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Enrichment through biomarkers in clinical trials

of Alzheimer's drugs in patients with mild

cognitive impairmentMarco Lorenzi; Michael Donohue; Donata Paternicò; Cristina Scarpazza;

Susanne Ostrowitzki; Olivier Blin; Elaine Irving; Giovanni B Frisoni and the Alzheimer's Disease Neuroimaging Initiative

2Frisoni et al. Nat Rev Neurol 2010

100%

0%

Ma

rke

r a

bn

orm

ality

(%

)

Normal MCI Dementia

Clinical Trials on MCI

Frisoni et al, 2010 -Jack et al, 2010

Earliest stage for recruiting patients with

Alzheimer’s Disease

Maximal effectiveness of treatments with drugs

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Clinical Trials on MCI

Feldman et al. 2007, Loy and Schneider, 2006, Petersen et al., 2005, Raschetti et al., 2007, Salloway et al., 2004 Potential Cause:

(Visser et al, 2005)

MCI population inhomogeneity

NO significant treatment effect

~50% converters to

Alzheimer

~50% non converters

Trials with anti-dementia drugs on MCI

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Enrichment of the statistical population with true AD cases

A strategy to increase the statistical power

MCI future converters

MCI non converters

Definition of an optimal marker for screening

SCREENED POSITIVE

SCREENED NEGATIVE

• Maximize true AD screened-in

(true positive rate)

• Minimize true AD screened-out

(false negative rate)

Aim of the studyInvestigate the enrichment properties of the different

markers employed in AD

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MCI and healthy elders from the ADNI Dataset

Candidate markers (Dubois et al, 2007)

• Functional (Temporoparietal hypometabolism)

• Structural (Hippocampal atrophy)

• Molecular (CSF biomarkers, cortical amyloid deposition)

• Cognitive (ADAS-cog scale)

PALZ score - Herholz et al, 2002

Methods

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Analysis of the marker “X”Enrichment strategy A

Modeling the marker’s distribution on healthy elders

70th 85th 90th 99th Definition of the thresholds from fixed percentiles in the healthy

population

Computation of the true positive rate

Distribution on MCI converters

Distribution on MCI non converters

Screening of the MCI population based on the thresholds

OUT IN

Marker values

Den

sity

Define the threshold maximizing the true positive rate

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- Efficiency criterium -

Minimize the loss of true Alzheimer’s case

Analysis of the marker “X”Enrichment strategy B

Marker values

Den

sity

Marker values

Fal

se N

egat

ive

Rat

e

Optimal thresholdMCInc MCIc

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Analysis of the marker “X”Sample size analysis

Enrichment strategy A/B

Optimal thresholds A/B

Sample size computation

(24 months, 25% efficacy, 90% power)

Outcome ADAS-COG and CDR-SOB

Screening of the ADNI MCI population

Marker “X”

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Results Enrichment Strategy A

Marker (# subjects) Percentile (marker’s value)

True positive rate

Cortical Amyloid Deposition (64) 95th (1.86 cm3) 60%

Hippocampal volume (399) 99th (2,819 mm3) 59%

Temporoparietal hypometabolism (207)

99th (26,848 t-score) 53%

ADAS-Cog (402) 99th (19.4) 49%

CSF Tau (196) 70th (76.2 pg/ml) 47%

CSF tau/abeta42 (196) 85th (0.59) 47%

CSF abeta42 (196) 70th (165.8 pg/ml) 47%

None ~ 30%

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Results Enrichment Strategy A

Cortical Amyloid Deposition (64 subjects)

Ctrls

MCIc

MCInc

Hippocampal Volume (399 subjects)

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Results Enrichment Strategy A

Ratio MCI converters/MCI non converters at the optimal thresholds

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Results Enrichment Strategy A

Sample size

ADAS-Cog

CDR

Screened out

Sample size Screened out

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Results Enrichment Strategy B

Marker (# subjects) Percentile

(marker’s value)

False negative rate

ADAS-Cog (402) 58th (10.3) 7.5%

Cortical Amyloid Deposition (64)

85th (1.58 cm3) 9%

Temporoparietal hypometabolism (207)

62nd (6,078 t-score) 16%

Hippocampal volume (399) 44th (3,806 mm3) 17%

CSF biomarkers: FNR monotonously decreasing

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Sample size Screened out

Sample size Screened out

ADAS-Cog

CDR

Results Enrichment Strategy B

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Conclusions

Significant enrichment of groups of MCI patients enrolled in clinical trials of AD drugs with “true AD cases”

Hippocampal volumetry might be an efficient enrichment strategy

Trade-off screening costs/statistical power

2 years follow-up

Poor representation of some markers in the dataset

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Thank you!