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Ocular Biomarkers for Alzheimer Disease DementiaAn Umbrella Review of Systematic Reviews and Meta-analyses

To identify the key insights or developments described in this article
1 Credit CME
Key Points

Question  What is the diagnostic accuracy of ocular biomarkers for early diagnosis of Alzheimer disease (AD), as investigated in systematic reviews?

Finding  In this umbrella review of 14 systematic reviews and meta-analyses, optical coherence tomography peripapillary retinal nerve fiber layer thickness, optical coherence tomography angiography, foveal avascular zone measurement, and prosaccade latency of saccadic eye movements were extensively investigated and yielded only moderate accuracy. Antisaccade error showed the best accuracy in a smaller number of trials.

Meaning  This study found that ocular biomarkers showed poor to moderate diagnostic accuracy for detection of AD in cross-sectional studies; longitudinal studies are needed on whether changes in these parameters could yield better predictions of AD onset.

Abstract

Importance  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).

Objective  To perform an umbrella review of systematic reviews to assess the diagnostic accuracy of ocular biomarkers for early diagnosis of Alzheimer disease.

Data Sources  MEDLINE, Embase, and PsycINFO were searched from January 2000 to November 2021. The references of included reviews were also searched.

Study Selection  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.

Data Extraction and Synthesis  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.

Main Outcomes and Measures  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.

Results  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).

Conclusions and Relevance  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.

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Article Information

Accepted for Publication: September 28, 2022.

Published Online: November 17, 2022. doi:10.1001/jamaophthalmol.2022.4845

Corresponding Author: Gianni Virgili, MD, Centre for Public Health, Queen’s University Belfast, Institute of Clinical Science, Block A, Royal Victoria Hospital, Belfast BT12 6BA, United Kingdom (g.virgili@qub.ac.uk).

Author Contributions: Drs Costanzo and Virgili had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Costanzo, Lengyel, Parravano, Veldsman, Badhwar, Llewellyn, Lourida, MacGillivray, Rittman, Virgili.

Acquisition, analysis, or interpretation of data: Costanzo, Lengyel, Biagini, Badhwar, Betts, Cherubini, Llewellyn, Rittman, Tamburin, Tai, Virgili.

Drafting of the manuscript: Costanzo, Lengyel, Biagini, Veldsman, Badhwar, Lourida, MacGillivray, Tai, Virgili.

Critical revision of the manuscript for important intellectual content: Costanzo, Lengyel, Parravano, Veldsman, Badhwar, Betts, Cherubini, Llewellyn, Lourida, MacGillivray, Rittman, Tamburin, Tai.

Statistical analysis: Virgili.

Obtained funding: Virgili.

Administrative, technical, or material support: Costanzo, Lengyel, Veldsman, Badhwar, Betts, Tai, Virgili.

Supervision: Costanzo, Lengyel, Parravano, Llewellyn, Rittman, Virgili.

Conflict of Interest Disclosures: Dr Parravano reports personal fees from Allergan, Novartis, Bayer, Roche, and Zeiss outside the submitted work. No other disclosures were reported.

Funding/Support: The research reported in this publication was supported by a grant from the Italian Ministry of Health, under the Aging Network of Italian Research Hospitals (IRCCS). The work was also supported by grant from the Medical Research Council of UK (grant MR/N029941/1) and an unrestricted grant from OPTOS Plc. The research for this article was financially supported by the Italian Ministry of Health and Fondazione Roma. This work was also funded by Alzheimer's Research UK (to Dr Llewellyn), Alan Turing Institute/Engineering and Physical Sciences Research Council (grant EP/N510129/1, to Dr Llewellyn), the National Institute for Health Research Applied Research Collaboration South West Peninsula (to Dr Llewellyn), National Health and Medical Research Council (to Dr Llewellyn), and the National Institute on Aging/National Institutes of Health (grant RF1AG055654, to Dr Llewellyn).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We are grateful to Iris Gordon, MSc (Information Specialist, Centre for Public Health, Queens University Belfast, UK), for conducting the searches for this review; compensation was not received.

AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

  • 1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
  • 1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
  • 1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
  • 1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
  • 1.00 credit toward the CME [and Self-Assessment requirements] of the American Board of Surgery’s Continuous Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.

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