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Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis

Sa Ren Orcid Logo, Janharpreet Singh, Sandro Gsteiger, Christopher Cogley, Ben Reed, Keith R Abrams, Dalia Dawoud, Rhiannon Owen Orcid Logo, Paul Tappenden, Terrence J Quinn, Sylwia Bujkiewicz Orcid Logo

Journal of Comparative Effectiveness Research, Volume: 15, Issue: 1

Swansea University Author: Rhiannon Owen Orcid Logo

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DOI (Published version): 10.57264/cer-2025-0095

Abstract

Aim: The use of amyloid-beta (Aβ) clearance to support regulatory approvals of drugs in Alzheimer’s disease (AD) remains controversial. We evaluate Aβ as a potential trial-level surrogate endpoint for clinical function in AD. Materials & methods: Data on the effectiveness of anti-Aβ monoclonal a...

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Published in: Journal of Comparative Effectiveness Research
ISSN: 2042-6305 2042-6313
Published: Becaris Publishing Limited 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa71455
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Sharing information across treatments considerably reduced the uncertainty, resulting in moderate surrogate relationships for aducanumab and lecanemab. No meaningful association was detected for other clinical outcomes, including Mini Mental State Examination and Alzheimer&#x2019;s Disease Assessment Scale-Cognitive Subscale. Conclusion: Although our results from the analysis of data across all MABs suggested that A&#x3B2; was a potential surrogate endpoint for CDR-SOB, individually the surrogacy patterns varied across treatments and showed no evidence of association. 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spelling 2026-03-09T15:21:07.3038524 v2 71455 2026-02-17 Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis 0d30aa00eef6528f763a1e1589f703ec 0000-0001-5977-376X Rhiannon Owen Rhiannon Owen true false 2026-02-17 MEDS Aim: The use of amyloid-beta (Aβ) clearance to support regulatory approvals of drugs in Alzheimer’s disease (AD) remains controversial. We evaluate Aβ as a potential trial-level surrogate endpoint for clinical function in AD. Materials & methods: Data on the effectiveness of anti-Aβ monoclonal antibodies (MABs) on Aβ and multiple clinical outcomes were identified from randomized controlled trials through a literature review. A Bayesian bivariate meta-analysis was used to evaluate Aβ as a surrogate endpoint for clinical function across all MABs and for each individual anti-Aβ MAB. The analysis for individual therapies was conducted in subgroups of treatments and by applying Bayesian hierarchical models to borrow information across treatments. Results: We identified 23 randomized controlled trials with 39 treatment contrasts for seven MABs. The surrogate relationship between treatment effects on Aβ and Clinical Dementia Rating-Sum of Boxes (CDR-SOB) across all MABs was strong: with a meaningful slope of 1.41 (0.60, 2.21) and small variance of 0.02 (0.00, 0.05). For individual treatments, the surrogate relationships were suboptimal, displaying large uncertainty. Sharing information across treatments considerably reduced the uncertainty, resulting in moderate surrogate relationships for aducanumab and lecanemab. No meaningful association was detected for other clinical outcomes, including Mini Mental State Examination and Alzheimer’s Disease Assessment Scale-Cognitive Subscale. Conclusion: Although our results from the analysis of data across all MABs suggested that Aβ was a potential surrogate endpoint for CDR-SOB, individually the surrogacy patterns varied across treatments and showed no evidence of association. Bayesian information-sharing revealed moderate surrogate relationship only for aducanumab and lecanemab. Journal Article Journal of Comparative Effectiveness Research 15 1 Becaris Publishing Limited 2042-6305 2042-6313 Alzheimer’s disease; amyloid-beta; clinical outcomes; meta-analysis; surrogate endpoint 2 12 2025 2025-12-02 10.57264/cer-2025-0095 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University 2026-03-09T15:21:07.3038524 2026-02-17T12:49:38.4016497 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Sa Ren 0000-0001-9040-249x 1 Janharpreet Singh 2 Sandro Gsteiger 3 Christopher Cogley 4 Ben Reed 5 Keith R Abrams 6 Dalia Dawoud 7 Rhiannon Owen 0000-0001-5977-376X 8 Paul Tappenden 9 Terrence J Quinn 10 Sylwia Bujkiewicz 0000-0002-3003-9403 11 71455__36377__a9c90a3fcb6f4cc08b8dac10a572b456.pdf 71455.VoR.pdf 2026-03-09T15:17:56.5701509 Output 1409115 application/pdf Version of Record true © 2025 The authors. This work is licensed under the Creative Commons Attribution 4.0 License. true eng https://creativecommons.org/licenses/by/4.0/
title Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis
spellingShingle Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis
Rhiannon Owen
title_short Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis
title_full Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis
title_fullStr Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis
title_full_unstemmed Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis
title_sort Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer’s disease: a Bayesian meta-analysis
author_id_str_mv 0d30aa00eef6528f763a1e1589f703ec
author_id_fullname_str_mv 0d30aa00eef6528f763a1e1589f703ec_***_Rhiannon Owen
author Rhiannon Owen
author2 Sa Ren
Janharpreet Singh
Sandro Gsteiger
Christopher Cogley
Ben Reed
Keith R Abrams
Dalia Dawoud
Rhiannon Owen
Paul Tappenden
Terrence J Quinn
Sylwia Bujkiewicz
format Journal article
container_title Journal of Comparative Effectiveness Research
container_volume 15
container_issue 1
publishDate 2025
institution Swansea University
issn 2042-6305
2042-6313
doi_str_mv 10.57264/cer-2025-0095
publisher Becaris Publishing Limited
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science
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description Aim: The use of amyloid-beta (Aβ) clearance to support regulatory approvals of drugs in Alzheimer’s disease (AD) remains controversial. We evaluate Aβ as a potential trial-level surrogate endpoint for clinical function in AD. Materials & methods: Data on the effectiveness of anti-Aβ monoclonal antibodies (MABs) on Aβ and multiple clinical outcomes were identified from randomized controlled trials through a literature review. A Bayesian bivariate meta-analysis was used to evaluate Aβ as a surrogate endpoint for clinical function across all MABs and for each individual anti-Aβ MAB. The analysis for individual therapies was conducted in subgroups of treatments and by applying Bayesian hierarchical models to borrow information across treatments. Results: We identified 23 randomized controlled trials with 39 treatment contrasts for seven MABs. The surrogate relationship between treatment effects on Aβ and Clinical Dementia Rating-Sum of Boxes (CDR-SOB) across all MABs was strong: with a meaningful slope of 1.41 (0.60, 2.21) and small variance of 0.02 (0.00, 0.05). For individual treatments, the surrogate relationships were suboptimal, displaying large uncertainty. Sharing information across treatments considerably reduced the uncertainty, resulting in moderate surrogate relationships for aducanumab and lecanemab. No meaningful association was detected for other clinical outcomes, including Mini Mental State Examination and Alzheimer’s Disease Assessment Scale-Cognitive Subscale. Conclusion: Although our results from the analysis of data across all MABs suggested that Aβ was a potential surrogate endpoint for CDR-SOB, individually the surrogacy patterns varied across treatments and showed no evidence of association. Bayesian information-sharing revealed moderate surrogate relationship only for aducanumab and lecanemab.
published_date 2025-12-02T05:34:49Z
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