Literature DB >> 20541287

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

M Lorenzi1, M Donohue, D Paternicò, C Scarpazza, S Ostrowitzki, O Blin, E Irving, G B Frisoni.   

Abstract

Clinical trials of disease modifying drugs for Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI) might benefit from enrichment with true AD cases. Four hundred five MCI patients (143 converters and 262 nonconverters to AD within 2 years) of the Alzheimer's disease Neuroimaging Initiative (ADNI) were used. Markers for enrichment were hippocampal atrophy on magnetic resonance (MRI), temporoparietal hypometabolism on FDG PET, cerebrospinal fluid (CSF) biomarkers (Abeta42, tau, and phospho-tau), and cortical amyloid deposition (11C-PIB positron emission tomography (PET)). Two separate enrichment strategies were tested to A) maximize the proportion of MCI converters screened in, and B) minimize the proportion of MCI converters screened out. Based on strategy A, when compared with no enrichment and ADAS-Cog as an outcome measure (sample size of 834), enrichment with 18F-FDG PET and hippocampal volume lowered samples size to 260 and 277 cases per arm, but at the cost of screening out 1,597 and 434 cases per arm. When compared with no enrichment and clinical dementia rating (CDR-SOB) as an outcome measure (sample size of 674), enrichment with hippocampal volume and Abeta42 lowered sample sizes to 191 and 291 cases per arm, with 639 and 157 screened out cases. Strategy B reduced the number of screened out cases (740 for [11C]-PIB PET, 101 hippocampal volume, 82 ADAS-COG and 330 for [18F]-FDG PET) but at the expense of decreased power and a relative increase size (740 for [11C]-PIB PET, 676 for hippocampal volume, 744 for ADAS-Cog, and 517 for [18F]-FDG PET). Enrichment comes at the price of an often relevant proportion of screened out cases, and in clinical trial settings, the balance between enrichment of screened in and loss of screened out patients should be critically discussed. 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20541287     DOI: 10.1016/j.neurobiolaging.2010.04.036

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  29 in total

1.  Characterizing Alzheimer's disease using a hypometabolic convergence index.

Authors:  Kewei Chen; Napatkamon Ayutyanont; Jessica B S Langbaum; Adam S Fleisher; Cole Reschke; Wendy Lee; Xiaofen Liu; Dan Bandy; Gene E Alexander; Paul M Thompson; Leslie Shaw; John Q Trojanowski; Clifford R Jack; Susan M Landau; Norman L Foster; Danielle J Harvey; Michael W Weiner; Robert A Koeppe; William J Jagust; Eric M Reiman
Journal:  Neuroimage       Date:  2011-01-27       Impact factor: 6.556

Review 2.  The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Enchi Liu; John C Morris; Ronald C Petersen; Andrew J Saykin; Mark E Schmidt; Leslie Shaw; Judith A Siuciak; Holly Soares; Arthur W Toga; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2011-11-02       Impact factor: 21.566

3.  Estimating sample sizes for predementia Alzheimer's trials based on the Alzheimer's Disease Neuroimaging Initiative.

Authors:  Joshua D Grill; Lijie Di; Po H Lu; Cathy Lee; John Ringman; Liana G Apostolova; Nicole Chow; Omid Kohannim; Jeffrey L Cummings; Paul M Thompson; David Elashoff
Journal:  Neurobiol Aging       Date:  2012-04-13       Impact factor: 4.673

4.  Simulating effects of biomarker enrichment on Alzheimer's disease prevention trials: conceptual framework and example.

Authors:  Jeannie-Marie S Leoutsakos; Alexandra L Bartlett; Sarah N Forrester; Constantine G Lyketsos
Journal:  Alzheimers Dement       Date:  2013-08-15       Impact factor: 21.566

5.  Unbiased comparison of sample size estimates from longitudinal structural measures in ADNI.

Authors:  Dominic Holland; Linda K McEvoy; Anders M Dale
Journal:  Hum Brain Mapp       Date:  2011-08-09       Impact factor: 5.038

Review 6.  Role of cerebrospinal fluid and plasma biomarkers in the diagnosis of neurodegenerative disorders and mild cognitive impairment.

Authors:  Luis F Gonzalez-Cuyar; Joshua A Sonnen; Kathleen S Montine; C Dirk Keene; Thomas J Montine
Journal:  Curr Neurol Neurosci Rep       Date:  2011-10       Impact factor: 5.081

7.  Alzheimer Disease Biomarkers as Outcome Measures for Clinical Trials in MCI.

Authors:  Anna Caroli; Annapaola Prestia; Sara Wade; Kewei Chen; Napatkamon Ayutyanont; Susan M Landau; Cindee M Madison; Cathleen Haense; Karl Herholz; Eric M Reiman; William J Jagust; Giovanni B Frisoni
Journal:  Alzheimer Dis Assoc Disord       Date:  2015 Apr-Jun       Impact factor: 2.703

Review 8.  CSF biomarkers for amyloid and tau pathology in Alzheimer's disease.

Authors:  Hanna Rosenmann
Journal:  J Mol Neurosci       Date:  2011-11-05       Impact factor: 3.444

9.  Operationalizing hippocampal volume as an enrichment biomarker for amnestic mild cognitive impairment trials: effect of algorithm, test-retest variability, and cut point on trial cost, duration, and sample size.

Authors:  Peng Yu; Jia Sun; Robin Wolz; Diane Stephenson; James Brewer; Nick C Fox; Patricia E Cole; Clifford R Jack; Derek L G Hill; Adam J Schwarz
Journal:  Neurobiol Aging       Date:  2013-10-03       Impact factor: 4.673

Review 10.  Using Pittsburgh Compound B for in vivo PET imaging of fibrillar amyloid-beta.

Authors:  Ann D Cohen; Gil D Rabinovici; Chester A Mathis; William J Jagust; William E Klunk; Milos D Ikonomovic
Journal:  Adv Pharmacol       Date:  2012
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