Prevalence and prognosis of Alzheimer’s disease at the mild cognitive impairment stage

For Peer Review

Prevalence and prognosis of Alzheimer’s disease at the mild

cognitive impairment stage

Journal: Brain

Manuscript ID: BRAIN-2014-01616.R1

Manuscript Type: Original Article

Date Submitted by the Author: 27-Nov-2014

Complete List of Authors: Vos, Stephanie; Maastricht University, Verhey, Frans; Maastricht University Medical Center, Psychiatry & Neuropsychology Frölich, Lutz; Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, 4Division of Geriatric Psychiatry Kornhuber, Johannes; Friedrich-Alexander University of Erlangen, Jens, Wiltfang; Uni Göttingen, Maier, Wolfgang; University of Bonn, Peters, Oliver; Charité – Universitätsmedizin Berlin, Psychiatry and Psychotherapy Ruether, Eckart; University of Göttingen, Nobili, Flavio; University of Genoa, Clinical Neurophysiology Unit, Dept of Neurosciences, Ophthalmology and Genetics Morbelli, Silvia; University of Genoa, Nuclear Medicine Unit, Dept. of Internal Medicine Frisoni, Giovanni; IRCCS Fatebenefratelli, Epidemiology and Neuroimaging Drzezga, Alexander; University of Cologne, Didic, Mira; AP-HM Timone, Service de Neurologie et de Neuropsychologie van Berckel, Bart; VU University Medical centre, Nuclear Medicine & PET research; Simmons, Andy; Institute of Psychiatry, Soininen, Hilkka; University of Eastern Finland and Kuopio University Hospital, Department of Neurology Kloszewska, Iwona; Medical University of Lodz, Mecocci, Patrizia; University of Perugia, Tsolaki, Magda; Aristotle University of Thessaloniki, Vellas, Bruno; CHU Toulouse, Alzheimer Disease Research and Clinical Center Lovestone, Simon; King's College London, Old Age Psychiatry Muscio, Cristina; IRCCS San Giovanni di Dio Fatebenefratelli, Herukka, Sanna-Kaisa; University of Eastern Finland, Department of Neurology Salmon, Eric; Université de Liège, Bastin, Christine; University of Liège, Cyclotron Research Centre; Wallin, Anders; University of Gothenburg, Nordlund, Arto; Sahlgrenska Academy, Institute of Clinical Neuscience Mendonca, alexandre; University of Lisbon, Silva, Dina; University of Lisbon,

ScholarOne, 375 Greenbrier Drive, Charlottesville, VA, 22901 Support (434) 964 4100

Brain

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Santana, Isabel; Coimbra University Hospital, Lemos, Raquel; University of Coimbra, Engelborghs, Sebastiaan; University of Antwerp, Van der Mussele, Stefan; University of Antwerp, Freund-levi, Yvonne; Karolinska University Hospital Huddinge, Wallin, Asa; Lund University, Hampel, Harald; Université Pierre et Marie Curie-Paris, van der Flier, W,M.; VUmc, Scheltens, Philip; Vumc, Visser, Pieter Jelle; Maastricht University,

Subject category: Dementia

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Prevalence and prognosis of Alzheimer’s disease at the mild cognitive

impairment stage

Stephanie J. B. Vos,1 Frans Verhey,1 Lutz Frölich,2* Johannes Kornhuber,3* Jens Wiltfang,4*

Wolfgang Maier,5* Oliver Peters,6* Eckart Rüther,7* Flavio Nobili,8† Silvia Morbelli,9 † Giovanni B.

Frisoni,10,11† Alexander Drzezga,12† Mira Didic,13† Bart N. M. van Berckel,14† Andrew Simmons,15ǂ

Hilkka Soininen,16ǂ Iwona Kłoszewska,17ǂ Patrizia Mecocci,18ǂ Magda Tsolaki,19ǂ Bruno Vellas,20ǂ

Simon Lovestone,21ǂ Cristina Muscio,10,22,23 Sanna-Kaisa Herukka,16 Eric Salmon,24,25 Christine

Bastin,25 Anders Wallin,26 Arto Nordlund,26 Alexandre de Mendonça,27 Dina Silva,27 Isabel

Santana,28 Raquel Lemos,29 Sebastiaan Engelborghs,30,31 Stefan Van der Mussele,30 The

Alzheimer’s Disease Neuroimaging Initiative,ѱ Yvonne Freund-Levi,32 Åsa K. Wallin,33 Harald

Hampel,34 Wiesje van der Flier,35 Philip Scheltens35 and Pieter Jelle Visser1,35

See Schott for a scientific commentary on this article (doi:10.1093/brain/).

Abstract

Three sets of research criteria are available for diagnosis of Alzheimer’s disease in subjects with

mild cognitive impairment: the International Working Group-1, International Working Group-2,

and National Institute of Aging-Alzheimer Association criteria. We compared the prevalence and

prognosis of Alzheimer’s disease at the mild cognitive impairment stage according to these

criteria. Subjects with mild cognitive impairment (n = 1607), 766 of whom had both amyloid and

neuronal injury markers, were recruited from 13 cohorts. We used cognitive test performance and

available biomarkers to classify subjects as prodromal Alzheimer’s disease according to

International Working Group-1 and International Working Group-2 criteria and in the high

Alzheimer’s disease likelihood group, conflicting biomarker groups (isolated amyloid pathology

or suspected non-Alzheimer pathophysiology), and low Alzheimer’s disease likelihood group

according to the National Institute of Ageing-Alzheimer Association criteria. Outcome measures

were the proportion of subjects with Alzheimer’s disease at the mild cognitive impairment stage

and progression to Alzheimer’s disease-type dementia. We performed survival analyses using Cox

proportional hazards models. According to the International Working Group-1 criteria, 850 (53%)

subjects had prodromal Alzheimer’s disease. Their 3-year progression rate to Alzheimer’s disease-

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type dementia was 50% compared to 21% for subjects without prodromal Alzheimer’s disease.

According to the International Working Group-2 criteria, 308 (40%) subjects had prodromal

Alzheimer’s disease. Their 3-year progression rate to Alzheimer’s disease-type dementia was 61%

compared to 22% for subjects without prodromal Alzheimer’s disease. According to the National

Institute of Ageing-Alzheimer Association criteria, 353 (46%) subjects were in the high

Alzheimer’s disease likelihood group, 49 (6%) in the isolated amyloid pathology group, 220

(29%) in the suspected non-Alzheimer pathophysiology group, and 144 (19%) in the low

Alzheimer’s disease likelihood group. The 3-year progression rate to Alzheimer’s disease-type

dementia was 59% in the high Alzheimer’s disease likelihood group, 22% in the isolated amyloid

pathology group, 24% in the suspected non-Alzheimer pathophysiology group, and 5% in the low

Alzheimer’s disease likelihood group. Our findings support the use of the proposed research

criteria to identify Alzheimer’s disease at the mild cognitive impairment stage. In clinical settings,

the use of both amyloid and neuronal injury markers as proposed by the National Institute of

Ageing-Alzheimer Association criteria offers the most accurate prognosis. For clinical trials,

selection of subjects in the National Institute of Ageing-Alzheimer Association high Alzheimer’s

disease likelihood group or the International Working Group-2 prodromal Alzheimer’s disease

group could be considered.

Author affiliations:

1Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental

Health and Neuroscience, Alzheimer Centre Limburg, Maastricht, The Netherlands

2Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, University of

Heidelberg, Mannheim, Germany

3Department of Psychiatry and Psychotherapy, Friedrich-Alexander University of Erlangen,

Erlangen, Germany

4Department of Psychiatry and Psychotherapy, University Medical Centre (UMG), Georg-August-

University, Göttingen, Germany

5Department of Psychiatry and Psychotherapy, University of Bonn, German Centre for

Neurodegenerative Diseases (DZNE), Bonn, Germany

6Department of Psychiatry and Psychotherapy, Charité Berlin, Berlin, Germany

7Department of Psychiatry and Psychotherapy, University of Göttingen, Göttingen, Germany

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8Clinical Neurophysiology Service, Department of Neurosciences, Ophthalmology and Genetics,

University of Genoa, Genoa, Italy

9Nuclear Medicine, Department of Internal Medicine, University of Genoa, Genoa, Italy

10IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy

11University Hospitals and University of Geneva, Geneva, Switzerland

12Department of Nuclear Medicine, University of Cologne, Cologne, Germany

13Service de Neurologie et Neuropsychologie, Pôle de neurosciences cliniques, AP-HM Timone,

U1106, Aix-Marseille Univ Marseille, France

14Department of Nuclear Medicine and PET Research, VU University Medical CentRE,

Amsterdam, The Netherlands

15Department of Neuroimaging, Centre for Neuroimaging Science, King’s College London,

Institute of Psychiatry, London, UK

16Institute of Clinical Medicine, Neurology, University of Eastern Finland and Neurocenter,

Neurology, Kuopio University Hospital, Kuopio, Finland

17Medical University of Lodz, Lodz, Poland

18Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy

19Aristotle University of Thessaloniki, Memory and Dementia Center, 3rd Department of

Neurology, “G Papanicolaou” General Hospital, Thessaloniki, Greece

20UMR INSERM 1027, CHU Toulouse, Toulouse, France

21University of Oxford, Department of Psychiatry, Oxford, UK

22Fondazione Europea Ricerca Biomedica (FERB), Centro di Eccellenza Alzheimer, Ospedale

Briolini, Gazzaniga, Bergamo, Italy

23Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy

24Memory Clinic, Department of Neurology, CHU Liège, Belgium

25Cyclotron Research Centre, University of Liège, Liège, Belgium

26Department of Psychiatry and Neurochemistry, Institute for Neuroscience and Physiology,

Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

27Institute of Molecular Medicine, Faculty of Medicine, University of Lisbon, Portugal

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28Department of Neurology, Coimbra University Hospital, Coimbra, Portugal

29Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal

30Reference Centre for Biological Markers of Dementia (BIODEM), Laboratory of

Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium

31Department of Neurology and Memory Clinic, Hospital Network Antwerp, Middelheim and

Hoge Beuken, Antwerp, Belgium

32Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical

Geriatrics, Karolinska Institutet, and Department of Geriatric Medicine, Karolinska University

Hospital Huddinge, Stockholm, Sweden

33Lund University, Clinical Sciences Malmö, Clinical Memory Research Unit, Lund, Sweden

34Centre des Maladies Cognitives et Comportementales, Institut du Cerveau et de la Moelle

épinière, Paris, France; Université Pierre et Marie Curie-Paris 6, AP-HP, Hôpital de la Salpêtrière,

Paris, France

35Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU

University Medical Center, Amsterdam, The Netherlands

*On behalf of the German Dementia Competence Network.

†On behalf of the EADC-PET consortium.

ǂOn behalf of the AddNeuroMed consortium.

ѱData used in preparation of this article were partially obtained from the Alzheimer’s Disease

Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the

ADNI contributed to the design and implementation of ADNI and/or provided data but did not

participate in analysis or writing of this report. A complete listing of ADNI investigators can be

found at: http://adni.loni.usc.edu/wpcontent/uploads/how_to_apply/

ADNI_Acknowledgement_List.pdf

Correspondence to: Stephanie J. B. Vos, PhD

Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health

and Neuroscience, Alzheimer Centre Limburg

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P.O. Box 616, 6200 MD Maastricht, The Netherlands

E-mail: [email protected]

Running title: Comparing diagnostic research criteria

Keywords: Alzheimer’s disease; MCI; biomarkers; diagnostic criteria; prognosis

Abbreviations: FDG = 18F-fluorodeoxyglucose; IAP = isolated Alzheimer pathology; IWG-1 =

International Working Group-1; IWG-2 = International Working Group-2; MCI = mild cognitive

impairment; NIA-AA = National Institute of Ageing-Alzheimer Association; SNAP = suspected

non-Alzheimer pathophysiology.

Introduction

In recent years three sets of research criteria for diagnosis of Alzheimer’s disease in subjects with

mild cognitive impairment (MCI) have been proposed: the International Working Group (IWG)-1

(Dubois et al., 2007, 2010), IWG-2 (Dubois et al., 2014), and National Institute of Ageing-

Alzheimer Association (NIA-AA) criteria (Albert et al., 2011). The criteria include biomarkers of

Alzheimer’s disease pathology to increase the confidence that subjects with MCI have

Alzheimer’s disease as underlying cause. However, they differ in the definition of MCI and

biomarker abnormality (Visser et al., 2012) (Table 1). A direct comparison between the criteria is

lacking and it remains unclear which criteria are best to use.

The IWG criteria use the term prodromal Alzheimer’s disease for diagnosis of Alzheimer’s

disease and were designed to serve as research criteria. The IWG-1 criteria require episodic

memory impairment and at least one abnormal Alzheimer’s disease biomarker. This biomarker

can be a topographical marker [i.e. medial temporal lobe atrophy on MRI or parieto-temporal

hypoperfusion on 18F-fluorodeoxyglucose (FDG)-PET] or a pathophysiological marker (i.e.

decreased CSF amyloid-β1-42, increased CSF tau, or increased amyloid PET uptake) (Dubois et al.,

2007, 2010). The updated IWG-2 criteria require cognitive impairment in any cognitive domain

and either both decreased CSF amyloid-β1-42 and increased tau, or increased amyloid PET uptake

(Dubois et al., 2014). These criteria specify two subtypes: typical prodromal Alzheimer’s disease

if impairment on a memory test is present; and atypical prodromal Alzheimer’s if only impairment

on a non-memory test is present. The NIA-AA criteria use the term ‘mild cognitive impairment

due to Alzheimer’s disease’ and were designed for both clinical and research use. They require

cognitive impairment in any cognitive domain and abnormal amyloid markers (i.e. decreased CSF

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https://www.researchgate.net/publication/6222398_Research_criteria_for_the_diagnosis_of_Alzheimer's_disease_Revising_the_NINCDS-ADRDA_criteria?el=1_x_8&enrichId=rgreq-7e49217a-49f1-4d4a-a581-eec83ebf3a7d&enrichSource=Y292ZXJQYWdlOzI3MjUxNTU3MDtBUzoyMDA2Nzk1MjEwMzQyNDBAMTQyNDg1NzEzNDc1Nw==

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amyloid-β1-42 or increased amyloid PET uptake) or neuronal injury markers (i.e. medial temporal

lobe atrophy on MRI, increased CSF tau, or parietotemporal hypoperfusion on FDG-PET). They

relate the number of abnormal biomarkers to the likelihood that MCI is due to Alzheimer’s disease

(Albert et al., 2011) (Table 1).

Preliminary studies have shown that the IWG-1 and NIA-AA criteria have a fair to good

predictive ability for progression to Alzheimer’s disease-type dementia in subjects with MCI

(Bouwman et al., 2010; Oksengard et al., 2010; Petersen et al., 2013; Prestia et al., 2013). The

validity of the IWG-2 criteria has not yet been tested. The aim of the present study is to compare

the IWG-1, IWG-2 and NIA-AA criteria on prevalence and outcome of Alzheimer’s disease at the

MCI stage by means of a large multicentre study.

Material and methods

Subjects

Subjects were recruited from five multicentre studies: DESCRIPA (Visser et al., 2008),

AddNeuroMed (Lovestone et al., 2009), German Dementia Competence Network (DCN;

Kornhuber et al., 2009), the European Alzheimer’s Disease Consortium (EADC)-PET (Morbelli

et al., 2012), and American Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) study

(Mueller et al., 2005; Supplementary material); and from eight centres of the EADC: Amsterdam

(van der Flier et al., 2014), Antwerp (Van der Mussele et al., 2014), Brescia (Frisoni et al., 2009),

Coimbra (Baldeiras et al., 2008), Gothenburg (Eckerström et al., 2010), Kuopio (Seppälä et al.,

2011), Liège (Bastin et al., 2010), and Lisbon (Maroco et al., 2011). If a subject participated in

more than one study, we used data from the study with the longest follow-up.

Inclusion criteria of the present study were diagnosis of MCI, availability of at least one of the

following biomarkers: amyloid-β1-42 and tau in CSF, qualitative or quantitative measures of medial

temporal lobe atrophy on MRI [visual rating scale (medial temporal lobe atrophy score) or

hippocampal volume], or cerebral glucose metabolism on brain FDG-PET; and at least one

clinical follow-up assessment. Exclusion criteria were diagnosis of dementia at baseline or any

other vascular, somatic, psychiatric or neurological disorder that might have caused the cognitive

impairment.

Clinical assessment

Clinical assessment was performed according to the routine protocol at each site, including a

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clinical interview, Mini-Mental State Examination scoring, and neuropsychological assessment.

Baseline diagnosis of MCI was made according to the criteria of Petersen et al. (2004). Raw

scores on neuropsychological tests were converted to Z-scores at each centre. Cognitive

impairment was defined as Z-score < −1.5 [standard deviation (SD)] on at least one cognitive test

(Supplementary Table 1). Subjects with a Z-score < −1.5 SD on a memory test were classified as

having amnestic MCI. Subjects with a Z-score < −1.5 SD on a non-memory test only were

classified as having non-amnestic MCI.

Primary outcome measures were the proportion of subjects with Alzheimer’s disease at the MCI

stage based on the IWG-1, IWG-2 and NIA-AA criteria and progression to Alzheimer’s disease-

type dementia according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth

Edition (APA, 1994) and National Institute of Neurological and Communicative Disorders and

Stroke - Alzheimer’s Disease and Related Disorders Association criteria (McKhann et al., 1984).

Secondary outcome measure was cognitive decline on the Mini-Mental State Examination.

The medical ethics committee at each centre approved the study. All subjects provided informed

consent.

Biomarker assessment

Biomarker assessment was performed according to the routine protocol at each site. PET scans

were rated centrally. We used centre-specific cut-offs to define abnormal biomarkers

(Supplementary Table 2). Visual assessments of medial temporal lobe atrophy on MRI and

cerebral glucose metabolism on FDG-PET were performed by experienced clinicians who were

blinded to clinical and CSF biomarker data.

Subject classification

According to the IWG-1 criteria, subjects were classified as ‘prodromal Alzheimer’s disease’ if

they had episodic memory impairment and at least one abnormal biomarker. This could be a

topographical or pathophysiological marker (Table 1). Although the IWG-1 criteria recommended

a cued recall test to define memory impairment, such tests were not available for most studies and

we used non-cued memory tests as well. According to the IWG-1 update of 2010, we defined

atypical prodromal Alzheimer’s disease as non-amnestic MCI with abnormal biomarkers in a post

hoc analysis.

According to the IWG-2 criteria, subjects were classified as ‘prodromal Alzheimer’s disease’ if

they had impairment in memory (typical prodromal Alzheimer’s disease) or non-memory domains

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(atypical prodromal Alzheimer’s disease) and abnormal CSF amyloid-β1-42 and tau biomarkers

(Table 1). In the main analysis we pooled typical and atypical prodromal Alzheimer’s disease but

we also performed analyses for each subgroup separately.

According to the NIA-AA criteria, we distinguished between amyloid (i.e. CSF amyloid-β1-42) and

neuronal injury markers (i.e. CSF tau, cerebral glucose metabolism on FDG-PET, medial temporal

lobe atrophy score or hippocampal volume). Subjects with MCI in any domain were classified in

the low Alzheimer’s disease likelihood group if both amyloid and neuronal injury markers were

normal, in the high Alzheimer’s disease likelihood group if amyloid and at least one neuronal

injury marker were abnormal, and in one of the two conflicting biomarker groups if the amyloid

marker was abnormal and neuronal injury markers normal [isolated amyloid pathology group

(IAP)] or if at least one neuronal injury marker was abnormal and the amyloid marker normal

[suspected non-Alzheimer pathophysiology group (SNAP)] (Jack et al., 2012; Petersen et al.,

2013; Vos et al., 2013a). Of the subjects who had only one biomarker available, subjects were

classified in the intermediate Alzheimer’s disease likelihood group if the marker that was tested

was abnormal and in the uninformative/inconclusive group if the marker was tested normal (Table

1).

Statistical analyses

Statistical analyses were done with SPSS version 20.0 (Chicago, IL, USA) with significance set at

P < 0.05. Baseline differences between the biomarker subgroups were analysed using ANOVA for

continuous variables and χ2 tests or logistic regression models for categorical variables. Cox

proportional hazards models were used to test the predictive ability for Alzheimer’s disease-type

dementia. The relation of the criteria with change on the Mini-Mental State Examination was

assessed by slope analyses with general linear mixed models including the baseline and last

follow-up score. The model was specified with a random intercept and slope and with centre as a

random effect because this model provided the best −2 log-likelihood compared with models with

simpler covariance structures. All analyses were adjusted for age, gender, education and centre.

Additionally, we calculated the sensitivity, specificity, positive and negative predictive value, and

Youden index (sensitivity + specificity−1) for Alzheimer’s disease-type dementia after 3 years.

Results

Sample demographics

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We included 1607 subjects with a mean follow-up of 2.4 years (SD 1.3, range 0.5–9). One

thousand five hundred and eleven subjects had a 1-year follow-up, 1069 a 2-year follow-up, 594 a

3-year follow-up, 170 a 4-year follow-up, 70 a 5-year follow-up, and 44 subjects had a follow-up

longer than 5 years. Seven hundred and sixty-six subjects had data on amyloid and neuronal injury

markers (CSF amyloid-β1-42 with CSF tau, medial temporal lobe, or FDG-PET) and 841 subjects

had data on only a neuronal injury marker (medial temporal lobe n = 698; FDG-PET n = 143).

Supplementary Tables 3 and 4 show the number of subjects for each biomarker by centre and the

characteristics for the total sample and separate biomarker groups.

Prevalence and outcome

Table 2 shows the classification and characteristics of subjects according to the criteria and Table

3 shows the outcome according to the criteria classification. Eight hundred and fifty (53%)

subjects had prodromal Alzheimer’s disease according to the IWG-1 criteria, and 308 (40%)

subjects according to the IWG-2 criteria, either typical or atypical (Table 2). Subjects with

prodromal Alzheimer’s disease were more likely to progress to Alzheimer’s disease-type dementia

(Table 3, Fig. 1) and showed a larger decline on the Mini-Mental State Examination

(Supplementary Table 5 and Supplementary Fig. 1) than subjects without prodromal Alzheimer’s

disease.

According to the NIA-AA criteria, of the subjects with amyloid and injury markers available, 353

(46%) subjects were classified in the high Alzheimer’s disease likelihood group, 49 (6%) in the

IAP group, 220 (29%) in the SNAP group, and 144 (19%) in the low Alzheimer’s disease

likelihood group (Table 2). Of the subjects with only a neuronal injury marker available, 459

(55%) were classified in the intermediate Alzheimer’s disease likelihood group and 382 (45%) in

the inconclusive group. Subjects in the high Alzheimer’s disease likelihood group were more

likely to progress to Alzheimer’s disease-type dementia than subjects in all other groups (Table 3

and Fig. 1). When the NIA-AA categories were dichotomized, subjects with high Alzheimer’s

disease likelihood had a higher progression rate compared to subjects in the low Alzheimer’s

disease likelihood and conflicting biomarker groups and subjects in the high Alzheimer’s disease

likelihood and conflicting biomarker groups had a higher progression rate than subjects in the low

Alzheimer’s disease likelihood group (Supplementary Table 5). The high and intermediate

Alzheimer’s disease likelihood groups showed a larger decline on the Mini-Mental State

Examination compared to all other groups (Supplementary Table 6 and Supplementary Fig. 1).

Head-to-head comparison of criteria

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In the subgroup of subjects with both amyloid and injury markers (n = 766), the Cox regression

prediction model showed a slightly better fit for the NIA-AA criteria than for the IWG-2 and

IWG-1 criteria because the −2 log-likelihood or deviance (a measure for unexplained variance)

was lowest for the NIA-AA criteria (2906 versus 2926 and 2982, respectively). Table 4 shows the

overlap in classification between the criteria by outcome after 3 years. The requirement of

memory impairment for IWG-1 prodromal Alzheimer’s disease and the requirement of abnormal

CSF amyloid-β1-42 and tau markers for IWG-2 prodromal Alzheimer’s disease resulted in

differences in classification compared to the NIA-AA criteria. Furthermore, the NIA-AA

conflicting biomarker groups are considered prodromal Alzheimer’s disease according to the

IWG-1 criteria but not according to the IWG-2 criteria. In subsequent analyses, we dichotomized

the NIA-AA criteria in two ways: (i) high Alzheimer’s disease likelihood group versus conflicting

and low Alzheimer’s disease likelihood groups; and (ii) high Alzheimer’s disease likelihood and

conflicting groups versus low Alzheimer’s disease likelihood group. Table 5 shows that the

specificity and positive predictive value were highest for IWG-2, whereas the sensitivity and

negative predictive value were highest for NIA-AA (ii). NIA-AA (i) showed the highest Youden

index.

In the subgroup of subjects with only a neuronal injury marker (n = 841), the Cox regression

model fit was slightly better for IWG-1 (−2 log-likelihood 3000) than for NIA-AA (−2 log-

likelihood 3012). The specificity was higher for IWG-1 than NIA-AA (Table 5).

Typical versus atypical Alzheimer’s disease

Of the subjects without IWG-1 prodromal Alzheimer’s disease, subjects with non-amnestic MCI

and abnormal biomarkers (atypical prodromal Alzheimer’s disease according to the IWG-1

update, n = 231) were more likely to progress to Alzheimer’s disease-type dementia (3-year

progression rate 31%) than subjects with amnestic or non-amnestic MCI with normal biomarkers

(n = 526, 3-year progression 17%, hazard ratio = 1.9, 95% CI 1.3–2.7, P < 0.0001; Supplementary

Fig. 2). Subjects with IWG-2 atypical prodromal Alzheimer’s disease (n = 49) had a similar

progression rate as subjects with IWG-2 typical prodromal Alzheimer’s disease (n = 259; 3-year

progression rate 63 versus 61%, P = 0.78; Supplementary Fig. 2).

Progression to non-Alzheimer’s disease dementia

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Using the IWG-2 criteria, progression to non-Alzheimer’s disease dementia was higher for

subjects without prodromal Alzheimer’s disease than for subjects with prodromal Alzheimer’s

disease (Table 2; 3-year progression rate 13% versus 3%; hazard ratio = 3.4, 1.3–8.8, P = 0.011).

Using the NIA-AA classification, progression to non-Alzheimer’s disease dementia was higher in

the low Alzheimer’s disease likelihood (3-year progression rate 14%) and SNAP (3-year

progression 13%) groups compared to the high Alzheimer’s disease likelihood and inconclusive

groups (3-year progression both 4%; Table 2; low: hazard ratio = 3.0, 1.3–6.9, P = 0.011

compared to high, hazard ratio = 2.8, 1.2–6.5, P = 0.016 compared to inconclusive; SNAP: hazard

ratio = 2.6, 1.2–5.6, P = 0.013 compared to high, hazard ratio = 2.5, 1.1–5.3, P = 0.021 compared

to inconclusive). Using the IWG-1 criteria, no difference in progression to non-Alzheimer’s

disease dementia was found between subjects without and with prodromal Alzheimer’s disease

(Table 2; 3-year progression rate 8% versus 7%; hazard ratio = 1.2, 0.8–1.9, P = 0.35).

Effect of neuronal injury marker

Subject classification based on an amyloid marker in combination with CSF tau or with medial

temporal lobe was generally the same (Table 6). Of the subjects with an abnormal amyloid marker

and two neuronal injury markers, 29% had only one injury marker abnormal, with tau being more

often abnormal than the medial temporal lobe (Table 7). Both these neuronal injury groups had a

similar outcome. Subjects with abnormal CSF amyloid-β1-42 and both abnormal CSF tau and

medial temporal lobe atrophy had a higher progression rate to Alzheimer’s disease-type dementia

than those with only one abnormal neuronal injury marker (68% versus 36–41%, P <0 .0001).

Similar findings were obtained in subjects with a normal amyloid marker (Table 7).

SNAP characterization

Because the SNAP group showed a relatively high progression rate to Alzheimer’s disease-type

dementia, we investigated CSF amyloid-β1-42 levels between subjects with and without progression

by comparing how much amyloid-β1-42 levels were above the cut-off. Analyses were restricted to

subjects for whom biomarkers were analysed by ELISA (n = 185), as the number of subjects with

suspected non-Alzheimer pathophysiology for whom biomarkers were analysed by xMAP was

relatively small (n = 35). Subjects with SNAP who progressed to Alzheimer’s disease-type

dementia had amyloid-β1-42 levels closer to the cut-off than subjects who did not progress and

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subjects who progressed to non-Alzheimer’s disease dementia [158 (SD 142) above the cut-off

versus 336 (SD 257) and 381 (SD 259) pg/ml above the cut-off, P < 0.0001; Fig. 2].

Discussion

This is the first large-scale multicentre study to compare the IWG-1, IWG-2 and NIA-AA criteria

for prodromal Alzheimer’s disease in subjects with MCI. We noted marked differences between

the criteria in Alzheimer’s disease prevalence and predictive accuracy for Alzheimer’s disease-

type dementia.

The IWG criteria were designed to identify individuals with a high probability of having

Alzheimer’s disease for research purposes. Indeed, we found relatively high progression rates for

Alzheimer’s disease-type dementia in subjects with prodromal Alzheimer’s disease but we found

also that a substantial part of the subjects not meeting prodromal Alzheimer’s disease criteria

progressed to Alzheimer’s disease-type dementia. For the IWG-1 criteria, we demonstrated that

the high progression rate in subjects without prodromal Alzheimer’s disease is likely due to the

presence of subjects with non-amnestic MCI with abnormal biomarkers. For the IWG-2 criteria,

we demonstrated that this is likely due to the inclusion of subjects with IAP and SNAP in this

group. A remarkable finding was the similar predictive accuracy of IWG-2 typical and atypical

prodromal Alzheimer’s disease. This corroborates a previous study (Vos et al., 2013b) and

supports the use of non-amnestic MCI as Alzheimer’s disease clinical phenotype.

The NIA-AA criteria were designed both for research and clinical purposes. The prognosis of the

low, high and intermediate Alzheimer’s disease likelihood subgroups nicely fitted with the

proposed terminology.

In the subsample with both amyloid and neuronal injury markers available, differences in

sensitivity, specificity, positive predictive value, and negative predictive value between the criteria

can be explained by whether one or two biomarkers needed to be abnormal. If both were required

to be abnormal (as was the case for IWG-2 and NIA-AA high Alzheimer’s disease likelihood

versus low Alzheimer’s disease likelihood and conflicting biomarker groups), positive predictive

value and specificity were high and sensitivity and negative predictive value low, consistent with

previous findings (van Rossum et al., 2012). If one biomarker was required abnormal (as was the

case for IWG-1, NIA-AA, high Alzheimer’s disease-likelihood and conflicting biomarker groups

versus low-Alzheimer’s disease-likelihood group), positive predictive value and specificity were

low and sensitivity and negative predictive value high.

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In the subsample with only a neuronal injury marker available, the higher specificity for IWG-1

compared to NIA-AA (intermediate Alzheimer’s disease likelihood group versus inconclusive

group) likely reflects the requirement of memory impairment for IWG-1 prodromal Alzheimer’s

disease. The progression rate to Alzheimer’s disease-type dementia in the NIA-AA intermediate

Alzheimer’s disease likelihood group was similar to that of the high Alzheimer’s disease

likelihood group and suggests that many subjects also had abnormal amyloid markers

The relatively high progression rate (~20%) for subjects with SNAP is intriguing, as the

biomarker profile suggests that non-Alzheimer’s disease pathology is likely (Petersen et al.,

2013). We found that subjects with SNAP who progressed to Alzheimer’s disease-type dementia

had CSF amyloid-β1-42 levels just above the cut-off. This indicates that the amyloid-β1-42 cut-offs

may have been too conservative, although using a more lenient cut-off would also lead to more

false positives. Alternatively, it could be that these subjects have comorbidities so that less

amyloid pathology is needed to progress to Alzheimer’s disease-type dementia. SNAP could also

be an atypical form of Alzheimer’s disease with less pronounced amyloid pathology. It is also

possible that these subjects have non-Alzheimer’s disease pathology with minimal amyloid

deposits and are misclassified as Alzheimer’s disease-type dementia at follow-up.

Only a small group of subjects was classified in the IAP group, likely because most subjects with

Alzheimer’s disease already have neuronal injury at the MCI stage. Approximately 20% of the

subjects with IAP progressed to Alzheimer’s disease-type dementia. A previous MCI study did

not find any converters with IAP, although this could be due to their relatively short follow-up (1

year; Petersen et al., 2013). Studies with longer follow-up are needed to see whether all subjects

with IAP will eventually progress to Alzheimer’s disease-type dementia or have some amyloid

pathology unrelated to Alzheimer’s disease.

Availability of only one biomarker is a common clinical situation. As amyloid assessment is

relatively invasive and expensive, often only neuronal injury markers will be measured. In

subjects with only injury markers, the prognostic accuracy of the NIA-AA intermediate

Alzheimer’s disease likelihood and inconclusive groups was very similar to that of the IWG-1

groups.

A higher progression rate to non-Alzheimer’s disease dementia was found in subjects without

IWG-2 prodromal Alzheimer’s disease compared to those with prodromal Alzheimer’s disease

and in subjects in the NIA-AA low Alzheimer’s disease likelihood and SNAP groups compared to

the high Alzheimer’s disease likelihood group. This is in-line with what is expected based on the

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biomarker profiles. In general, the progression rate to non-Alzheimer’s disease dementia at

follow-up was rather low, which could be because the cohorts were designed to study Alzheimer’s

disease.

We found that 29% of the subjects with abnormal CSF amyloid-β1-42 and two neuronal injury

markers (CSF tau and MTL) had only one of the abnormal injury markers. This is likely because

the neuronal injury biomarkers measure different pathophysiologies, and abnormality in one does

not always mean that the other is abnormal as well, at least at the MCI stage. Subjects with both

abnormal injury markers had higher Alzheimer’s disease progression rates compared to those with

only one abnormal injury marker in combination with amyloid pathology. This is in-line with

previous studies (Scott et al., 2010; van Rossum et al., 2012) and suggests that the former group is

further in the disease process or has a more aggressive form of Alzheimer’s disease.

The lack of standardized biomarker cut-offs is a known drawback in the field. We applied centre-

specific biomarker cut-offs to correct for possible differences in lab procedures. Use of the same

CSF ELISA cut-off for all centres would have led to essentially the same results (Supplementary

Table 7). Although the use of predefined cut-offs likely resulted in somewhat lower sensitivities

and specificities compared to other studies that used cut-offs defined within the sample, our study

may better reflect the real diagnostic accuracy of biomarkers/the criteria.

This study has several limitations. Because the findings were based on memory clinic or research

populations, they may not be generalizable to other settings. For some subjects a MRI assessment

was not performed or data were not provided to us, although this is normally part of clinical

routine. No autopsy data were available, which might have led to misclassification of Alzheimer’s

disease. Furthermore, we used retrospective data so centres used different cognitive tests and

biomarker protocols. While this reflects current clinical practice, it could have introduced

variability. Analyses for the largest cohorts separately showed some variability in prevalence and

outcome of Alzheimer’s disease in subjects with MCI (Supplementary Tables 8 and 9). However,

as this variability is typically random, pooling data from all centres is likely to balance out on

average. Furthermore, as our main aim was to compare the sets of criteria, variability in

operationalization will affect each of the criteria similarly. Standardization of cognitive tests and

biomarkers will be an important goal to achieve in the future and many initiatives have started

working on this. But even after standardization the criteria may still perform differently in specific

settings. Because we used retrospective data, access to tests that measure non-memory domains

was limited. Our operationalization of atypical prodromal Alzheimer’s disease may therefore not

entirely reflect the clinical variants described in the IWG-2 criteria and may be less sensitive to

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detect atypical cognitive profiles. While the IWG-1 criteria recommended a cued recall test to

define memory impairment, such tests were not available for most studies and we used non-cued

memory tests as well. New prospective studies should include a wider range of cognitive tests to

improve operationalization of the criteria. We used CSF amyloid-β1-42 as amyloid marker while

use of amyloid-PET could have led to different results and would be interesting in light of the

IWG-2 criteria. The major strengths of our study include the large sample size of well-

characterized subjects and relatively long follow-up.

Our findings have several implications. While the IWG-1, IWG-2 and NIA-AA criteria for

prodromal Alzheimer’s disease can all be used to select subjects for therapeutic trials or clinical

follow-up as they all predict cognitive decline with reasonable accuracy, a certain set of criteria

may be preferred for specific purposes. In clinical trials, a high conversion rate is needed. If both

amyloid and neuronal injury markers are available, one could best select subjects according to the

IWG-2 prodromal Alzheimer’s disease group or NIA-AA high Alzheimer’s disease likelihood

group. This means that subjects with any MCI can be included. If only neuronal injury markers are

available, the IWG-1 criteria should be considered rather than the NIA-AA criteria because of the

higher specificity due to requirement of amnestic MCI for prodromal Alzheimer’s disease. In

clinical settings, a refined prognosis is needed and exclusion of the disease is important to reassure

patients. The NIA-AA criteria will then offer the most accurate prognosis. As Alzheimer’s disease

at the MCI stage can manifest as non-memory impairment, a broad definition of MCI should be

applied.

IAP and SNAP are heterogeneous conditions with subgroups progressing to Alzheimer’s disease-

type dementia and further studies are needed to characterize these subjects’ prognosis and

underlying pathophysiology.

Funding

The research leading to these results has received support from the Innovative Medicines Initiative

Joint Undertaking under EMIF grant agreement n° 115372, resources of which are composed of

financial contribution from the European Union's Seventh Framework Programme (FP7/2007-

2013) and EFPIA companies’ in kind contribution.

This research was performed within the framework of CTMM, The Centre for Translational

Molecular Medicine (www.ctmm.nl), project LeARN (grant 02N-101).

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The DESCRIPA study was funded by the European Commission within the 5th framework

program (QLRT-2001- 2455).

The AddNeuroMed study was funded by InnoMed (Innovative Medicines in Europe), an

Integrated Project funded by the European Union of the Sixth Framework program priority FP6-

2004-LIFESCIHEALTH-5, Life Sciences, Genomics and Biotechnology for Health.

The Coimbra Centre was funded by Project PIC/IC/ 83206/2007 da Fundação para a Ciência e

Tecnologia – Portugal.

Research of the VUmc Alzheimer centre is part of the neurodegeneration research program of the

Neuroscience Campus Amsterdam. The VUmc Alzheimer Centre is supported by Alzheimer

Nederland and Stichting VUmc fonds. The clinical database structure was developed with funding

from Stichting Dioraphte.

The Alzheimer's Disease Neuroimaging Initiative (ADNI; National Institutes of Health Grant U01

AG024904 and DOD ADNI Department of Defense award number W81XWH-12-2-0012) was

funded by the National Institute on Aging, the National Institute of Biomedical Imaging and

Bioengineering, and through generous contributions from the following: Alzheimer’s Association;

Alzheimer’s Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers

Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La

Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO

Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson

Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale

Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.;

Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian

Institutes of Health Research is providing funds to Rev December 5, 2013 support ADNI clinical

sites in Canada. Private sector contributions are facilitated by the Foundation for the National

Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute

for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative

Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory

for Neuro Imaging at the University of Southern California.

Supplementary material

Supplementary material is available at Brain online.

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Figure legends

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Figure 1 Alzheimer’s disease-type dementia survival probability by the IWG-1, IWG-2 and

NIA-AA criteria. The graphs represent the Alzheimer’s disease-type dementia survival

probability according to the IWG-1 (left), IWG-2 (middle), and NIA-AA (right) criteria, adjusted

for age, gender, education and centre. IWG-1: The group without prodromal Alzheimer’s disease

represents subjects without memory impairment and/or abnormal biomarker(s). The prodromal

Alzheimer’s disease group represents subjects with memory impairment and at least one abnormal

biomarker. IWG-2: The group without prodromal Alzheimer’s disease represents subjects with

normal CSF amyloid-β1-42 and/or tau. The prodromal Alzheimer’s disease group represents

subjects with abnormal CSF amyloid-β1-42 and tau. NIA-AA: The low Alzheimer’s disease

likelihood group represents subjects with normal amyloid and neuronal injury markers, the high

Alzheimer’s disease likelihood group represents subjects with both abnormal amyloid and

neuronal injury markers, the IAP group is a conflicting biomarker group with an abnormal

amyloid marker and normal neuronal injury marker, the SNAP group is a conflicting biomarker

group with an abnormal neuronal injury marker and normal amyloid marker, the intermediate

Alzheimer’s disease likelihood group represents subjects with an abnormal neuronal injury marker

without information on amyloid pathology, the inconclusive group represents subjects with a

normal neuronal injury marker without information on amyloid pathology. AD = Alzheimer’s

disease.

Figure 2 CSF amyloid-β1-42 levels above the cut-off in the SNAP group by outcome. Results

are CSF amyloid-β1-42 levels above the cut-off of subjects with SNAP who had Alzheimer’s

disease-type dementia, no dementia or non-Alzheimer’s disease dementia at follow-up. As

amyloid-β1-42 cut-offs were different for different studies, we compared the amyloid-β1-42 levels

above the cut-off (deviation from the cut-off) and not overall amyloid-β1-42 levels. The bold line

represents the mean CSF amyloid-β1-42 levels above the cut-off.

AD = Alzheimer’s disease, Aß = amyloid-β.

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Figure 1. Alzheimer’s disease-type dementia survival probability by the IWG-1, IWG-2, and NIA-AA criteria

The graphs represent the Alzheimer’s disease-type dementia survival probability according to the IWG-1 (left), IWG-2 (middle), and NIA-AA (right) criteria, adjusted for age, gender, education, and center.

IWG-1: The group without prodromal Alzheimer’s disease represents subjects without memory impairment and/or abnormal biomarker(s). The prodromal Alzheimer’s disease group represents subjects with memory impairment and at least one abnormal biomarker. IWG-2: The group without prodromal Alzheimer’s disease

represents subjects with normal CSF Aβ1-42 and/or tau. The prodromal Alzheimer’s disease group

represents subjects with abnormal CSF Aβ1-42 and tau. NIA-AA: The low-Alzheimer’s disease-likelihood group represents subjects with normal amyloid and neuronal injury markers, the high-Alzheimer’s disease-

likelihood group represents subjects with both abnormal amyloid and neuronal injury markers, the IAP group is a conflicting biomarker group with an abnormal amyloid marker and normal neuronal injury marker, the SNAP group is a conflicting biomarker group with an abnormal neuronal injury marker and normal amyloid

marker, the intermediate-Alzheimer’s disease-likelihood group represents subjects with an abnormal neuronal injury marker without information on amyloid pathology, the inconclusive group represents

subjects with a normal neuronal injury marker without information on amyloid pathology. AD=Alzheimer’s disease, IWG=International Working Group, NIA-AA=National Institute of Aging and Alzheimer’s Association,

IAP=isolated Alzheimer pathology, SNAP=suspected non-Alzheimer pathophysiology.

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Figure 2. CSF Aß1-42 levels above the cut-off in the SNAP group by outcome.

Results are CSF Aß1-42 levels above the cut-off of subjects with SNAP who had Alzheimer’s disease-type dementia, no dementia or non-AD dementia at follow-up. As Aß1-42 cut-offs were different for different studies, we compared the Aß1-42 levels above the cut-off (deviation from the cut-off) and not overall Aß1-42 levels. The bold line represents the mean CSF Aß1-42 levels above the cut-off. AD=Alzheimer’s disease,

Aß=amyloid beta, SNAP=Suspected Non-Alzheimer Pathophysiology.

138x93mm (300 x 300 DPI)

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Supplemental data

Prevalence and prognosis of Alzheimer’s disease at the mild cognitive impairment stage

Stephanie J. B. Vos PhD, Frans Verhey MD, Lutz Frölich MD, Johannes Kornhuber MD, Jens

Wiltfang MD, Wolfgang Maier MD, Oliver Peters MD, Eckart Rüther MD, Flavio Nobili MD,

Silvia Morbelli MD, Giovanni B. Frisoni MD, Alexander Drzezga MD, Mira Didic PhD, Bart N.

M. van Berckel MD, Andrew Simmons PhD, Hilkka Soininen MD, Iwona Kloszewska, Patrizia

Mecocci MD, Magda Tsolaki MD, Bruno Vellas, Simon Lovestone PhD, Cristina Muscio MS,

Sanna-Kaisa Herukka MD, Eric Salmon MD, Christine Bastin PhD, Anders Wallin MD, Arto

Nordlund PhD, Alexandre de Mendonça MD, Dina Silva PhD, Isabel Santana MD, Raquel Lemos

PhD, Sebastiaan Engelborghs MD, Stefan Van der Mussele PhD, the Alzheimer’s Disease

Neuroimaging Initiative, Yvonne Freund-Levi MD, Åsa K. Wallin MD, Harald Hampel MD,

Wiesje van der Flier PhD, Philip Scheltens MD, and Pieter Jelle Visser MD,

Supplemental Table 1. Neuropsychological tests by center and by cognitive domain

Supplemental Table 2. Biomarker cut-offs per center

Supplemental Table 3. Number of subjects by center and by biomarker

Supplemental Table 4. Sample demographics by biomarker groups

Supplemental Table 5. Alzheimer’s disease-type dementia survival probability based on the NIA-

AA classification in two groups

Supplemental Table 6. Annual Mini-Mental State Examination change for each biomarker group

by the IWG-1, IWG-2, and NIA-AA criteria

Supplemental Table 7. Alzheimer’s disease prevalence at the mild cognitive impairment stage and

dementia survival probability with abnormal CSF Aß1-42 and tau defined according to the same

ELISA cut-offs

Supplemental Table 8. Prevalence of Alzheimer’s disease at the mild cognitive impairment stage

for each large cohort separately

Supplemental Table 9. 3-year progression rate to Alzheimer’s disease-type dementia at last

follow-up for each large cohort separately

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Supplemental Figure 1. Annual Mini-Mental State Examination change for each biomarker group

by the IWG-1, IWG-2, and NIA-AA criteria

Supplemental Figure 2. Alzheimer’s disease-type dementia survival probability by subdivided

IWG-1 and IWG-2 criteria

Supplemental Text 1. Methods ADNI study

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Supplemental Table 1. Neuropsychological tests by center and by cognitive domain

Center / study Neuropsychological tests

Memory Language Executive function Visuoconstruction

AddNeuroMed

(multicenter)

CERAD word list CERAD verbal fluency animals 1

minute

- CERAD visuoconstruction

ADNI (multicenter) RAVLT Verbal fluency animals 1

minute

TMT part A and B -

Amsterdam RAVLT Verbal fluency animals 1

minute

TMT part A and B Rey figure copy test

Antwerp RBANS word list, WMS verbal

paired associations, logical memory,

RBANS story recall, HDS

RBANS verbal fluency animals

1 minute

TMT part A and B RBANS figure copy, cube

drawing, luria meander

Brescia RAVLT, story Brescia Verbal fluency animals 1

minute, phonemic fluency 1

minute

TMT part A and B Rey copy figure

Coimbra ADAS-Cog word list, free & cued

recall

Fluency animals 1minute TMT part A and B ADAS-Cog

DCN (multicenter) CERAD word list, WMS logical

memory

CERAD verbal fluency animals

1 minute

TMT part A and B CERAD visuoconstruction

DESCRIPA

(multicenter)

RAVLT and CERAD word list were

primary tests

Verbal fluency animals 1

minute

TMT part A and B Rey figure copy test and

CERAD figures were

primary tests

EADC-PET

(multicenter)

RAVLT and CERAD word list were

primary tests

Verbal fluency animals 1

minute

TMT part A and B Rey figure copy test and

CERAD figures were

primary tests

Gothenburg RAVLT FAS word fluency 1 minute

(x3)

TMT part A and B Rey figure copy test

Kuopio CERAD word list - - CERAD visuoconstruction

Liège RI-48 word list Verbal fluency animals 2

minutes

Stroop interference -

Lisbon CVLT Verbal fluency supermarket

items 1 minute

TMT part A and B Cube copy

If multiple tests were performed for a cognitive domain, tests were ranked by preference; if scores of the first test were not available, we used scores of the

second tests etc. CERAD=The Consortium to Establish a Registry for Alzheimer’s Disease, RAVLT=Rey auditory Verbal Learning Test, TMT=Trail Making

Test, RBANS=Repeatable Battery for the Assessment of Neuropsychological Status, WMS=Wechsler Memory Scale, HDS= Hierarchic Dementia Scale,

ADAS-Cog=Alzheimer's Disease Assessment Scale-cognitive subscale, CVLT= Californian Verbal Learning Test. DESCRIPA tests per center are described

elsewhere.

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Supplemental Table 2. Biomarker cut-offs per center

Center / study CSF Aß1-42

(pg/ml)**

CSF total tau

(pg/ml)**

CSF

phosphorylated

tau (pg/ml)**

FDG-PET Hippocampal volume Medial

temporal lobe

atrophyg

AddNeuroMed

(multicenter)*

- - - - Z-score <-0·0003 (calculated in

healthy controls)

> 2

ADNI (multicenter)*

<192a

>93a

>23a

- < 5·389 cm

3, LEAP method

b -

Amsterdam <551c >375

c >52

c - < 5·389

cm

3, LEAP method

b > 2

Antwerp <638·5 >296·5 >56·5 - - -

Brescia <500d

>450/>500d

- - < 5th

percentile of volume

distribution of controlse

> 2

Coimbra <542 >250 >35 - - > 2

DCN (multicenter)*

<500 >600 >61 - <4500 mm3

DESCRIPA

(multicenter)*

<551c

>375c

>52c

- < 5·389 cm3, LEAP method

b > 2

EADC-PET

(multicenter)*

<500d >450/>500

d - AD profile < 5

th percentile of volume

distribution of controlse

> 2

Gothenburg <450 >400 >80 - - -

Kuopio <452 >399 >70 - Right: men<14·9, women<15·3f

Left: men<14·3, woman<14·1f

-

Liège - - - AD profile - -

Lisbon <445 >300 >61 - Z-score <-1·5 SD -

*For the multicenter studies, biomarker analyses were performed centrally, as described elsewhere.

**CSF analyses were performed using

commercially available sandwich ELISAs for all centers except for the ADNI study, which used the multiplex xMAP Luminex platform.

PET=Positron Emission Tomography, CSF=cerebrospinal fluid, Aß=amyloid-beta, FDG= fludeoxyglucose. aShaw LM, Vanderstichele H, Knapik-

Czajka M, et al. Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol 2009;65:403–413; bVos

SJ, van Rossum IA, Verhey F, et al. Prediction of Alzheimer disease in subjects with amnestic and nonamnestic MCI. Neurology 2013;80:1124-1132; cMulder C, Verwey NA, van der Flier WM, et al. Amyloid-ß(1-42), total tau, and phosphorylated tau as cerebrospinal fluid biomarkers for the

diagnosis of Alzheimer disease. Clin Chem 2010;56:248 –253; dSjogren M, Vanderstichele H, Ågren H, et al. Tau and Abeta42 in cerebrospinal fluid

from healthy adults 21–93 years of age: establishment of reference values. Clin Chem 2001;47:1776–1781; eGaluzzi S, Geroldi C, Ghidoni R, et al.

The new Alzheimer’s criteria in a naturalistic series of patients with mild cognitive impairment. J neurol 2010; 257, 2004-14; fHerukka SK, Pennanen

C, Soininen H, Pirttila T. CSF Abeta42, tau and phosphorylated tau correlate with medial temporal lobe atrophy. J Alzheimers Dis 2008;14:51-7; gScheltens P, Leys D, Barkhof F, et al. Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal ageing: diagnostic

value and neuropsychological correlates. J Neurol Neurosurg Psychiatry 1992; 55, 967e972.

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Supplemental Table 3. Number of subjects by center and by biomarker

Center / study Total

N

Amyloid

marker

Injury marker

CSF

Aß1-42

CSF

tau

FDG-

PET

Hippocampal

volume

Medial

temporal

lobe

atrophy

AddNeuroMed 99 - - - 98 85

ADNI 300 155 155 - 300 -

Amsterdam 124 88 88 - 96 110

Antwerp 32 32 32 - - -

Brescia 80 56 56 - 78 58

Coimbra 36 16 16 - - 35

DCN 373 227 227 - 283 -

DESCRIPA 267 104 104 - 217 235

EADC-PET 125 31 31 125 9 9

Gothenburg 36 36 36 - - -

Kuopio 50 19 19 - 48 -

Liège 49 - - 49 - -

Lisbon 36 2 2 - 36 -

CSF=cerebrospinal fluid, Aß=amyloid-beta, FDG= fludeoxyglucose, PET=Positron

Emission Tomography.

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Supplemental Table 4. Sample demographics by biomarker groups

Total

sample

N=1607

1 marker

FDG-PET

N=140

1 marker

MTL

N=698

1 marker

FDG-PET

or MTL

N=841

2 markers

CSF Aß

and tau

N=200

2/3 markers

CSF Aß and

tau with or

without MTL

or FDG-PET

N=766

3/4 biomarkers

CSF Aß and tau

and MTL with

or without

FDG-PET

N=544

Age, y 70·1

(8·4)

71·5 (8·0) 71·0

(8·0)

71·1 (8·0) 66·8

(8·8)

68·9 (8·7) 69·5 (8·5)

Female, n 808

(50%)

64 (46%) 389

(56%)

455 (54%) 93 (47%) 353 (46%) 245 (45%)

Education, y 10·8

(4·3)

11·0 (4·2) 10·4

(4·6)

10·5 (4·5) 10·6

(2·9)

11·1 (4·1) 11·4 (4·3)

Amnestic mild cognitive impairment, n 1207

(75%)

134 (96%) 501

(72%)

638 (76%) 148

(74%)

569 (74%) 407 (75%)

Follow-up, y 2·4 (1·3) 2·7 (1·8) 2·2 (1·2) 2·3 (1·3) 2·4 (1·4) 2·4 (1·2) 2·4 (1·2)

APOE-ε4 560

(45%)

14 (39%) 218

(44%)

233 (44%) 79 (44%) 327 (47%) 235 (47%)

MMSE baseline 26·9

(2·3)

26·7 (2·1) 27·2

(2·3)

27·1 (2·2) 27·0

(2·6)

26·7 (2·4) 26·7 (2·3)

MMSE last follow-up 24·6

(4·5)

24·2 (3·3) 25·3

(4·1)

25·1 (4·0) 25·3

(4·5)

24·2 (4·8) 23·9 (4·9)

Progression to Alzheimer’s disease-

type dementia at last follow-up

539

(34%)

73 (52%) 193

(28%)

269 (32%) 59 (30%) 270 (35%) 200 (37%)

Progression to other dementia at last

follow-up

85 (5%) 7 (5%) 30 (4%) 37 (4%) 8 (4%) 48 (6%) 36 (7%)

Results are mean (SD) or number (%) for subgroups with only a neuronal injury marker and subgroups with amyloid and neuronal injury markers.

PET=Positron Emission Tomography, CSF=cerebrospinal fluid, Aß=amyloid-beta, FDG=fludeoxyglucose, MTL=medial temporal lobe,

APOE=Apolipoprotein, MMSE=Mini-Mental State Examination.

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Supplemental Table 5. Alzheimer’s disease-type dementia survival probability based on

dichotomized NIA-AA classification

*Estimated 3-year progression (cumulative incidence) rate to

Alzheimer’s disease-type dementia,

**Hazard ratios

(95% CI) for progression to Alzheimer’s disease-type dementia calculated using Cox regression analyses and

corrected for baseline age, gender, education and center. IWG=International Working Group, NIA-

AA=National Institute of Aging and Alzheimer’s Association.

NIA-AA criteria Prevalence of Alzheimer’s

disease at the

mild cognitive

impairment

stage

3-year progression

rate to

Alzheimer’s

disease-type

dementia*

Hazard Ratio**

(95% CI) P-value

Amyloid & neuronal injury markers

(A)

- Combined low-Alzheimer’s disease-

likelihood and conflicting groups

413 (54%) 19% Reference

- High-Alzheimer’s disease-likelihood

group

353 (46%) 60% 4.2 (3.1-5.7) <0.0001

(B)

- Low-Alzheimer’s disease-likelihood group 144 (19%) 5% Reference

- Combined conflicting and high-

Alzheimer’s disease-likelihood groups

622 (81%) 46% 10.1 (4.1-24.6) <0.0001

Only neuronal injury markers

- Inconclusive group 382 (45%) 20% Reference

- Intermediate-Alzheimer’s disease

likelihood group

459 (55%) 48% 2.9 (2.1-3.9) <0.0001

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Supplemental Table 6. Annual Mini-Mental State Examination change for each biomarker

group by the IWG-1, IWG-2, and NIA-AA criteria

Results are annual decline on the MMSE according to the criteria. IWG=International Working Group, NIA-

AA=National Institute of Aging and Alzheimer’s Association, MMSE=Mini-Mental State Examination.

Slope MMSE P-value slope P-value compared

to

reference group

IWG-1

No prodromal Alzheimer’s disease -0·53 (0·08) P<0·0001 Reference

Prodromal Alzheimer’s disease -1·32 (0·08) P<0·0001 P<0·0001

IWG-2

No prodromal Alzheimer’s disease -0·53 (0·12) P<0·0001 Reference

Prodromal Alzheimer’s disease -1·63 (0·12) P<0·0001 P<0·0001

NIA-AA

Low-Alzheimer’s disease-likelihood group -0·34 (0·22) P=0·12 Reference

High-Alzheimer’s disease-likelihood group -1·53 (0·11) P<0·0001 P<0·0001

Conflicting Isolated Amyloid Pathology group -0·40 (0·30) P=0·18 P=0·88

Conflicting Suspected Non-Alzheimer

Pathophysiology group

-0·50 (0·16) P=0·0016 P=0·55

Intermediate-Alzheimer’s disease-likelihood

group

-1·19 (0·12)

P<0·0001 P=0·014

Uninformative/inconclusive group -0·50 (0·11)

P<0·0001 P=0·52

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Supplemental Table 7. Alzheimer’s disease prevalence at the mild cognitive impairment stage

and dementia survival probability with abnormal CSF Aß1-42 and tau defined according to the

same ELISA cut-offs



**Hazard ratios

(95% CI) for progression to Alzheimer’s disease-type dementia calculated using Cox regression analyses and

corrected for baseline age, gender, education and center. CSF ELISA cutoffs were the same for each center

(Aß1-42<551, total tau>375, phosphorylated tau>52, from Mulder C, Verwey NA, van der Flier WM, et al.

Amyloid-ß(1-42), total tau, and phosphorylated tau as cerebrospinal fluid biomarkers for the diagnosis of

Alzheimer disease. Clin Chem 2010;56:248 –253). IWG=International Working Group, NIA-AA=National

Institute of Aging and Alzheimer’s Association.

Prevalence of

Alzheimer’s

disease at the

mild

cognitive

impairment

stage

3-year progression

rate to

Alzheimer’s

disease-type

dementia*

Hazard Ratio**

(95% CI) P-value

IWG-1

No prodromal Alzheimer’s disease 747 (47%) 22% Reference

Prodromal Alzheimer’s disease 860 (54%) 50% 2.9 (2.4-3.6) <0.0001

IWG-2

No prodromal Alzheimer’s disease 458 (60%) 22% Reference

Prodromal Alzheimer’s disease 308 (40%) 61% 4.0 (3.0-5.2) <0.0001

NIA-AA

Low-Alzheimer’s disease-likelihood

group

132 (17%) 6% Reference

High-Alzheimer’s disease-likelihood

group

347 (45%) 58% 12.6 (5.2-31.0) <0.0001

Conflicting Isolated Amyloid Pathology

group

46 (6%) 21% 4.6 (1.5-13.9) 0.0064


pathophysiology group

241 (32%) 25% 4.5 (1.8-11.2) 0.0015

Intermediate-Alzheimer’s disease-

likelihood group

459 (55%) 49% 9.4 (3.8-23.2) <0.0001

Uninformative/inconclusive group 382 (45%) 21% 3.2 (1.3-8.0) 0.0014

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Supplemental Table 8. Prevalence of Alzheimer’s disease at the mild cognitive impairment stage for each large cohort separately

Results are prevalence of Alzheimer’s disease according to the criteria for the six largest cohorts. For the EADC-PET cohort, results were not calculated for

the subgroup with two markers available, as the sample size was too small. IWG=International Working Group, NIA-AA=National Institute of Aging and Alzheimer’s Association, NA=not applicable.

AddNeuroMed N=99

ADNI N=300

Amsterdam N=124

DESCRIPA N=267

DCN N=373

EADC-PET N=125

IWG-1

No prodromal Alzheimer’s disease 53 (54%) 109 (36%) 36 (29%) 150 (56%) 195 (52%) 42 (34%)

Prodromal Alzheimer’s disease 46 (47%) 191 (64%) 88 (71%) 117 (44%) 178 (48%) 83 (66%)

IWG-2

No prodromal Alzheimer’s disease NA 60 (39%) 45 (51%) 56 (54%) 164 (72%) NA

Prodromal Alzheimer’s disease NA 95 (61%) 43 (49%) 48 (46%) 63 (28%) NA

NIA-AA


group

NA 10 (7%) 12 (14%) 12 (12%) 67 (30%) NA


group

NA 105 (68%) 43 (49%) 54 (52%) 72 (32%) NA

Conflicting Isolated Amyloid

Pathology group

NA 5 (3%) 3 (3%) 10 (10%) 11 (5%) NA



NA 35 (23%) 30 (34%) 28 (27%) 77 (34%) NA


likelihood group

46 (47%) 80 (55%) 26 (72%) 88 (54%) 65 (45%) 70 (75%)

Uninformative/inconclusive group 53 (54%) 65 (45%) 10 (28%) 75 (46%) 81 (56%) 24 (26%)

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Supplemental Table 9. 3-year progression rate to Alzheimer’s disease-type dementia for each large cohort separately

Results are progression to Alzheimer’s disease-type dementia after 3 years according to the criteria for the six largest cohorts. For the EADC-PET cohort,

results were not calculated for the subgroup with two markers available, as the sample size was too small. IWG=International Working Group, NIA-

AA=National Institute of Aging and Alzheimer’s Association, NA=not applicable.

AddNeuroMed

N=99

ADNI

N=300

Amsterdam

N=124

DESCRIPA

N=267

DCN

N=373

EADC-PET

N=125

IWG-1

No prodromal Alzheimer’s disease 7 (13%) 14 (13%) 9 (25%) 19 (13%) 11 (6%) 11 (26%)

Prodromal Alzheimer’s disease 11 (24%) 73 (38%) 35 (40%) 51 (44%) 65 (37%) 40 (48%)

IWG-2

No prodromal Alzheimer’s disease NA 6 (10%) 8 (18%) 9 (16%) 16 (10%) NA

Prodromal Alzheimer’s disease NA 40 (42%) 26 (61%) 26 (54%) 31 (49%) NA

NIA-AA


group

NA 0 (0%) 1 (8%) 0 (0%) 0 (0%) NA


group

NA 43 (41%) 26 (61%) 28 (52%) 33 (46%) NA

Conflicting Isolated Amyloid

Pathology group

NA 0 (0%) 0 (0%) 2 (20%) 2 (18%) NA



NA 3 (9%) 7 (23%) 5 (18%) 12 (16%) NA


likelihood group

11 (24%) 32 (40%) 9 (35%) 30 (34%) 20 (31%) 31 (44%)

Uninformative/inconclusive group 7 (13%) 9 (14%) 1 (10%) 5 (7%) 9 (11%) 5 (21%)

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Supplemental Figure 1. Annual Mini-Mental State Examination change for each biomarker group by the IWG-1, IWG-2, and NIA-AA

criteria

The graph shows annual decline on the MMSE according to the criteria. IWG-1: The group without prodromal Alzheimer’s disease represents subjects

without memory impairment and/or abnormal biomarker(s). The prodromal Alzheimer’s disease group represents subjects with memory impairment and at

least one abnormal biomarker. IWG-2: The group without prodromal Alzheimer’s disease represents subjects with normal CSF Aß1-42 and/or t-tau markers.

The prodromal Alzheimer’s disease group represents subjects with abnormal CSF Aß1-42 and/or t-tau markers. NIA-AA: The low-Alzheimer’s disease-

likelihood group represents subjects with normal amyloid and neuronal injury markers, the high-Alzheimer’s disease-likelihood group represents subjects

with both abnormal amyloid and neuronal injury markers, the Isolated Amyloid Pathology group is a conflicting biomarker group with an abnormal amyloid

marker and normal neuronal injury marker, the Suspected Non-Alzheimer Pathophysiology group is a conflicting biomarker group with an abnormal neuronal

injury marker and normal amyloid marker, the intermediate-Alzheimer’s disease-likelihood group represents subjects with an abnormal neuronal injury

marker without information on amyloid pathology, the inconclusive group represents subjects with a normal neuronal injury marker without information on

amyloid pathology. AD=Alzheimer’s disease, IWG=International Working Group, NIA-AA=National Institute of Aging and Alzheimer’s Association,

IAP=isolated amyloid pathology, SNAP=suspected non-Alzheimer pathophysiology.

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Supplemental Figure 2. Alzheimer’s disease-type dementia

survival probability by subdivided IWG-1 and IWG-2 criteria

The graph shows Alzheimer’s disease-type dementia survival probability for

typical and atypical prodromal Alzheimer’s disease according to the IWG

criteria.

IWG-1: the prodromal Alzheimer’s disease group represents subjects with

memory impairment and at least one abnormal biomarker.

IWG-2: the atypical prodromal Alzheimer’s disease group represents

subjects with naMCI and abnormal CSF Aß1-42 and tau markers, the

typical AD prodromal Alzheimer’s disease group represents subjects with

memory impairment and abnormal CSF Aß1-42 and tau markers.

AD=Alzheimer’s disease, naMCI-non-amnestic MCI.

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Supplemental Text 1. Methods ADNI Study.

Data used in the preparation of this article were partially obtained from the

Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu).

The ADNI was launched in 2003 by the National Institute on Aging (NIA), the

National Institute of Biomedical Imaging and Bioengineering (NIBIB), the Food and

Drug Administration (FDA), private pharmaceutical companies and non-profit

organizations, as a $60 million, 5-year public-private partnership. The primary goal of

ADNI has been to test whether serial magnetic resonance imaging (MRI), positron

emission tomography (PET), other biological markers, and clinical and

neuropsychological assessment can be combined to measure the progression of mild

cognitive impairment (MCI) and early Alzheimer’s disease(AD). Determination of

sensitive and specific markers of very early AD progression is intended to aid

researchers and clinicians to develop new treatments and monitor their effectiveness,

as well as lessen the time and cost of clinical trials. The Principal Investigator of this

initiative is Michael W. Weiner, MD, VA Medical Center and University of California

–San Francisco. ADNI is the result of efforts of many co-investigators from a broad

range of academic institutions and private corporations, and subjects have been

recruited from over 50 sites across the U.S. and Canada. The initial goal of ADNI was

to recruit 800 subjects but ADNI has been followed by ADNI-GO and ADNI-2. To

date these three protocols have recruited over 1500 adults, ages 55 to 90,to participate

in the research, consisting of cognitively normal older individuals, people with early or

late MCI, and people with early AD. The follow up duration of each group is specified

in the protocols for ADNI-1, ADNI-2 and ADNI-GO. Subjects originally recruited for

ADNI-1 and ADNI-GO had the option to be followed in ADNI-2. For up-to-date

information, see www.adni-info.org.

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See Schott for a scientific commentary on this article (doi:10.1093/brain/).

Vos et al. compare the prevalence and prognosis of Alzheimer’s disease at the

mild cognitive impairment stage based on the IWG-1, IWG-2 and NIA-AA criteria.

All three aid identification of early Alzheimer’s disease, but combining amyloid

and neuronal injury markers according to the NIA-AA criteria offers the most

accurate prognosis.

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Table 1 Classification according to the IWG-1, IWG-2 and NIA-AA criteria

Criteria Definition

IWG-1 (2007)

No prodromal Alzheimer’s disease No memory impairment or normal biomarkers

Prodromal Alzheimer’s disease Memory impairment, at least one abnormal Alzheimer’s disease

biomarker

IWG-2 (2014)

No prodromal Alzheimer’s disease Any cognitive impairment, normal CSF amyloid-β1-42 and/or

tau or normal amyloid PET scana

Prodromal Alzheimer’s disease Any cognitive impairment, abnormal CSF amyloid-β1-42 and tau

or abnormal amyloid PET scana

NIA-AA (2011)

Low Alzheimer’s disease likelihood

group

Any cognitive impairment, normal amyloid and neuronal

injury markers

High Alzheimer’s disease likelihood

group

Any cognitive impairment, abnormal amyloid and neuronal

injury markers

Conflicting IAP group Any cognitive impairment, abnormal amyloid and normal

neuronal injury marker

Conflicting SNAP group Any cognitive impairment, normal amyloid and abnormal

neuronal injury marker

Intermediate Alzheimer’s disease

likelihood group

Any cognitive impairment, one marker testedb and abnormal

Inconclusive/uninformative group Any cognitive impairment, one marker testedb and normal

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Amyloid marker = CSF amyloid-β1-42; neuronal injury marker = CSF tau/medial temporal lobe

atrophy score/hippocampal volume/FDG-PET, cognitive impairment is defined as Z-score < −1.5.

aIn our study, CSF data are used for subject classification;

bIn our study, only neuronal injury markers were tested.

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Table 2 Demographics and clinical outcome according to the IWG-1, IWG-2 and NIA-AA criteria

IWG-1 criteria IWG-2 criteria NIA-AA criteria

No

prodromal

Alzheimer

’s disease

Prodrom

al

Alzheim

er’s

disease

No

prodromal

Alzheimer

’s disease

Prodrom

al

Alzheim

er’s

disease

Low

Alzheimer’

s disease

likelihood

High

Alzheimer

’s disease

likelihood

Conflicting

A:

IAP

Conflicting B:

SNAP

Intermedia

te

Alzheimer’

s disease

likelihood

Uninformati

ve/inconclu

sive

Normal

markers or

no

amnestic

mild

cognitive

impairmen

t

n = 757

Amnesti

c mild

cognitive

impairm

ent and

at least

1 marker

+

n = 850

CSF

markers −

n = 458

CSF

markers

+

n = 308

Amyloid −

Injury −

n = 144

Amyloid +

Injury +

n = 353

Amyloid +

Injury −

n = 49

Amyloid -

Injury +

n = 220

Amyloid ?

Injury +

n = 459

Amyloid ?

Injury −

n = 382

Age, years 68.6 (8.7)P 71.3

(7.9)

67.2 (8.9)

P 71.4

(7.6)

62.9

(9.0)H,A,B,I,

U

71.4

(7.6)L,A,B,I,

U

66.1

(7.7)L,H,B,I,U

69.4 (8.3)L,H,A,I

72.8

(7.3)L,H,A,B,

U

69.0

(8.4)L,H,A,I

Female, n 406

(54%)P

402

(47%)

206 (45%) 147

(48%)

63 (44%)U

165

(47%)U

21 (43%)U 104 (47%)

U 223

(49%)U

232

(61%)L,H,A,B,

I

Education, years 10.3 (4.4)P 11.2

(4.2)

10.6 (3.9)P 11.9

(4.1)

10.5 (3.2)H

11.7

(4.3)L,B,I,U

11.0 (4.0) 10.5 (4.0)H

10.7 (4.4)H

10.3 (4.8)H

Amnestic mild

cognitive impairment,

n

357

(47%)P

850

(100%)

310

(68%)P

259

(84%)

98

(68%)H,I

293

(83%)L,A,B,

U

30 (61%)H,I

148 (67%)H,I

379

(83%)L,A,B,

U

259

(68%)H,I

Follow-up, years 2.4 (1.3) 2.3 (1.3) 2.4 (1.3) 2.3 (1.2) 2.4 (1.1)

2.3 (1.2)

2.7 (1.5)I

2.5 (1.3)I

2.2

(1.3)A,B,U

2.4 (1.4)I

APOE-ε4 218

(37%)P

342

(53%)

137

(33%)P

190

(66%)

36

(28%)H,A,I

207

(63%)L,A,B,

22 (46%)L,H

62 (32%)H,I

144

(51%)L,H,B,

89 (35%)H,I

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I,U U

MMSE

at baseline

27.5 (2.2)P 26.4

(2.3)

27.1 (2.3)P 26.2

(2.5)

27.7

(2.3)H,B,I

26.2

(2.4)L,A,B,I,

U

27.6

(1.9)H,B,I

26.7

(2.3)L,H,A,U

26.7

(2.2)L,H,A,U

27.6

(2.2)H,B,I

MMSE

at last follow-up

26.2 (3.9)P 23.3

(4.5)

25.8 (3.9)P 22.4

(5.0)

27.0

(3.2)H,B,I

22.5

(4.9)L,A,B,I,

U

26.3 (4.0)H,I

25.7 (4.0)L,H,I

24.2

(3.8)L,H,A,B,

U

26.2 (4.0)H,I

Progression to

Alzheimer’s disease-

type dementia at last

follow-up

134

(18%)P

405

(48%)

84 (18%)P

186

(60%)

5

(4%)H,A,B,I,

U

207

(59%)L,A,B,

I,U

11

(22%)L,H,I

47 (21%)L,H,I

201

(44%)L,H,A,

B,U

68

(18%)L,H,I

Time to Alzheimer’s

disease-type

dementia, years

2.4 (1.3) 2.3 (1.3) 2.5 (1.7) 2.3 (1.2) 2.9 (1.1) 2.3 (1.2)

3.1 (1.8) 2.6 (1.8) 2.3 (1.3)U

2.7 (1.5)I

Progression to non-

Alzheimer’s disease

dementia at last

follow-up

45 (6%) 40 (5%) 43 (9%)P 5 (2%) 15

(10%)H,U

10 (3%)L,B

2 (4%) 21 (10%)H,U

26 (6%) 11 (3%)L,B

Diagnosis of non-

Alzheimer’s disease

dementia

Frontotemporal

dementia

15 9 13 7 6 8 3

Lewy body dementia 12 4 7 5 2 8 1

Vascular dementia 7 1 4 1 2 1 1 2 2 1

Parkinson’s disease

dementia

2 2 1

Progressive

supranuclear palsy

1 1

Alcohol-related

dementia

1 1 1

Not available 10 23 16 4 1 8 1

10

8 5

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Results are mean (SD) for continuous variables or frequency (%).

MMSE = Mini-Mental State Examination (range 0–30)

APOE genotype was only available in a subgroup of the sample: IWG-1 no prodromal Alzheimer’s disease n = 593 and prodromal Alzheimer’s disease n = 641; IWG-2 no

prodromal Alzheimer’s disease n = 410 and prodromal Alzheimer’s disease n = 289; NIA-AA Low n = 128, High n = 327, IAP n = 48, SNAP n = 196, Intermediate n = 281,

Inconclusive n = 254.

LP < 0.05 compared to low Alzheimer’s disease likelihood

HP < 0.05 compared to high Alzheimer’s disease likelihood

AP < 0.05 compared to conflicting A group IAP

BP < 0.05 compared to conflicting B group SNAP

IP < 0.05 compared to intermediate Alzheimer’s disease likelihood

UP < 0.05 compared to uninformative/inconclusive group.

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Table 3 Alzheimer’s disease-type dementia survival probability by the IWG-1, IWG-2

and NIA-AA criteria



**Hazard ratios (95% CI) for progression to Alzheimer’s disease-type dementia calculated using Cox

regression analyses and corrected for baseline age, gender, education and centre.

3-year progression

rate to Alzheimer’s

disease-type

dementia*

Hazard ratio**

(95% CI)

P-value

IWG-1

No prodromal Alzheimer’s disease 21% Reference

Prodromal Alzheimer’s disease 50% 3.0 (2.4–3.7) <0.0001

IWG-2

No prodromal Alzheimer’s disease 22% Reference

Prodromal Alzheimer’s disease 61% 4.0 (3.0–5.2) <0.0001

NIA-AA

Low Alzheimer’s disease likelihood group 5% Reference

High Alzheimer’s disease likelihood group 59% 14.4 (5.9–35.2) <0.0001

Conflicting IAP group 22% 4.6 (1.6–13.2) 0.0050

Conflicting SNAPgroup 24% 4.7 (1.8–11.9) 0.0011

Intermediate Alzheimer’s disease likelihood group 49% 10.2 (4.1–25.2) <0.0001

Uninformative/inconclusive group 21% 3.5 (1.4–8.8) 0.0079

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Table 4 Overlap in subject classification according to the IWG-1, IWG-2 and NIA-AA criteria by outcome after 3 years

Results are total number of subjects (% of subjects with Alzheimer’s disease-type dementia after 3 years of follow-up).

NIA-AA

Amyloid and neuronal injury markers (n = 766) Only a neuronal injury marker (n =

841)

Low

Alzheimer’

s disease

likelihood

(n = 144)

High

Alzheimer’s

disease

likelihood (n

= 353)

Conflicting:

IAP

(n = 49)

Conflicting:

SNAP (n = 220)

Intermediate

Alzheimer’s

disease likelihood

(n = 459)

Uninformative/

Inconclusive

(n = 382)

IWG-1 No prodromal Alzheimer’s disease 144 (2%) 60 (45%) 19 (11%) 72 (11%) 80 (19%) 382 (12%)

Prodromal Alzheimer’s disease - 293 (49%) 30 (23%) 148 (20%) 379 (39%) -

IWG-2 No prodromal Alzheimer’s disease 144 (2%) 45 (42%) 49 (18%) 220 (17%) NA NA

Prodromal Alzheimer’s disease - 308 (49%) - - NA NA

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NA = not applicable

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Table 5 Predictive accuracy of the IWG-1, IWG-2 and NIA-AA criteria for Alzheimer’s disease-type dementia after 3 years

Sample Sensitivity Specificity Positive

predictive value

Negative

predictive value

Youden index

Amyloid and neuronal injury markers

IWG-1 0.82 (0.77–0.87) 0.47 (0.43–0.51) 0.38 (0.34–0.43) 0.86 (0.83–0.90) 0.29 (0.22–0.35)

IWG-2 0.69 (0.63–0.75) 0.71 (0.67–0.75) 0.49 (0.43–0.55) 0.85 (0.82–0.88) 0.40 (0.33–0.47)

NIA-AA (A) high versus conflicting/low 0.77 (0.72–0.83) 0.66 (0.63–0.70) 0.48 (0.43–0.53) 0.88 (0.85–0.91) 0.44 (0.37–0.51)

NIA-AA (B) conflicting/high versus low 0.99 (0.97–1.00) 0.26 (0.22–0.29) 0.35 (0.31–0.39) 0.98 (0.96–1.00) 0.24 (0.20–0.28)

Only a neuronal injury marker

IWG-1 0.71 (0.64–0.77) 0.63 (0.60–0.67) 0.39 (0.34–0.44) 0.87 (0.83–0.90) 0.34 (0.27–0.41)

NIA-AA inconclusive versus

intermediate

0.78 (0.72–0.83) 0.53 (0.49–0.57) 0.36 (0.31–0.40) 0.88 (0.84–0.91) 0.31 (0.24–0.38)

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Results are predictive accuracy for Alzheimer’s disease-type dementia after 3-year follow-up according to the criteria for the subgroup with amyloid and

neuronal injury markers (n = 766) and for the subgroup with only a neuronal injury marker (n = 841). For the IWG-1 and IWG-2 criteria, groups are defined

as no prodromal Alzheimer’s disease versus prodromal Alzheimer’s disease.

Youden index = sensitivity + specificity−1.

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Table 6 Classification based on amyloid marker and CSF tau or medial temporal lobe neuronal injury marker

IWG-1 criteria NIA-AA criteria

Normal

group

Amnestic mild cognitive

impairment and at least

one marker +

Amyloid −

Injury −

Amyloid +

Injury +

Amyloid +

Injury −

Amyloid −

Injury +

CSF amyloid-β1-42 and tau, n = 766

Prevalence 327 (43%) 439 (57%) 198 (26%) 308 (40%) 94 (12%) 166 (22%)



55 (17%) 215 (49%) 12 (6%) 186 (60%) 32 (34%) 40 (24%)

CSF amyloid-β1-42 and MTL, n =

544

Prevalence 240 (44%) 304 (56%) 156 (29%) 191 (35%) 102 (19%) 95 (18%)



42 (18%) 158 (52%) 14 (9%) 122 (64%) 28 (28%) 36 (38%)

Results are prevalence and progression rate for subject classifications based on CSF amyloid-β1-42 and tau versus CSF amyloid-β1-42 and medial

temporal lobe.

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MTL = medial temporal lobe

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Table 7 Classification based on amyloid marker and two neuronal injury markers

Amyloid marker Amyloid + (n = 286) Amyloid − (n = 258)

Neuronal injury markers Tau −

MTL −

Tau +

MTL −

Tau -

MTL +

Tau+

MTL +

Tau −

MTL −

Tau +

MTL −

Tau −

MTL +

Tau+

MTL +

Prevalence within amyloid subgroup 37 (13%) 58 (20%) 25 (9%) 168 (58%) 91 (35%) 65 (25%) 39 (15%) 63 (24%)

Prevalence in total group 37 (7%) 58 (11%) 25 (5%) 166 (31%) 91 (17%) 65 (12%) 39 (7%) 63 (12%)



12 (32%) 24 (41%) 9 (36%) 113 (68%) 4 (4%) 10 (15%) 5 (13%) 23 (37%)

Results are prevalence and progression rate for subject classifications based on CSF amyloid-β1-42, tau and medial temporal lobe.

MTL=medial temporal lobe.

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Prevalence and prognosis of Alzheimer’s disease at the mild cognitive impairment stage

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