Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease.
In: Alzheimer's & Dementia: The Journal of the Alzheimer's Association, Jg. 20 (2024-04-01), Heft 4, S. 2698-2706
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Zugriff:
INTRODUCTION: Increasing evidence suggests that amyloid reduction could serve as a plausible surrogate endpoint for clinical and cognitive efficacy. The double‐blind phase 3 DIAN‐TU‐001 trial tested clinical and cognitive declines with increasing doses of solanezumab or gantenerumab. METHODS: We used latent class (LC) analysis on data from the Dominantly Inherited Alzheimer Network Trials Unit 001 trial to test amyloid positron emission tomography (PET) reduction as a potential surrogate biomarker. RESULTS: LC analysis categorized participants into three classes: amyloid no change, amyloid reduction, and amyloid growth, based on longitudinal amyloid Pittsburgh compound B PET standardized uptake value ratio data. The amyloid‐no‐change class was at an earlier disease stage for amyloid amounts and dementia. Despite similar baseline characteristics, the amyloid‐reduction class exhibited reductions in the annual decline rates compared to the amyloid‐growth class across multiple biomarker, clinical, and cognitive outcomes. DISCUSSION: LC analysis indicates that amyloid reduction is associated with improved clinical outcomes and supports its use as a surrogate biomarker in clinical trials. Highlights: We used latent class (LC) analysis to test amyloid reduction as a surrogate biomarker.Despite similar baseline characteristics, the amyloid‐reduction class exhibited remarkably better outcomes compared to the amyloid‐growth class across multiple measures.LC analysis proves valuable in testing amyloid reduction as a surrogate biomarker in clinical trials lacking significant treatment effects. [ABSTRACT FROM AUTHOR]
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Examining amyloid reduction as a surrogate endpoint through latent class analysis using clinical trial data for dominantly inherited Alzheimer's disease.
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Autor/in / Beteiligte Person: | Wang, Guoqiao ; Li, Yan ; Xiong, Chengjie ; Benzinger, Tammie L. S. ; Gordon, Brian A. ; Hassenstab, Jason ; Aschenbrenner, Andrew J. ; McDade, Eric ; Clifford, David B. ; Libre‐Guerra, Jorge J. ; Shi, Xinyu ; Mummery, Catherine J. ; van Dyck, Christopher H. ; Lah, James J. ; Honig, Lawrence S. ; Day, Gregg ; Ringman, John M. ; Brooks, William S. ; Fox, Nick C. ; Suzuki, Kazushi |
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Zeitschrift: | Alzheimer's & Dementia: The Journal of the Alzheimer's Association, Jg. 20 (2024-04-01), Heft 4, S. 2698-2706 |
Veröffentlichung: | 2024 |
Medientyp: | academicJournal |
ISSN: | 1552-5260 (print) |
DOI: | 10.1002/alz.13735 |
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