Predicted natural progression as an Alzheimer's prognostic covariate improves the precision of lecanemab efficacy assessments and clinical trial efficiency
Baseline prediction of future progression can serve as an APC for treatment effect assessments. These predictions can be derived from progression models developed using external controls. APC accounts for heterogeneity in progression among trial participants, improving treatment effect estimates. Enhanced accuracy and precision were observed across lecanemab phase II and phase III trials for various endpoints. This approach results in substantial increase in statistical power and reduced sample size for future AD trials.
Authors
- Lü Tian (ORCID: https://orcid.org/0000-0002-5893-0169)
- Shobha Dhadda (ORCID: https://orcid.org/0000-0002-7290-7168)
- Viswanath Devanarayan (ORCID: https://orcid.org/0000-0003-2059-9252)
- Yuanqing Ye (ORCID: https://orcid.org/0000-0001-5708-8961)
- Liang Zhu (ORCID: https://orcid.org/0000-0002-1970-6914)
- Michael C. Irizarry (ORCID: https://orcid.org/0000-0002-0246-2511)
- Lynn D. Kramer
Institutions
- University of Illinois Chicago (US)
- Eisai (United States) (US)
- Stanford University (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1002/alz.70045
- Citations
- 2
- Primary Topic
- Health Systems, Economic Evaluations, Quality of Life
- Type
- article
- Field-Weighted Citation Impact
- 6.26
Funders
- Eisai