95%CI] p HR [95%CI] p HR [95%CI] p
3.5 [2.6-4.7] <0.001 1.6 [1.3-2.0] <0.001 1.9 [1.6-2.2] <0.001
Study population = placebo group subjects, excluding those who developed non-AD dementia 20
Minimal Clinically Important Difference (MCID)
• To determine the smallest difference on the composite
measure that is clinically important
• Compare changes in the composite score across groups of
individuals known to have small but real differences in their
health status (anchor measures)
– What is a small but “clinically important” change in this
population?
• Progression from CDR 0 to 0.5
• Loss of independence in one IADL– Measured over 1 year (shortest measurable period in this study)
– “Baseline” for this analysis = 2 year visit (to avoid practice effects) 21
MCID: anchor-based 1-year mean change• 1st MCID estimate = difference in 1-year mean change on composite
in subjects who did and did not undergo change on anchor measures
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
2 3
Me
an
1-y
ea
r co
mp
osi
te s
core
ch
an
ge
Stable CDR 0
(N= 478)
CDR 0→0.5
(N=63)-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
2 3
No IADL decline
(N=749)
Loss of
independence in 1
IADL (N=35)
MCID = -0.28
(p<0.001)
MCID = -0.05
(p=0.484)
CDR anchor IADL anchor
22
Coley N, Gallini A, Ousset PJ, Vellas B, Andrieu S. Alzheimers Dement. 2016;12(12):1216-1225
MCID: anchor-based ROC curve analysis
• To describe the performance of composite measure change scores in discriminating between participants who do/do not undergo change on anchor measures– AUC = 0.7-0.8: acceptable discrimination
– AUC = 0.8-0.9: excellent discrimination
– AUC >0.9: outstanding discrimination
• Optimal cut-off determined using Youden Index (max. Sp & Se)
= 2nd MCID estimate
CDR anchor
(N=541, 63 decliners)
IADL anchor
(N=784; 35 decliners)
AUC
(95%CI)
0.7
(0.6-0.8)
0.5
(0.4-0.6)
Optimal cut-off ≤ -0.3 ≤ -0.3
Sensitivity 57.1% 37.1%
Specificity 80.3% 72.9%
23
Summary
• Baseline composite score was highly predictive of 5-year AD
dementia risk in a prevention trial setting
• 5-year composite score change from baseline differed
significantly by:
– Age
– ApoE genotype
– CDR progression status during follow-up
– AD dementia status during follow-up
• 2-year practice effects were observed in nearly all subgroups
• A first estimation of the MCID on this composite measure is -0.3
points (over 1 year)24
Dementia risk scores as surrogate outcomes –rationale, preliminary evidence and challenges
40% des cas de démences potentiellement attribuables aux facteurs modifiables
Comment mesurer l’effet d’une intervention qui débute dès la période « midlife » ?
Scores de risque de démence comme critères de substitution?
Sensibles au changement?
Capables de détecter l’effet d’une intervention?
Coley N, Hoevenaar-Blom M et al. Alzheimers Dement. 2020;16(12):1674-1685
CriteriaSubjective rating/5
CAIDE LIBRA ANU-ADRI BDSI DRS FDRS
Dementia prediction based on midlife data 5 4 4 0 1 1
External validation 5 2 3 2 1 0
Overall predictive accuracy 2 1 3 4 4 0
Importance of modifiable factors in total score 3 4 3 1 2 1
Validation as an RCT outcome measure 0 0 0 0 0 0
Use in RCTs as an outcome measure 3 2 4 0 0 0
Average rating 3 2 2 1 1 0
Candidate risk scores
ANU-ADRI: Australian National University AD Risk Index; BDSI: Brief Dementia Screening Indictor; CAIDE:
Cardiovascular Risk Factors, Aging and Incidence of Dementia; DRS: Dementia Risk Score; FDRS: Framingham
Dementia Risk score; LIBRA: Lifestyle for Brain Health
CAIDE LIBRA
Score MAPT PREDIVA HATICE Score MAPT PREDIVA HATICE
Age 0/3/4
Education 0/2/3
Sex 0/1
Blood pressure 0/2 0/1.6
Cholesterol 0/2 0/1.4
Diabetes 0/1.3 (I)
Renal dysfunction 0/1.1 -
CHD 0/1.0 -
Depression 0/2.1
BMI 0/2 0/1.6
Physical activity 0/1 0/1.1
Smoking 0/1.5 (I)
Alcohol -1/0 (I)
Medi. Diet 0/1.7 - -
Cognitive activity -3.2/0 - -
MAX SCORE 15 14.4 11.7(I)/ 8.9 12.7 13.3
Score components and data availability
No
n-
mo
dif
iab
leM
od
ifia
ble
Suitability of scoring systems for detecting
change?• CAIDE and LIBRA attribute points using categorical scoring
systems based on underlying prediction models
– E.g. CAIDE: SBP ≤140 = 0 points; SBP >140 = 2 points
• Large changes in individual risk factors (and dementia risk) may
not be registered if they do not cross the categorical cut off
points
• Proposal for alternative scoring systems:
– Z-scores
– Weighted z-scores
MAPT (FR) preDIVA (NL) HATICE (NL, FI, FR)
Sample size 1679 3526 2724
Intervention and
control conditions
• Multidomain intervention (cognitive training,
physical activity, nutrition counselling,
preventive consultation) + placebo
• Multidomain intervention + omega-3
supplement
• Omega-3 supplement
• Placebo
• Nurse-led
multidomain
cardiovascular care
• Usual care
• Coach-supported
interactive internet
platform to encourage self-
management of CV risk
factors & lifestyle change
• Static internet platform
Intervention duration 3 years 6-8 years 1.5 years
Primary outcome Cognitive function Dementia, disability Composite score of BMI, SBP
and cholesterol
Main secondary
outcomes
Functional status, physical status, depression,
dementia, health resource utilization
Cardiovascular events,
change in cognitive
function, depression
Cardiovascular events, lifestyle
parameters, cognitive
functioning
Main eligibility criteria - Age 70+
- Spontaneous memory complaint, and/or
limitations in one instrumental activity of daily
living, and/or slow gait speed
- Free of dementia
- Age 70-78
- Free of dementia
- Age 65+
- ≥2 CV risk factors and/or
history of CVD
- Computer literate
- Free of dementia
Datasets: main trial design features
Coley N, Hoevenaar-Blom M et al. Alzheimers Dement. 2020
Change over time
(up to 2 years FUP)
• 48 - 58% of intervention group participants
underwent change on the CAIDE score
• 30-31% decreased score (i.e. reduced dementia
risk)
• 18-27% increased score
• Up to 79% of participants changed over time on LIBRA
• Similar proportions increased (32-42%) and
decreased (29-43%) in score
Coley N, Hoevenaar-Blom M et al. Alzheimers Dement. 2020
Change in original score vs.
change in z-core version
• Z-score versions able to detect changes in risk factors
that were not registered by the original scores
(especially for CAIDE)
• Change of -1.25 to 1.25 points on z-score version
for subjects with zero change on original version
• Original versions changed by as much as +/- 5 points
for individuals showing no change on z-score versions
←amélioration du risque de démence
-0.8 -0.6 -0.4 -0.2 0.0 0.2
-0.3 -0.2 -0.1 0.0 0.1
-0.8 -0.6 -0.4 -0.2 0.0 0.2
-0.3 -0.2 -0.1 0.0 0.1
Différence d’évolution (IC95%) du score de risque entre groupe intervention et
contrôle
CAIDE score
original
CAIDE version z-
score
LIBRA score
original
LIBRA version
z-score
MAPT preDIVA HATICE Simulation effet « cliniquement important »
Conclusions
• Scores CAIDE et LIBRA (version d’origine ou version modifiée)
potentiellement utiles comme critère de substitution
• sensibles au changements
• capables de détecter un effet modeste, mais statistiquement
significatif, d’une intervention multidomaine
• Impact réel d’un effet modeste à court terme sur un score de
risque sur l’incidence de démence à long terme?
RemerciementsCDR-SB analysis
INSERM-Univ Toulouse
Sandrine Andrieu
Bruno Vellas
UCSF
Mike Weiner
Elan Pharmaceuticals
Jesse Cedarbaum
Mark Jaros
REAL.FR study investigators &
funders (PHRC)
Composite score analysis
INSERM-Univ Toulouse
Sandrine Andrieu
Adeline Gallini
Pierre-Jean Ousset
Bruno Vellas
GuidAge study group & funders
(Ipsen)
Risk scores analysis
INSERM-Univ Toulouse
Sandrine Andrieu
Amsterdam UMC
Marieke Hoevenaar-Blom
Jan-Willem van Dalen
Eric Moll van Charante
Edo Richard
Karolinska Institute
Miia Kivipelto
University of Eastern Finland
Hilkka Soininen
PRODEMOS consortium & funders
HATICE consortium & funders
preDIVA study group & funders
MAPT/DSA group & funders