Amyloid beta (Aβ) targeting immunotherapies have evolved as promising treatment options for patients with early symptomatic Alzheimer's disease (AD). Understanding how eligibilty criteria impact on the number of patients potentially qualifying for treatment is of high relevance for designing diagnostic workflows in clinical practice and for estimating required ressources and costs.

We aimed at estimating the number of potentially eligible patients for treatment with the Aβ targeting antibodies aducanumab, lecanemab and donanemab in a specialized center real-world sample by the applying the phase 3 clinical trial and the appropriate use recommendations (AUR) inclusion and exclusion criteria to the data set. The post-mortem report was used for defining amyloid positivity and the presence of AD pathology in this study.

Retrospective, descriptive study.

The multicenter National Alzheimer‘s Coordinating Center-Uniform Data Set (NACC-UDS) and Neuropathology Data Set (NACC-NP).

We included all 3,343 participants of the NACC dataset with available post-mortem pathology reports.

887 participants were potential candidates for anti-Aβ immunotherapy as they presented with amnestic mild cognitive impairment or mild dementia and the clinical diagnosis of AD (amnestic AD syndrome). Applying the criterion of amyloid positivity (post mortem report) and the clinical trial inclusion and exclusion criteria to this sample resulted in 83 (9 %), 275 (31 %), and 172 (19 %) participants eligible for treatment with aducanumab, lecanemab, and donanemab, respectively. Applying the criteria of the AUR resulted in 242 (27 %) and 266 (30 %) participants eligible for treatment with aducanumab or lecanemab, respectively. The eligible participant groups for each antibody showed partial, but not full overlap. Co-pathologies were common.

The number of eligible participants varies between the different antibodies and the selected groups only partly overlap, indicating partly different groups of eligible participants for each antibody. Since not all inclusion and exclusion criteria can be extracted from the NACC-UDS dataset, the real number of eligible patients will be smaller.