Dataset Information

Refractory neovascular age-related macular degeneration: time-dependent changes of central retinal thickness with anti-VEGF treatment.

ABSTRACT:

Purpose

To assess the influence of time interval since last injection and time from baseline on central retinal thickness (CRT) in neovascular age-related macular degeneration (nAMD) with fluid refractory to monthly anti-VEGF treatment.

Methods

This retrospective study included nAMD eyes with incomplete response to anti-VEGF defined by the presence of intra- or subretinal fluid on optical coherence tomography despite maximal (monthly) anti-VEGF dosing. The outcome measure was CRT, and two time variables (time from last injection ant time from baseline) were the independent factors included in the individual correlation analyses. In addition, an association analysis was performed.

Results

Sixty eyes of 56 patients (67.9% females, mean age: 78.7 ± 6.8 years) were included with a mean included time period of 35.6 months. A significant positive correlation between CRT and the time from last injection occurred in 24 (40%) and 25 (42%) eyes by univariate and multivariate analysis, respectively. Time from baseline was significantly correlated with CRT in 29 (48.3%) and 30 (50%) eyes by univariate and multivariate analysis, respectively. This correlation was positive in 12 (20%) and negative in 18 eyes (30%). No association with such correlation was found.

Conclusion

So-called refractory nAMD frequently shows a correlation of CRT with the interval in days from the preceding anti-VEGF injection, revealing that there is a subgroup of short-term responsiveness of the residual fluid. Moreover, slower CRT changes may occur over the years, either decrease or increase. In case of a slow CRT increase, this might require a diagnostic workup and therapeutic change.

SUBMITTER: Zola M

PROVIDER: S-EPMC8166689 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionDue to its progressive nature, early evaluation and timely prediction of legal blindness are important in patients with neovascular age-related macular degeneration (nAMD). We examined the association between early-stage variation in central retinal thickness (CRT) and long-term visual outcomes in patients with nAMD.MethodsWe included 103 nAMD patients who were administered anti-vascular endothelial growth factor (anti-VEGF). Participants were considered qualified if they were (1) 50 years and older, (2) treatment-naïve, (3) received standard anti-VEGF treatment and had complete baseline information. We further excluded patients with less than 1-year follow-up data and those who experienced best corrected visual acuity ≤35. Early-stage variability in CRT was measured as the first-year coefficient of variability (CV) of CRT. Patients were then classified into the high-variability and low-variability groups according to the X-tile. A product-limit plot was used to demonstrate the differences and tested with the log-rank test. The association between first-year variability and visual outcomes was quantified using Cox regression models. Time-to-event primary endpoint was the overall visual preservation (OVP) rate, defined as the time from the first injection to legal blindness, i.e., best corrected visual acuity ≤35 Early Treatment Diabetic Retinopathy Study (ETDRS) letters.ResultsA threshold of 20% of first-year CV in CRT was used to categorize 76 qualified patients into high variability (35, 46.1%) and low variability (41, 53.9%). The 5- and 10-year OVPs for patients with high versus low variability were 76% versus 48% and 59% versus 22%, respectively. High early-stage CRT variability showed a significantly higher risk of legal blindness. Even after adjusting for the demographic and clinical features, the variability remained significant (HR = 2.39, 95% CI: 1.20-4.78).ConclusionFirst-year variability of CRT was predictive of long-term visual outcomes in patients with nAMD, and 20% of the variability could be used as a clinically convenient threshold to qualitatively classify patients into high- and low-variability groups. The current study is important for identifying high-risk populations and for long-term disease management.

Project description:PurposeTo probabilistically forecast needed anti-vascular endothelial growth factor (anti-VEGF) treatment frequency using volumetric spectral domain-optical coherence tomography (SD-OCT) biomarkers in neovascular age-related macular degeneration from real-world settings.MethodsSD-OCT volume scans were segmented with a custom deep-learning-based analysis pipeline. Retinal thickness and reflectivity values were extracted for the central and the four inner Early Treatment Diabetic Retinopathy Study (ETDRS) subfields for six retinal layers (inner retina, outer nuclear layer, inner segments [IS], outer segments [OS], retinal pigment epithelium-drusen complex [RPEDC] and the choroid). Machine-learning models were probed to predict the anti-VEGF treatment frequency within the next 12 months. Probabilistic forecasting was performed using natural gradient boosting (NGBoost), which outputs a full probability distribution. The mean absolute error (MAE) between the predicted versus actual anti-VEGF treatment frequency was the primary outcome measure.ResultsIn a total of 138 visits of 99 eyes with neovascular AMD (96 patients) from two clinical centers, the prediction of future anti-VEGF treatment frequency was observed with an accuracy (MAE [95% confidence interval]) of 2.60 injections/year [2.25-2.96] (R2 = 0.390) using random forest regression and 2.66 injections/year [2.31-3.01] (R2 = 0.094) using NGBoost, respectively. Prediction intervals were well calibrated and reflected the true uncertainty of NGBoost-based predictions. Standard deviation of RPEDC-thickness in the central ETDRS-subfield constituted an important predictor across models.ConclusionsThe proposed, fully automated pipeline enables probabilistic forecasting of future anti-VEGF treatment frequency in real-world settings.Translational relevancePrediction of a probability distribution allows the physician to inspect the underlying uncertainty. Predictive uncertainty estimates are essential to highlight cases where human-inspection and/or reversion to a fallback alternative is warranted.

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