Ocular Biomarkers for Alzheimer Disease Dementia: An Umbrella Review of Systematic Reviews and Meta-analyses.


Journal

JAMA ophthalmology
ISSN: 2168-6173
Titre abrégé: JAMA Ophthalmol
Pays: United States
ID NLM: 101589539

Informations de publication

Date de publication:
01 01 2023
Historique:
pubmed: 18 11 2022
medline: 24 1 2023
entrez: 17 11 2022
Statut: ppublish

Résumé

Several ocular biomarkers have been proposed for the early detection of Alzheimer disease (AD) and mild cognitive impairment (MCI), particularly fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA). To perform an umbrella review of systematic reviews to assess the diagnostic accuracy of ocular biomarkers for early diagnosis of Alzheimer disease. MEDLINE, Embase, and PsycINFO were searched from January 2000 to November 2021. The references of included reviews were also searched. Systematic reviews investigating the diagnostic accuracy of ocular biomarkers to detect AD and MCI, in secondary care or memory clinics, against established clinical criteria or clinical judgment. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline checklist was followed and the Risk Of Bias in Systematic reviews tool was used to assess review quality. The prespecified outcome was the accuracy of ocular biomarkers for diagnosing AD and MCI. The area under the curve (AUC) was derived from standardized mean difference. From the 591 titles, 14 systematic reviews were included (median [range] number of studies in each review, 14 [5-126]). Only 4 reviews were at low risk of bias on all Risk of Bias in Systematic Reviews domains. The imaging-derived parameters with the most evidence for detecting AD compared with healthy controls were OCT peripapillary retinal nerve fiber layer thickness (38 studies including 1883 patients with AD and 2510 controls; AUC = 0.70; 95% CI, 0.53-0.79); OCTA foveal avascular zone (5 studies including 177 patients with AD and 371 controls; AUC = 0.73; 95% CI, 0.50-0.89); and saccadic eye movements prosaccade latency (30 studies including 651 patients with AD/MCI and 771 controls; AUC = 0.64; 95% CI, 0.58-0.69). Antisaccade error was investigated in fewer studies (12 studies including 424 patients with AD/MCI and 382 controls) and yielded the best accuracy (AUC = 0.79; 95% CI, 0.70-0.88). This umbrella review has highlighted limitations in design and reporting of the existing research on ocular biomarkers for diagnosing AD. Parameters with the best evidence showed poor to moderate diagnostic accuracy in cross-sectional studies. Future longitudinal studies should investigate whether changes in OCT and OCTA measurements over time can yield accurate predictions of AD onset.

Identifiants

pubmed: 36394831
pii: 2798773
doi: 10.1001/jamaophthalmol.2022.4845
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

84-91

Subventions

Organisme : Medical Research Council
ID : MR/N029941/1
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : RF1 AG055654
Pays : United States
Organisme : Department of Health
Pays : United Kingdom

Commentaires et corrections

Type : CommentIn

Auteurs

Eliana Costanzo (E)

IRCCS-Fondazione Bietti, Rome, Italy.

Imre Lengyel (I)

Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, United Kingdom.

Mariacristina Parravano (M)

IRCCS-Fondazione Bietti, Rome, Italy.

Ilaria Biagini (I)

Department NEUROFARBA, University of Florence, Florence, Italy.

Michele Veldsman (M)

Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.

AmanPreet Badhwar (A)

Department of Pharmacology and Physiology, University of Montreal, Montreal, Québec, Canada.
Centre de recherche de l'Institut Universitaire de Geriatrie, Montreal, Québec, Canada.

Matthew Betts (M)

Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
Center for Behavioral Brain Sciences, University of Magdeburg, Magdeburg, Germany.

Antonio Cherubini (A)

Geriatria, Accettazione geriatrica e Centro di ricerca per l'invecchiamento, IRCCS INRCA, Ancona, Italy.

David J Llewellyn (DJ)

College of Medicine and Health, University of Exeter, Exeter, United Kingdom.

Ilianna Lourida (I)

College of Medicine and Health, University of Exeter, Exeter, United Kingdom.

Tom MacGillivray (T)

Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.

Timothy Rittman (T)

Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.

Stefano Tamburin (S)

Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.

Xin You Tai (XY)

Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.

Gianni Virgili (G)

Department NEUROFARBA, University of Florence, Florence, Italy.
Centre for Public Health, Queens University Belfast, Belfast, United Kingdom.

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Classifications MeSH