Artificial Intelligence Analysis of Biofluid Markers in Age-Related Macular Degeneration: A Systematic Review

Pucchio, Aidan; Krance, Saffire H.; Pur, Daiana R.; Miranda, Rafael N; Felfeli, Tina

doi:10.2147/opth.s377262

Cited by 10 publications

(8 citation statements)

References 70 publications

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“…death, chance of recovery, recurrence) and the frequency with which these outcomes can be expected to occur (49). Precise prognostic predictions, prognostic analysis, prognostic assumptions, and prognostic decision-making in a clinical setting are the practical aspects of arti cial intelligence in the prognosis of diseases (48, [50][51][52][53][54]. This ability of AI can help clinicians to make better decisions on the possible outcome of diseases.…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Applications in Decision Making for Disease Management

Abdekhoda

Ranjbaran

2023

Preprint

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Background: Artificial intelligence (AI) has several potential applications in medicine, creating opportunities for reliable and evidence based decision making in disease management. Thus, the practical aspects of AI in decision-making should be identified. This study was conducted to identify AI applications in decision making for disease management. Method: This study was a systematic review using the PRISMA-ScR checklist. Data collection was carried out by searching the related keywords in WOS and Scopus in May 2023. Results: Regarding the AI applications in decision making for disease management, we found 80 sub-themes which were categorized into six themes, i.e. 1) Processing and managing data, 2) Characterization and analysis, 3) Prediction and risk stratification, 4) Screening, 5) Prognosis, and 6) Diagnosis. Conclusion: AI has considerable capability in disease treatment and would be an integral part of medicine in the future. This study clearly identified six main themes that addressed AI capability in decision making for disease management. The use of AI can help in making medical decisions with more trust and confidence and thus make medical interventions more accurate and effective.

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Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Applications in Decision Making for Disease Management

Abdekhoda

Ranjbaran

2023

Preprint

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“…Establishing their role in refining treatment paradigms in the real world is required, particularly in large volume retinal clinics with multiple clinicians. Artificial intelligence may have a role in the detection of disease activity including in retinal fluid analysis [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Systematic Review of Neovascular Age-Related Macular Degeneration Disease Activity Criteria Use to Shorten, Maintain or Extend Treatment Intervals with Anti-VEGF in Clinical Trials: Implications for Clinical Practice

2023

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Introduction Clinical trials in neovascular age-related macular degeneration (nAMD) using anti-vascular endothelial growth factor (ant-VEGF) injections use disease activity (DA) criteria to shorten, maintain or increase the interval between injections. Differences in these DA criteria may contribute to differences in the proportions of patients with macular fluid at key time points or achieving extended dosing intervals in these trials. We identified, collated and evaluated DA criteria from pivotal anti-VEGF nAMD trials to understand how differences impact on these studies and real-world visual acuity and extending dosing outcomes. Methods This was a systematic review of literature on Pubmed for randomised clinical trials in nAMD using a proactive treatment regimen. We excluded case reports, review articles and studies on fewer than 50 participants. Results Twelve clinical trials (LUCAS, VIEW, TREX-AMD, FLUID, TREND, RIVAL, ALTAIR, CANTREAT, ARIES, TREX-Conbercept, HAWK & HARRIER, TENAYA & LUCERNE) investigating anti-VEGF treatment of nAMD were identified according to our search strategy. Different studies utilised a different combination of DA criteria. Specifically, six trials included visual acuity change; four included macular thickness change; one included visual acuity change if associated with macular thickness change; one with qualitative optical coherence tomography (OCT) features; four with qualitative OCT features if also associated with visual acuity change; 10 with macular haemorrhage and five with other fluorescein angiographic features. Conclusion Different clinical trials use different DA criteria when altering the interval between anti-VEGF injections. This makes it difficult to draw meaningful conclusions about secondary outcomes such as proportion of patients treated at extended dosing intervals or proportions of eyes with persistent subretinal or intraretinal fluid. Standardising DA criteria in clinical trials and preferentially using those easily applied in a real-world setting would lead to results more achievable in real-world settings and for a meaningful comparison of treatment durability.

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“…The use of biomarker analysis with artificial intelligence has been demonstrated in many ophthalmic diseases, such as glaucoma, uveitis, uveal melanoma, age-related macular degeneration, corneal and ocular surface diseases, and retinal occlusive diseases. [8][9][10][11][12] Herein, we evaluated the variability of intraocular inflammatory biomarkers in multiplex assays of intraocular biofluid samples.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Variability of Replicates of Intraocular Inflammatory Biomarkers in Ocular Fluid Samples Analyzed with Multiplex Assays

Lamoureux,

Wong,

Felfeli

2023

OPTH

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Certain factors such as instrumental and sample processing errors may contribute to variability of ocular biofluid samples when they are run as replicates with multiplex assays. There is a paucity of literature on the variability of replicates in multiplex assays. This study aims to evaluate whether there is significant variability in replicate analyses of multiplex assays. Methods: A total of 152 human ocular biofluid samples (51 aqueous humor and 101 vitreous) were collected and assayed for 27 cytokine biomarker concentrations (pg/mL). Samples were evaluated as replicates (duplicate analysis) at four different time points. Statistical methods including paired samples t-test, 3-way ANOVA, intraclass correlation coefficient (ICC; <0.5-0.75=poor-moderate, 0.75->0.90 =good-excellent reliability), and coefficients of variation (CV) were employed to evaluate for statistical significance, with Bonferroni corrected P=0.002. Results: Among the 4104 biomarker replicate assays for aqueous humor and vitreous, two analytes (PDGF-BB and IL-7) had a statistically significant difference between the sampled concentrations of the replicates in vitreous samples (mean (diff)=2.05, P<0.001, mean (diff)=1.56, P<0.001, respectively). Majority of the ICC values fell within the good-excellent range (86% of samples) with a minority falling in the poor-moderate range (14% of samples). More variability was noted in the vitreous humour, with five analytes (IL-2, IL-10, IL-12(p70), IL-13, IL-17) demonstrating an average ICC of less than 0.5. The CV calculated for each set of replicates suggested that 93% of replicates had an acceptable level of quantitative assay variability (CV<20%). Conclusion:This study demonstrates that the analysis of most biomarkers in ocular fluids may not require the use of replicates. However, certain analytes such as PDGF-BB and IL-7 may require the use of replicates to ensure reliable results. Caution should be taken when applying these findings to other laboratory settings as our study was conducted by an experienced technician using a standardized protocol. In less standardized settings, replicates may be required in order to ensure accuracy of results. These findings may guide researchers with the design of their studies on ophthalmic biomarker analysis.

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Artificial Intelligence Analysis of Biofluid Markers in Age-Related Macular Degeneration: A Systematic Review

Cited by 10 publications

References 70 publications

Artificial Intelligence Applications in Decision Making for Disease Management

Artificial Intelligence Applications in Decision Making for Disease Management

Systematic Review of Neovascular Age-Related Macular Degeneration Disease Activity Criteria Use to Shorten, Maintain or Extend Treatment Intervals with Anti-VEGF in Clinical Trials: Implications for Clinical Practice

Variability of Replicates of Intraocular Inflammatory Biomarkers in Ocular Fluid Samples Analyzed with Multiplex Assays

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