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Record W1747781838 · doi:10.1001/jama.2015.4669

Prevalence of Amyloid PET Positivity in Dementia Syndromes

2015· review· en· W1747781838 on OpenAlexfundno aff
Rik Ossenkoppele, Willemijn J. Jansen, Gil D. Rabinovici, Dirk L. Knol, Wiesje M. van der Flier, Bart N.M. van Berckel, Philip Scheltens, Pieter Jelle Visser, Sander C.J. Verfaillie, Marissa D. Zwan, Sofie M. Adriaanse, Adriaan A. Lammertsma, Frederik Barkhof, William J. Jagust, Bruce L. Miller, Howard J. Rosen, Susan Landau, Victor L. Villemagne, Christopher C. Rowe, Dong Yeob Lee, Duk L. Na, Sang Won Seo, Marie Sarazin, Catherine M. Roe, Osama Sabri, Henryk Barthel, Norman Koglin, John R. Hodges, Cristian E. Leyton, Rik Vandenberghe, Koen Van Laere, Alexander Drzezga, Stefan Förster, Timo Grimmer, Pascual Sánchez‐Juan, J.M. Carril, Vincent Mok, Vincent Camus, William E. Klunk, Ann D. Cohen, Philipp T. Meyer, Sabine Hellwig, Andrew B. Newberg, Kristian Steen Frederiksen, Adam Fleisher, Mark A. Mintun, David A. Wolk, Agneta Nordberg, Juha O. Rinne, Gaël Chételat, Alberto Lleó, Rafael Blesa, Juan Fortea, Karine Madsen, Karen M. Rodrigue, David J. Brooks

Bibliographic record

VenueJAMA · 2015
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institute of Neurological Disorders and StrokeNational Institute on AgingHealth and Health Services Research FundCharles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. LouisCanadian Institutes of Health ResearchUniversity of California, San DiegoPfizerUniversity of California, Los AngelesAstraZenecaEuropean CommissionGenentechNational Institutes of HealthRégion NormandieUniversity of Texas at DallasIXICOTurun Yliopistollinen KeskussairaalaMedical Research CouncilServierUniversitat Autònoma de BarcelonaUniversidad de CantabriaTurun YliopistoKarolinska InstitutetEisaiDementia Collaborative Research Centres, AustraliaTechnische Universität MünchenDeutsche ForschungsgemeinschaftGentofte HospitalCommonwealth Scientific and Industrial Research OrganisationInstitut National de la Santé et de la Recherche MédicaleBayer HealthCareCenter for Translational Molecular MedicineAvid RadiopharmaceuticalsUniversity of PittsburghWashington University in St. LouisSynarcImperial College LondonLui Che Woo Institute of Innovative MedicineNorthern California Institute for Research and EducationEuropean Federation of Pharmaceutical Industries and AssociationsAlzheimer's AssociationF. Hoffmann-La RocheAmorfix Life SciencesThomas Jefferson UniversityBiogenBioClinicaUniversity of PennsylvaniaBristol-Myers SquibbAmerican Parkinson Disease AssociationJanssen Alzheimer Immunotherapy Research And DevelopmentScience and Industry Endowment FundNational Health and Medical Research CouncilEdith Cowan UniversityMedpaceEli Lilly and CompanyAlzheimer's Disease Neuroimaging InitiativeMeso Scale Diagnostics
KeywordsMedicineDementiaAmyloid (mycology)PathologyDisease

Abstract

fetched live from OpenAlex

IMPORTANCE: Amyloid-β positron emission tomography (PET) imaging allows in vivo detection of fibrillar plaques, a core neuropathological feature of Alzheimer disease (AD). Its diagnostic utility is still unclear because amyloid plaques also occur in patients with non-AD dementia. OBJECTIVE: To use individual participant data meta-analysis to estimate the prevalence of amyloid positivity on PET in a wide variety of dementia syndromes. DATA SOURCES: The MEDLINE and Web of Science databases were searched from January 2004 to April 2015 for amyloid PET studies. STUDY SELECTION: Case reports and studies on neurological or psychiatric diseases other than dementia were excluded. Corresponding authors of eligible cohorts were invited to provide individual participant data. DATA EXTRACTION AND SYNTHESIS: Data were provided for 1359 participants with clinically diagnosed AD and 538 participants with non-AD dementia. The reference groups were 1849 healthy control participants (based on amyloid PET) and an independent sample of 1369 AD participants (based on autopsy). MAIN OUTCOMES AND MEASURES: Estimated prevalence of positive amyloid PET scans according to diagnosis, age, and apolipoprotein E (APOE) ε4 status, using the generalized estimating equations method. RESULTS: The likelihood of amyloid positivity was associated with age and APOE ε4 status. In AD dementia, the prevalence of amyloid positivity decreased from age 50 to 90 years in APOE ε4 noncarriers (86% [95% CI, 73%-94%] at 50 years to 68% [95% CI, 57%-77%] at 90 years; n = 377) and to a lesser degree in APOE ε4 carriers (97% [95% CI, 92%-99%] at 50 years to 90% [95% CI, 83%-94%] at 90 years; n = 593; P < .01). Similar associations of age and APOE ε4 with amyloid positivity were observed in participants with AD dementia at autopsy. In most non-AD dementias, amyloid positivity increased with both age (from 60 to 80 years) and APOE ε4 carriership (dementia with Lewy bodies: carriers [n = 16], 63% [95% CI, 48%-80%] at 60 years to 83% [95% CI, 67%-92%] at 80 years; noncarriers [n = 18], 29% [95% CI, 15%-50%] at 60 years to 54% [95% CI, 30%-77%] at 80 years; frontotemporal dementia: carriers [n = 48], 19% [95% CI, 12%-28%] at 60 years to 43% [95% CI, 35%-50%] at 80 years; noncarriers [n = 160], 5% [95% CI, 3%-8%] at 60 years to 14% [95% CI, 11%-18%] at 80 years; vascular dementia: carriers [n = 30], 25% [95% CI, 9%-52%] at 60 years to 64% [95% CI, 49%-77%] at 80 years; noncarriers [n = 77], 7% [95% CI, 3%-18%] at 60 years to 29% [95% CI, 17%-43%] at 80 years. CONCLUSIONS AND RELEVANCE: Among participants with dementia, the prevalence of amyloid positivity was associated with clinical diagnosis, age, and APOE genotype. These findings indicate the potential clinical utility of amyloid imaging for differential diagnosis in early-onset dementia and to support the clinical diagnosis of participants with AD dementia and noncarrier APOE ε4 status who are older than 70 years.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.015
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.057
GPT teacher head0.387
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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".

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Citations666
Published2015
Admission routes1
Has abstractyes

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