Predicting cognitive function in Alzheimer's clinical trials via amyloid β‐protein biomarkers
Year: 2026
Type: article
Study designs: Systematic Review, Meta-Analysis
Abstract: OBJECTIVES: This study investigates the association between amyloid-β (Aβ) biomarkers and clinical cognitive outcomes and quantitatively elucidates their relationship, providing robust evidence supporting the amyloid hypothesis and advancing the development of novel anti-amyloid therapeutics, such as aducanumab, lecanemab and donanemab. METHODS: Placebo-controlled randomized clinical trials reporting Aβ-related biomarkers and cognitive function clinical outcomes were retrieved from PubMed, EMBASE and Cochrane Library. Pearson correlation analysis was first used to screen indices, and then a model-based meta-analysis (MBMA) using non-linear mixed-effect modelling was established to predict cognitive function based on biomarkers while examining relevant factors affecting the relationship. RESULTS: Primary outcomes included changes in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) and the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-COG-11). The analysis included 57 articles representing 93 417 subjects, with a modelling subset of 18 246 patients providing paired biomarker-endpoint data for Alzheimer's disease or mild cognitive impairment. Results showed significant correlations between the standard uptake value ratio (SUVR) of β-amyloid plaques and CDR-SB, centiloid and CDR-SB, and SUVR and ADAS-COG-11. Three prediction models of cognitive function scales based on imaging index of β-amyloid plaques were established and found to be significantly impacted by factors such as baseline CDR-SB, treatment duration and the proportion of patients receiving basic treatment. CONCLUSIONS: This study clarified the correlation and established predictive models for CDR-SB and ADAS-COG-11 based on amyloid imaging. This research identifies potential biomarkers and model-derived benchmarks for future dose selection and decision-making in Alzheimer's drug development, potentially accelerating the development of new treatments.
DOI: 10.1002/bcp.70665
Institution: Shanghai University of Traditional Chinese Medicine
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7166534858