Enrichment through biomarkers in clinical trials of Alzheimer's drugs in patients with mild

1. Marco Lorenzi; Michael Donohue; Donata Paternicò; Cristina Scarpazza; Susanne Ostrowitzki; Olivier Blin; Elaine Irving; Giovanni B Frisoni and the Alzheimer's Disease Neuroimaging Initiative Enrichment through biomarkers in clinical trials of Alzheimer's drugs in patients with mild cognitive impairment

2. Clinical Trials on MCI Normal MCI Dementia Earliest stage for recruiting patients with Alzheimer’s Disease Maximal effectiveness of treatments with drugs Frisoni et al, 2010 -Jack et al, 2010

3. Clinical Trials on MCI Trials with anti-dementia drugs on MCI NO significant treatment effect 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 ~50% converters to Alzheimer ~50% non converters

4. A strategy to increase the statistical power Enrichment of the statistical population with true AD cases Definition of an optimal marker for screening MCI future converters MCI non converters • Maximize true AD screened-in • (true positive rate) Aim of the study Investigate the enrichment properties of the different markers employed in AD SCREENED NEGATIVE SCREENED POSITIVE • Minimize true AD screened-out • (false negative rate)

5. Methods MCI and healthy elders from the ADNI Dataset Candidate markers (Dubois et al, 2007) • Cognitive(ADAS-cog scale) • Structural(Hippocampal atrophy) • Functional (Temporoparietal hypometabolism) PALZ score - Herholz et al, 2002 • Molecular (CSF biomarkers, cortical amyloid deposition)

6. Analysis of the marker “X” Enrichment strategy A Modeling the marker’s distribution on healthy elders Distribution on MCI converters Distribution on MCI non converters 70th 85th 90th 99th Definition of the thresholds from fixed percentiles in the healthy population Density Screening of the MCI population based on the thresholds OUT IN Computation of the true positive rate Define the threshold maximizing the true positive rate Marker values

7. Analysis of the marker “X” Enrichment strategy B MCInc MCIc Optimal threshold - Efficiency criterium - Minimize the loss of true Alzheimer’s case Density False Negative Rate Marker values Marker values

8. Analysis of the marker “X” Sample size analysis Marker “X” Enrichment strategy A/B Sample size computation (24 months, 25% efficacy, 90% power) Outcome ADAS-COG and CDR-SOB Optimal thresholds A/B Screening of the ADNI MCI population

9. Results Enrichment Strategy A

10. Ctrls MCIc MCInc Results Enrichment Strategy A Cortical Amyloid Deposition (64 subjects) Hippocampal Volume (399 subjects)

11. Results Enrichment Strategy A Ratio MCI converters/MCI non converters at the optimal thresholds

12. Results Enrichment Strategy A Sample size Screened out ADAS-Cog Sample size Screened out CDR

13. Results Enrichment Strategy B CSF biomarkers: FNR monotonously decreasing

14. Results Enrichment Strategy B Sample size Screened out ADAS-Cog Sample size Screened out CDR

15. 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

16. Thank you!