Real World Lecanemab Outcome Data at 6 months in an Academic Healthcare System
Bibliographic record
Abstract
BACKGROUND: Monoclonal antibodies targeting amyloid-beta plaques have emerged as a new disease-modifying drug class that target and remove cerebral amyloid in early-stage Alzheimer's disease. Whereas the CLARITY-AD trial demonstrated significant cognitive and functional slowing as measured by the CDR-SB at 18 months, limited data relating to real-world cognitive and behavioral outcomes exists. Our objective was to describe 6-month clinical outcomes in a community sample of early-stage AD subjects receiving lecanemab. METHOD: We reviewed retrospective observational data from 79 early stage-AD patients receiving mABs over 6 months at an academic community hospital-based clinic in Seattle, WA. All patients were administered the Montreal Cognitive Assessment (MOCA), functional assessment questionnaire (FAQ), patient health questionnaire (PHQ-9), and generalized anxiety disorder (GAD-7) as part of usual clinical protocol. Cognitive screening tests performed up to one year prior to lecanemab served as a baseline assessment. Demographics and incidence of amyloid related imaging abnormalities-edema/microhemorrhage (ARIA-E) and (ARIA-H) were calculated. RESULT: Average patient age was 71.6 (59.5% female) with 65.8% of patients carrying an MCI diagnosis. Racial demographics showed mostly White patients (94.9%) with limited representation of diverse populations (2.5% unknown; 1.3% Asian; 1.3% Native American; 1.3% Latino ethnicity). The majority of treated patients were ApoE4 carriers (70.8%) with 12.7% of patients being homozygous for ApoE4. Mean MOCA score was 21.1±1.4 at baseline, 19.9±4.2 at 6 months; FAQ score 6.4±2.8 at baseline, 8.1±2.8 at 6 months; PHQ9 score 2.1±0.7 at baseline, 1.5±4.2 at 6 months; GAD-7 score 2.0±2.1 at baseline, 0.9±1.6 at 6 months. Fifteen patients (19%) developed either ARIA-E or ARIA-H. Of those 15 patients, 8 had isolated ARIA-H (53.3%), 3 had isolated ARIA-E (20%), and 4 (27%) patients showed mixed findings of both. CONCLUSION: In the interim analysis, a trend toward improved depression and anxiety scores over 6 months was observed with modest declines in cognition and performance. A full data set analysis will provide comprehensive data relating to clinical outcomes with mAb treatments. Further analysis of longitudinal data is necessary to confirm whether anti-amyloid monoclonal antibody clinical trial efficacy translates into real world clinical effectiveness at 12 and 18 months.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".