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Record W4409988625 · doi:10.1186/s13195-025-01745-3

Prognostic value of plasma biomarkers for informing clinical trial design in mild-to-moderate Alzheimer’s disease

2025· article· en· W4409988625 on OpenAlexaff
Yuqi Qiu, Diane M. Jacobs, Karen Messer, David P. Salmon, Cheryl L. Wellington, Sophie Stukas, Carolyn Revta, James Brewer, Gabriel C. Léger, Brianna Askew, Lia Donahue, Stephen Kaplita, Vladimir Coric, Irfan Qureshi, Howard Feldman

Bibliographic record

VenueAlzheimer s Research & Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersNational Institute on AgingUniversity of California, San DiegoNational Institutes of HealthBiohaven Pharmaceuticals
KeywordsGeriatric psychiatryNeurologyMedicineDiseaseClinical trialInternal medicineValue (mathematics)Alzheimer's diseaseOncologyIntensive care medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Emerging evidence supports the diagnostic and prognostic utility of plasma biomarkers in Alzheimer’s disease (AD), particularly in early disease stages. We sought to extend these findings by evaluating the prognostic value of plasma biomarkers in a clinical trial of mild-to-moderate AD. Methods Post-hoc analyses investigated whether baseline concentrations of plasma biomarkers (Aβ42/Aβ40, T-tau, P-tau181, NfL, and GFAP) predicted change in ADAS-Cog11, CDR-SB, and volumetric MRI among participants in T2 Protect AD, a negative 48-week, phase-2, placebo-controlled trial of troriluzole in mild-to-moderate AD. All trial participants met diagnostic criteria for probable AD. Baseline concentrations of, and 48-week changes in, plasma biomarkers were assessed for association with 48-week change in outcomes using linear regression. Combinations of baseline biomarkers that best predicted change on the ADAS-Cog11 and CDR-SB were identified using least absolute shrinkage and selection operator (LASSO) regression. Biomarker-informed sample size calculations were modeled. Results Of 350 trial participants, 319 had all requisite biomarker and clinical outcome data for inclusion in these analyses (mean age 71.5, SD = 8.03; 58.6% female). Higher plasma NfL at baseline predicted worsening scores on the ADAS-Cog11 (effect size (ES) = 1.42, 95%CI = [0.43, 2.41], p = 0.026) and CDR-SB (ES = 0.42, 95%CI = [0.10, 0.73], p = 0.048). LASSO regression revealed that worsening on the ADAS-Cog11 was best predicted by the combination of baseline plasma NfL, T-tau, and Aβ42/40 ratio, whereas baseline NfL alone best predicted worsening on CDR-SB. Higher baseline NfL predicted increasing ventricular volume (ES = 1.30cm3, 95%CI = [0.43, 2.17], p = 0.018) and decreasing mid-temporal cortical volume (ES = -0.47, 95%CI = [-0.74, -0.20], p = 0.003). Increasing NfL over the 48-week trial was associated with worsening on CDR-SB but not ADAS-Cog11. Modeling of biomarker-informed power calculations revealed that including high NfL as a trial entry criterion could substantially reduce requisite trial sample size. Conclusions Elevated baseline plasma NfL predicted more rapid clinical decline and MRI volume loss. Furthermore, increasing plasma NfL concentration over time was associated with worsening on the CDR-SB. Plasma NfL is an easily accessible biomarker that may enhance the design of clinical trials in mild-to-moderate AD. Trial registration The T2 Protect AD trial was registered as NCT03605667 on clinicaltrials.gov on 2018-07-27.

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)0.202
metaresearch head score (Gemma)0.339
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.985

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2020.339
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.280
GPT teacher head0.507
Teacher spread0.226 · 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.

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
Published2025
Admission routes1
Has abstractyes

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