Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging
Open accessAbstract
BACKGROUND AND OBJECTIVES: Treatment options for Alzheimer disease (AD) are limited and have focused mainly on symptomatic therapy and improving quality of life. Recently, lecanemab, an anti-β-amyloid monoclonal antibody (mAb), received accelerated approval by the US Food and Drug Administration for treatment in the early stages of biomarker-confirmed symptomatic AD. An additional anti-β-amyloid mAb, aducanumab, was approved in 2021, and more will potentially become available in the near future. Research on the applicability and generalizability of the anti-β-amyloid mAb eligibility criteria on adults with biomarkers available in the general population has been lacking. The study's primary aim was to apply the clinical trial eligibility criteria for lecanemab treatment to participants with early AD of the population-based Mayo Clinic Study of Aging (MCSA) and assess the generalizability of anti-amyloid treatment. The secondary aim of this study was to apply the clinical trial eligibility criteria for aducanumab treatment in MCSA participants. METHODS: This cross-sectional study aimed to apply the clinical trial eligibility criteria for lecanemab and aducanumab treatment to participants with early AD of the population-based MCSA and assess the generalizability of anti-amyloid treatment. RESULTS: Two hundred thirty-seven MCSA participants (mean age [SD] 80.9 [6.3] years, 54.9% male, and 97.5% White) with mild cognitive impairment (MCI) or mild dementia and increased brain amyloid burden by PiB PET comprised the study sample. Lecanemab trial's inclusion criteria reduced the study sample to 112 (47.3% of 237) participants. The trial's exclusion criteria further narrowed the number of potentially eligible participants to 19 (overall 8% of 237). Modifying the eligibility criteria to include all participants with MCI (instead of applying additional cognitive criteria) resulted in 17.4% of participants with MCI being eligible for lecanemab treatment. One hundred four participants (43.9% of 237) fulfilled the aducanumab clinical trial's inclusion criteria. The aducanumab trial's exclusion criteria further reduced the number of available participants, narrowing those eligible to 12 (5.1% of 237). Common exclusions were related to other chronic conditions and neuroimaging findings. DISCUSSION: Findings estimate the limited eligibility in typical older adults with cognitive impairment for anti-β-amyloid mAbs.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Only 8% of a sample of adults with dementia or MCI and a positive brain amyloid PET scan would meet the lecanemab clinical trial inclusion and exclusion criteria.
“only 8% of the sample would meet the lecanemab clinical trial inclusion and exclusion criteria. 968”
From 2024 Alzheimer's disease facts and figures (2024) · cites this paper as [968]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369 · see citing works
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915 · see citing works
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657 · see citing works
Self-citationThe Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882 · see citing works
Mild cognitive impairment as a diagnostic entity
Petersen, R. C. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01388.x · Cited by 7,864 · see citing works
Self-citationLecanemab in early Alzheimer's disease
van Dyck, C. H., Swanson, C. J., Aisen, P., Bateman, R. J., Chen, C., Gee, M., Kanekiyo, M., Li, D., Reyderman, L., Cohen, S., et al. (2023) · New England Journal of Medicine · doi:10.1056/nejmoa2212948 · Cited by 5,678 · see citing works
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound‐B
Klunk, W. E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D. P., Bergström, M., Savitcheva, I., Huang, G., Estrada, S., et al. (2004) · Annals of Neurology · doi:10.1002/ana.20009 · Cited by 4,496 · see citing works
Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI.
Hixson, J., & Vernier, D. (1990) · Journal of Lipid Research · doi:10.1016/s0022-2275(20)43176-1 · Cited by 2,933 · see citing works
External validity of randomised controlled trials: “To whom do the results of this trial apply?”
Rothwell, P. M. (2005) · The Lancet · doi:10.1016/s0140-6736(04)17670-8 · Cited by 2,544 · see citing works
2022 Alzheimer's disease facts and figures
Anonymous (2022) · Alzheimer s & Dementia · doi:10.1002/alz.12638 · Cited by 2,384 · see citing works
Cerebral microbleeds: a guide to detection and interpretation
Greenberg, S. M., Vernooij, M. W., Cordonnier, C., Viswanathan, A., Al-Shahi Salman, R., Warach, S., Launer, L. J., Van Buchem, M. A., & Breteler, M. M. (2009) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70013-4 · Cited by 1,798 · see citing works
Two Randomized Phase 3 Studies of Aducanumab in Early Alzheimer's Disease
Budd Haeberlein, S., Aisen, P. S., Barkhof, F., Chalkias, S., Chen, T., Cohen, S., Dent, G., Hansson, O., Harrison, K., von Hehn, C., et al. (2022) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2022.30 · Cited by 1,367 · see citing works
The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET
Klunk, W. E., Koeppe, R. A., Price, J. C., Benzinger, T. L., Devous, M. D., Jagust, W. J., Johnson, K. A., Mathis, C. A., Minhas, D., Pontecorvo, M. J., et al. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.07.003 · Cited by 1,348 · see citing works
Lecanemab: Appropriate Use Recommendations
Cummings, J., Apostolova, L., Rabinovici, G. D., Atri, A., Aisen, P., Greenberg, S., Hendrix, S., Selkoe, D., Weiner, M., Petersen, R. C., et al. (2023) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2023.30 · Cited by 961 · see citing works
Self-citationDefining imaging biomarker cut points for brain aging and Alzheimer's disease
Jack, C. R., Wiste, H. J., Weigand, S. D., Therneau, T. M., Lowe, V. J., Knopman, D. S., Gunter, J. L., Senjem, M. L., Jones, D. T., Kantarci, K., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.08.005 · Cited by 931 · see citing works
Self-citationRoberts, R. O., Geda, Y. E., Knopman, D. S., Cha, R. H., Pankratz, V. S., Boeve, B. F., Ivnik, R. J., Tangalos, E. G., Petersen, R. C., & Rocca, W. A. (2008) · Neuroepidemiology · doi:10.1159/000115751 · Cited by 796 · see citing works
Self-citationAlzheimer’s disease drug development pipeline: 2022
Cummings, J., Lee, G., Nahed, P., Kambar, M. E. Z. N., Zhong, K., Fonseca, J., & Taghva, K. (2022) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12295 · Cited by 665 · see citing works
Sauver, J. L. S., Grossardt, B. R., Leibson, C. L., Yawn, B. P., Melton, L. J., & Rocca, W. A. (2012) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2011.11.009 · Cited by 652 · see citing works
Trajectories of brain aging in middle-aged and older adults: Regional and individual differences
Raz, N., Ghisletta, P., Rodrigue, K. M., Kennedy, K. M., & Lindenberger, U. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.020 · Cited by 626 · see citing works
Longitudinal tau PET in ageing and Alzheimer’s disease
Jack, C. R., Wiste, H. J., Schwarz, C. G., Lowe, V. J., Senjem, M. L., Vemuri, P., Weigand, S. D., Therneau, T. M., Knopman, D. S., Gunter, J. L., et al. (2018) · Brain · doi:10.1093/brain/awy059 · Cited by 452 · see citing works
Self-citationThe Short Test of Mental Status
Kokmen, E. (1991) · Archives of Neurology · doi:10.1001/archneur.1991.00530190071018 · Cited by 338 · see citing works
Jack, C. R., Wiste, H. J., Therneau, T. M., Weigand, S. D., Knopman, D. S., Mielke, M. M., Lowe, V. J., Vemuri, P., Machulda, M. M., Schwarz, C. G., et al. (2019) · JAMA · doi:10.1001/jama.2019.7437 · Cited by 324 · see citing works
Self-citationAducanumab: Appropriate Use Recommendations
Cummings, J., Aisen, P., Apostolova, L. G., Atri, A., Salloway, S., & Weiner, M. (2021) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2021.41 · Cited by 316 · see citing works
Tan, Y. Y., Papež, V., Chang, W. H., Mueller, S. H., Denaxas, S., & Lai, A. G. (2022) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(22)00186-6 · Cited by 284 · see citing works
Tang‐Wai, D. F., Knopman, D. S., Geda, Y. E., Edland, S. D., Smith, G. E., Ivnik, R. J., Tangalos, E. G., Boeve, B. F., & Petersen, R. C. (2003) · Archives of Neurology · doi:10.1001/archneur.60.12.1777 · Cited by 201 · see citing works
Self-citationWilkins, C. H., Windon, C., Dilworth‐Anderson, P., Romanoff, J., Gatsonis, C. G., Hanna, L., Apgar, C., Gareen, I. F., Hill, C. V., Hillner, B. E., et al. (2022) · JAMA Neurology · doi:10.1001/jamaneurol.2022.3157 · Cited by 144 · see citing works
Hlávka, J. P., Mattke, S., & Liu, J. (2018) · RAND Corporation eBooks · doi:10.7249/rr2503 · Cited by 134 · see citing works
du Vaure, C. B., Dechartres, A., Battin, C., Ravaud, P., & Boutron, I. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-012265 · Cited by 122 · see citing works
Deters, K., Napolioni, V., Sperling, R. A., Greicius, M. D., Mayeux, R. P., Hohman, T. J., & Mormino, E. C. (2021) · Neurology · doi:10.1212/wnl.0000000000011599 · Cited by 115 · see citing works
Liu, J., Hlavka, J., Hillestad, R., & Mattke, S. (2017) · doi:10.7249/rr2272 · Cited by 98 · see citing works
Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition
Raghavan, S., Reid, R. I., Przybelski, S. A., Lesnick, T. G., Graff-Radford, J., Schwarz, C. G., Knopman, D. S., Mielke, M. M., Machulda, M. M., Petersen, R. C., et al. (2021) · Brain Communications · doi:10.1093/braincomms/fcab106 · Cited by 79 · see citing works
Self-citationGraff‐Radford, J., Botha, H., Rabinstein, A. A., Gunter, J. L., Przybelski, S. A., Lesnick, T. G., Huston, J., Flemming, K. D., Preboske, G. M., Senjem, M. L., et al. (2018) · Neurology · doi:10.1212/wnl.0000000000006780 · Cited by 78 · see citing works
Self-citationStites, S. D., Midgett, S., Mechanic-Hamilton, D. J., Zuelsdorff, M. L., Glover, C. M., Márquez, D. X., Balls‐Berry, J. E., Streitz, M. L., Babulal, G. M., Trani, J., et al. (2021) · The Gerontologist · doi:10.1093/geront/gnab182 · Cited by 69 · see citing works
Cardiometabolic Health and Longitudinal Progression of White Matter Hyperintensity
Scharf, E. L., Graff‐Radford, J., Przybelski, S. A., Lesnick, T. G., Mielke, M. M., Knopman, D. S., Preboske, G. M., Schwarz, C. G., Senjem, M. L., Gunter, J. L., et al. (2019) · Stroke · doi:10.1161/strokeaha.119.025822 · Cited by 67 · see citing works
Self-citationAnderson, T. S., Ayanian, J. Z., Souza, J., & Landon, B. E. (2021) · JAMA · doi:10.1001/jama.2021.15286 · Cited by 66 · see citing works
Raman, R., Aisen, P., Carillo, M. C., Detke, M., Grill, J. D., Okonkwo, O. C., Rivera-Mindt, M., Sabbagh, M., Vellas, B., Weiner, M., et al. (2022) · The Journal of Prevention of Alzheimer's Disease · doi:10.14283/jpad.2022.50 · Cited by 52 · see citing works
Lecanemab trial in AD brings hope but requires greater clarity
Thambisetty, M., & Howard, R. J. (2023) · Nature Reviews Neurology · doi:10.1038/s41582-022-00768-w · Cited by 51 · see citing works
“Real world” eligibility for aducanumab
Canevelli, M., Rossi, P. D., Astrone, P., Consorti, E., Vanacore, N., & Cesari, M. (2021) · Journal of the American Geriatrics Society · doi:10.1111/jgs.17390 · Cited by 36 · see citing works
“Real‐world” eligibility for aducanumab depends on clinical setting and patients' journey
Padovani, A., Caratozzolo, S., Rozzini, L., Pilotto, A., Benussi, A., & Tedeschi, G. (2021) · Journal of the American Geriatrics Society · doi:10.1111/jgs.17530 · Cited by 31 · see citing works
Togher, Z., Dolphin, H., Russell, C., Ryan, M., Kennelly, S., & O’Dowd, S. (2022) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.5789 · Cited by 22 · see citing works
Weighting and standardization of frequencies to determine prevalence of AD imaging biomarkers
Roberts, R. O., Knopman, D. S., Syrjanen, J. A., Aakre, J. A., Vassilaki, M. E., Kremers, W. K., Mielke, M. M., Machulda, M. M., Graff‐Radford, J., Geda, Y. E., et al. (2017) · Neurology · doi:10.1212/wnl.0000000000004652 · Cited by 15 · see citing works
Self-citationOf education and public policy: Aducanumab
Lundebjerg, N. E., Hollmann, P. A., & Supiano, M. A. (2021) · Journal of the American Geriatrics Society · doi:10.1111/jgs.17523 · Cited by 8 · see citing works
Population-Based Prevalence of Infarctions on 3D Fluid-Attenuated Inversion Recovery (FLAIR) Imaging
Cogswell, P. M., Aakre, J. A., Castillo, A. M., Knopman, D. S., Kantarci, K., Rabinstein, A. A., Petersen, R. C., Jack, C. R., Mielke, M. M., Vemuri, P., et al. (2022) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2022.106583 · Cited by 8 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission
Livingston, G., Huntley, J., Liu, K. Y., Costafreda, S. G., Selbæk, G., Alladi, S., Ames, D., Banerjee, S., Burns, A., Brayne, C., et al. (2024) · The Lancet · doi:10.1016/s0140-6736(24)01296-0 · Cited by 3,860 · see citing works
2024 Alzheimer's disease facts and figures
(2024) · Alzheimer's & Dementia · doi:10.1002/alz.13809 · Cited by 2,536 · see citing works
- Authors
- Pittock, R. R., Aakre, J. A., Castillo, A. M., Ramanan, V. K., Kremers, W. K., Jack, C. R., Vemuri, P., Lowe, V. J., Knopman, D. S., Petersen, R. C., Graff-Radford, J., & Vassilaki, M.
- Affiliations
- Mayo Clinic (US)
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN.
- Corresponding author
- Vassilaki, Maria
- ORCID
- Venue
- Neurology
- Published
- 2023-11-07
- Volume
- 101
- Issue
- 19
- Pages
- e1837-e1849
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- PMC
- PMC10663008
- OpenAlex
- W4385854855
- Cited by
- 151
- References
- 43
- Citations by year
- 2026: 40 · 2025: 44 · 2024: 59 · 2023: 8
- FWCI
- 26.68
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Neurology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Mayo Clinic (AG 058738, P30 AG062677, U01 AG006786)
- Abbott Laboratories
- Amgen
- Mayo Foundation for Medical Education and Research
- GHR Foundation
- University of Oxford
- National Institutes of Health (AG062677, AG011378)
- National Institute on Aging (R21AG058738, AG041851, AG011378, U01AG006786, AG-006786, 058738, AG058738, R33AG058738, R01AG041851, R37AG011378, P30AG062677)
- National Cancer Institute
- National Institute of Neurological Disorders and Stroke (R01NS097495)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, anti-amyloid monoclonal antibodies, lecanemab, aducanumab, treatment eligibility criteria, inclusion and exclusion criteria, mild cognitive impairment, mild dementia, amyloid PET, PiB PET, Mayo Clinic Study of Aging, generalizability of trial results, early Alzheimer's disease, exclusion criteria, chronic disease, neuroimaging
- MeSH terms
- Cognitive Aging, Aged, Alzheimer Disease, Amyloid, Child, Cross-Sectional Studies, Female, Humans, Male, Quality of Life, Amyloid beta-Peptides, Cognitive Dysfunction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review