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Record W3045856304 · doi:10.1002/alz.038049

Gantenerumab in‐depth outcomes

2020· article· en· W3045856304 on OpenAlexaff
Stephen Salloway, Randall J. Bateman, Andrew J. Aschenbrenner, Tammie L.S. Benzinger, David B. Clifford, Kelley A. Coalier, Carlos Cruchaga, Anne M. Fagan, Martin R. Farlow, Alison Goate, Brian A. Gordon, Jason Hassenstab, Clifford R. Jack, Robert A. Koeppe, Eric McDade, Susan Mills, John C. Morris, Anna Santacruz, Peter J. Snyder, Guoqiao Wang, Chengjie Xiong, B. Joy Snider, Catherine J. Mummery, Ghulam M. Surti, Didier Hannequin, David Wallon, Sarah Berman, James J. Lah, Ivonne Z. Jiménez‐Velázquez, Erik D. Roberson, Christopher H. van Dyck, Lawrence S. Honig, Raquel Sánchez‐Valle, William S. Brooks, Serge Gauthier, Colin L. Masters, Doug Galasko, Jared R. Brosch, Ging‐Yuek Robin Hsiung, Suman Jayadev, Maïté Formaglio, Mario Masellis, Roger Clarnette, Jérémie Pariente, Bruno Dubois, Florence Pasquier, Monika Baudler, Paul Delmar, Rachelle S. Doody, Paulo Fontoura, Geoffrey A. Kerchner

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of TorontoVancouver Coastal Health Research InstituteMcGill University Health Centre
Fundersnot available
KeywordsMedicineClinical endpointBiomarkerInternal medicineAsymptomaticPlaceboSurrogate endpointOncologyClinical trialGastroenterologyPathology

Abstract

fetched live from OpenAlex

Abstract Background Gantenerumab is a humanized anti‐amyloid‐beta monoclonal antibody in clinical development for the treatment of several stages of Alzheimer disease (AD). Gantenerumab was evaluated in a phase 2/3 clinical trial program designed to evaluate its efficacy in autosomal dominant AD based on a combination of clinical and biomarker evidence. Method The study enrolled both mutation carriers (n=69 with 3:1 randomization of treatment (n=52) vs placebo (n=17)) and non‐carriers (n=28, all on placebo) from 15 years before to 10 years after the expected age of onset inclusive. Patients were both asymptomatic (CDR 0 and MMSE >25) and symptomatic (CDR 0.5‐1 and MMSE >16). There were 41 asymptomatic and 28 symptomatic mutation carriers. The initial dose of gantenerumab was 225 mg monthly administered subcutaneously. The dose was titrated to 1200 mg/month following a protocol amendment based on the increased amyloid lowering seen at higher doses in the gantenerumab program in symptomatic AD. The treatment duration was a minimum of 4 years (range 48‐80 months). The primary outcome was change from baseline in the DIAN‐TU multivariate cognitive endpoint. Secondary clinical outcomes included the DIAN‐TU cognitive composite, Cogstate multivariate cognitive endpoint, CDR SB, and time to CDR progression of >0.5 points. Change from baseline in amyloid PET was the primary biomarker outcome. Other biomarker outcomes included MRI, tau PET, CSF amyloid, tau and phosphotau, and CSF and plasma neurofilament light (NfL). Safety outcomes including ARIA were compared between drug and placebo groups. Result We will report change from baseline on the DIAN‐TU multivariate cognitive endpoint, DIAN‐TU cognitive composite, CDR‐SB and other secondary efficacy endpoints. We expect significant lowering on amyloid PET with PIB and florbetapir based on the results from recent anti‐amyloid antibodies, including Gantenerumab, in sporadic AD. We will also present the results of change in other key imaging and fluid biomarkers. The frequency, duration, and severity of ARIA will be reported and compared with studies in sporadic AD. Conclusion This clinical trial was designed to inform future for ADAD and will provide new insights on the role of amyloid reduction in both pre‐symptomatic and clinical AD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.328
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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