Modeling the Lifetime Effects of Lecanemab in Early Alzheimer’s Disease
Author(s)
Oliver Burn, MSc1, Kate Molloy, MSc1, Simon Rothwell, Ph.D.2, Kerigo Ndirangu, MPH3, David Trueman, MSc1, Janice Pan, MPH3.
1Source Health Economics, London, United Kingdom, 2Eisai Europe Ltd, Hatfield, United Kingdom, 3Eisai Inc., Nutley, NJ, USA.
1Source Health Economics, London, United Kingdom, 2Eisai Europe Ltd, Hatfield, United Kingdom, 3Eisai Inc., Nutley, NJ, USA.
OBJECTIVES: To assess the long-term effects of lecanemab plus standard of care (SoC) compared with SoC alone in a cohort of patients with early Alzheimer’s disease (AD; mild cognitive impairment [MCI] due to AD, or mild AD dementia) using different modelling approaches and data from Clarity AD.
METHODS: A Markov model was employed using health states based on disease severity, long-term institutionalization, and death, with disease severity defined using the Clinical Dementia Rating - Sum of Boxes (CDR-SB) classification for MCI due to AD, and Mild, Moderate, and Severe AD. State transitions during the first 18 months of treatment were estimated using either patient count data (Approach 1) or multistate survival analysis (Approach 2). Transition probabilities beyond 18 months for the lifetime of the cohort were informed by longitudinal natural history data for the SoC arm with a hazard ratio for time-to-worsening health state applied to estimate outcomes in the lecanemab arm. Scenario analyses are presented using data from the open-label extension of Clarity AD and applying a reduction in treatment effect at moderate disease.
RESULTS: Over a lifetime horizon, the model predicted a slower rate of disease progression for lecanemab compared with SoC. Time to mild AD was delayed by 1.28 years. Patients treated with lecanemab experienced a survival benefit of 1.18 years compared to patients treated with SoC alone. The model also predicted that compared to SoC, lecanemab increased the time in community care and reduced time spent in long-term institutional care. Results were similar when using Approach 1 and 2.
CONCLUSIONS: Patients treated with lecanemab experience delayed progression to Moderate and Severe AD, resulting in additional LYs and reduced time in institutional care.
METHODS: A Markov model was employed using health states based on disease severity, long-term institutionalization, and death, with disease severity defined using the Clinical Dementia Rating - Sum of Boxes (CDR-SB) classification for MCI due to AD, and Mild, Moderate, and Severe AD. State transitions during the first 18 months of treatment were estimated using either patient count data (Approach 1) or multistate survival analysis (Approach 2). Transition probabilities beyond 18 months for the lifetime of the cohort were informed by longitudinal natural history data for the SoC arm with a hazard ratio for time-to-worsening health state applied to estimate outcomes in the lecanemab arm. Scenario analyses are presented using data from the open-label extension of Clarity AD and applying a reduction in treatment effect at moderate disease.
RESULTS: Over a lifetime horizon, the model predicted a slower rate of disease progression for lecanemab compared with SoC. Time to mild AD was delayed by 1.28 years. Patients treated with lecanemab experienced a survival benefit of 1.18 years compared to patients treated with SoC alone. The model also predicted that compared to SoC, lecanemab increased the time in community care and reduced time spent in long-term institutional care. Results were similar when using Approach 1 and 2.
CONCLUSIONS: Patients treated with lecanemab experience delayed progression to Moderate and Severe AD, resulting in additional LYs and reduced time in institutional care.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
SA70
Topic
Clinical Outcomes, Methodological & Statistical Research, Study Approaches
Topic Subcategory
Decision Modeling & Simulation
Disease
Neurological Disorders