Predicting the Societal Value of Lecanemab in Early Alzheimer’s Disease in Japan: A Patient-Level Simulation
Bibliographic record
Abstract
INTRODUCTION: Alzheimer's disease (AD), a neurodegenerative disorder that progresses from mild cognitive impairment (MCI) to dementia, is responsible for significant burden on caregivers and healthcare systems. In this study, data from the large phase III CLARITY AD trial were used to estimate the societal value of lecanemab plus standard of care (SoC) versus SoC alone against a range of willingness-to-pay (WTP) thresholds from a healthcare and societal perspective in Japan. METHODS: A disease simulation model was used to evaluate the impact of lecanemab on disease progression in early AD based on data from the phase III CLARITY AD trial and published literature. The model used a series of predictive risk equations based on clinical and biomarker data from the Alzheimer's Disease Neuroimaging Initiative and Assessment of Health Economics in Alzheimer's Disease II study. The model predicted key patient outcomes, including life years (LYs), quality-adjusted life years (QALYs), and total healthcare and informal costs of patients and caregivers. RESULTS: Over a lifetime horizon, patients treated with lecanemab plus SoC gained an additional 0.73 LYs compared with SoC alone (8.50 years vs. 7.77 years). Lecanemab, with an average treatment duration of 3.68 years, was found to be associated with a 0.91 increase in patient QALYs and a total increase of 0.96 when accounting for caregiver utility. The estimated value of lecanemab varied according to the WTP thresholds (JPY 5-15 million per QALY gained) and the perspective employed. From the narrow healthcare payer's perspective, it ranged from JPY 1,331,305 to JPY 3,939,399. From the broader healthcare payer's perspective, it ranged from JPY 1,636,827 to JPY 4,249,702, while from the societal perspective, it ranged from JPY 1,938,740 to JPY 4,675,818. CONCLUSION: The use of lecanemab plus SoC would improve health and humanistic outcomes with reduced economic burden for patients and caregivers with early AD in Japan.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".