Efficacy assessment of an active tau immunotherapy in Alzheimer's disease patients with amyloid and tau pathology : a post hoc analysis of the “ADAMANT” randomised, placebo-controlled, double-blind, multi-centre, phase 2 clinical trial
(2024) In EBioMedicine 99.- Abstract
Background: Tau pathology correlates with and predicts clinical decline in Alzheimer's disease. Approved tau-targeted therapies are not available. Methods: ADAMANT, a 24-month randomised, placebo-controlled, parallel-group, double-blinded, multicenter, Phase 2 clinical trial (EudraCT2015-000630-30, NCT02579252) enrolled 196 participants with Alzheimer's disease; 119 are included in this post-hoc subgroup analysis. AADvac1, active immunotherapy against pathological tau protein. A machine learning model predicted likely Amyloid+Tau+ participants from baseline MRI. Statistical methods: MMRM for change from baseline in cognition, function, and neurodegeneration; linear regression for associations between antibody response and endpoints.... (More)
Background: Tau pathology correlates with and predicts clinical decline in Alzheimer's disease. Approved tau-targeted therapies are not available. Methods: ADAMANT, a 24-month randomised, placebo-controlled, parallel-group, double-blinded, multicenter, Phase 2 clinical trial (EudraCT2015-000630-30, NCT02579252) enrolled 196 participants with Alzheimer's disease; 119 are included in this post-hoc subgroup analysis. AADvac1, active immunotherapy against pathological tau protein. A machine learning model predicted likely Amyloid+Tau+ participants from baseline MRI. Statistical methods: MMRM for change from baseline in cognition, function, and neurodegeneration; linear regression for associations between antibody response and endpoints. Results: The prediction model achieved PPV of 97.7% for amyloid, 96.2% for tau. 119 participants in the full analysis set (70 treatment and 49 placebo) were classified as A+T+. A trend for CDR-SB 104-week change (estimated marginal means [emm] = −0.99 points, 95% CI [−2.13, 0.13], p = 0.0825]) and ADCS-MCI-ADL (emm = 3.82 points, CI [−0.29, 7.92], p = 0.0679) in favour of the treatment group was seen. Reduction was seen in plasma NF-L (emm = −0.15 log pg/mL, CI [−0.27, −0.03], p = 0.0139). Higher antibody response to AADvac1 was related to slowing of decline on CDR-SB (rho = −0.10, CI [−0.21, 0.01], p = 0.0376) and ADL (rho = 0.15, CI [0.03, 0.27], p = 0.0201), and related to slower brain atrophy (rho = 0.18–0.35, p < 0.05 for temporal volume, whole cortex, and right and left hippocampus). Conclusions: In the subgroup of ML imputed or CSF identified A+T+, AADvac1 slowed AD-related decline in an antibody-dependent manner. Larger anti-tau trials are warranted. Funding: AXON Neuroscience SE.
(Less)
- author
- organization
- publishing date
- 2024-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Alzheimer's disease, Immunotherapy, Machine learning, Post-hoc analysis, Tau
- in
- EBioMedicine
- volume
- 99
- article number
- 104923
- publisher
- Elsevier
- external identifiers
-
- pmid:38101301
- scopus:85179999611
- ISSN
- 2352-3964
- DOI
- 10.1016/j.ebiom.2023.104923
- language
- English
- LU publication?
- yes
- id
- 5257028c-e168-443e-a6ea-21fde282e043
- date added to LUP
- 2024-01-31 11:43:14
- date last changed
- 2024-04-16 23:57:56
@article{5257028c-e168-443e-a6ea-21fde282e043,
abstract = {{<p>Background: Tau pathology correlates with and predicts clinical decline in Alzheimer's disease. Approved tau-targeted therapies are not available. Methods: ADAMANT, a 24-month randomised, placebo-controlled, parallel-group, double-blinded, multicenter, Phase 2 clinical trial (EudraCT2015-000630-30, NCT02579252) enrolled 196 participants with Alzheimer's disease; 119 are included in this post-hoc subgroup analysis. AADvac1, active immunotherapy against pathological tau protein. A machine learning model predicted likely Amyloid+Tau+ participants from baseline MRI. Statistical methods: MMRM for change from baseline in cognition, function, and neurodegeneration; linear regression for associations between antibody response and endpoints. Results: The prediction model achieved PPV of 97.7% for amyloid, 96.2% for tau. 119 participants in the full analysis set (70 treatment and 49 placebo) were classified as A+T+. A trend for CDR-SB 104-week change (estimated marginal means [emm] = −0.99 points, 95% CI [−2.13, 0.13], p = 0.0825]) and ADCS-MCI-ADL (emm = 3.82 points, CI [−0.29, 7.92], p = 0.0679) in favour of the treatment group was seen. Reduction was seen in plasma NF-L (emm = −0.15 log pg/mL, CI [−0.27, −0.03], p = 0.0139). Higher antibody response to AADvac1 was related to slowing of decline on CDR-SB (rho = −0.10, CI [−0.21, 0.01], p = 0.0376) and ADL (rho = 0.15, CI [0.03, 0.27], p = 0.0201), and related to slower brain atrophy (rho = 0.18–0.35, p < 0.05 for temporal volume, whole cortex, and right and left hippocampus). Conclusions: In the subgroup of ML imputed or CSF identified A+T+, AADvac1 slowed AD-related decline in an antibody-dependent manner. Larger anti-tau trials are warranted. Funding: AXON Neuroscience SE.</p>}},
author = {{Cullen, Nicholas C. and Novak, Petr and Tosun, Duygu and Kovacech, Branislav and Hanes, Jozef and Kontsekova, Eva and Fresser, Michal and Ropele, Stefan and Feldman, Howard H. and Schmidt, Reinhold and Winblad, Bengt and Zilka, Norbert}},
issn = {{2352-3964}},
keywords = {{Alzheimer's disease; Immunotherapy; Machine learning; Post-hoc analysis; Tau}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{EBioMedicine}},
title = {{Efficacy assessment of an active tau immunotherapy in Alzheimer's disease patients with amyloid and tau pathology : a post hoc analysis of the “ADAMANT” randomised, placebo-controlled, double-blind, multi-centre, phase 2 clinical trial}},
url = {{http://dx.doi.org/10.1016/j.ebiom.2023.104923}},
doi = {{10.1016/j.ebiom.2023.104923}},
volume = {{99}},
year = {{2024}},
}