Progression of Abca4-Related Retinopathy

Müller, Philipp L.; Pfau, Maximilian; Treis, Tim; Pascual-Camps, Isabel; Birtel, Johannes; Lindner, Moritz; Herrmann, Philipp; Holz, Frank G.

doi:10.1097/iae.0000000000002747

Cited by 14 publications

(18 citation statements)

References 26 publications

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“…31 Müller et al 4 have reported a mean rate of RPE-atrophy enlargement of 0.89 ± 0.13 mm 2 /year in ABCAArelated retinopathy eyes. Whereas both the ProgStar and Müller et al 4 used the mean as a measure of central tendency, it might be not appropriate in our series as the distribution of progression rates was highly rightskewed ( Supplementary Fig. S3).…”

Section: Discussionmentioning

confidence: 97%

“…30,31 A second model was carried out in which the squareroot-transformed RPE atrophy enlargement rate was the dependent variable. 4 Because baseline SW-FAF and NIR-FAF hypoautofluorescent areas strongly correlated with each other, only the former was included in multivariable models to avoid collinearity. Complete case analysis was used to deal with missing data in all the models.…”

Section: Discussionmentioning

confidence: 99%

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Factors Influencing Retinal Pigment Epithelium-Atrophy Progression Rate in Stargardt Disease

Cicinelli

Rabiolo

Brambati

et al. 2020

Trans. Vis. Sci. Tech.

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To evaluate demographic, clinical, imaging, and genetic factors associated with retinal pigment epithelium enlargement in Stargardt disease (STGD1) and to measure the agreement between short-wavelength fundus autofluorescence (SW-FAF) and near-infrared fundus autofluorescence (NIR-FAF). Methods: Retrospective cohort study of patients with STGD1 with ≥2 gradable SW-FAF images. RPE-atrophy areas were measured on SW-FAF and NIR-FAF at each visit and regressed against time to obtain the rate of RPE-atrophy enlargement. Agreement between SW-FAF and NIR-FAF with regards to baseline atrophic areas and rates of enlargement was evaluated. Baseline factors predictive of faster SW-FAF RPE-atrophy enlargement were investigated with linear mixed models. Results: Fifty-four eyes of 28 patients (median age: 45 years; 13 males) were included. SW-FAF and NIR-FAF agreed well for slow rates of RPE-atrophy progression, but agreement decreased as the rate increased. Median (interquartile range [IQR]) rate of RPE-atrophy expansion was 0.18 (0.10-0.85) mm 2 /year on SW-FAF and 0.24 (0.08-0.33) mm 2 /year on NIR-FAF. Larger baseline RPE-atrophy area (estimate: 0.057 mm 2 /year, P < 0.001), worse visual acuity (0.305 mm 2 /year, P = 0.005), multifocal disease (0.401 mm 2 /year, P = 0.02), and SW-FAF pattern (0.534 mm 2 /year, P =0 .03) were associated with a faster rate of progression (predictive R 2 : 0.65). Conclusions: SW-FAF and NIR-FAF are not interchangeable in the evaluation of RPEatrophy enlargement, and both imaging modalities may be required for optimal detection of disease progression. A multivariable model based on baseline clinical and imaging information may identify patients at higher risk of fast disease progression. Translational Relevance: The knowledge of the agreement of different FAF modalities, the estimated rates of RPE-atrophy enlargement, and factors predictive of faster anatomic decay in STGD1 may allow tailored clinical management and better clinical trials design.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Factors Influencing Retinal Pigment Epithelium-Atrophy Progression Rate in Stargardt Disease

Cicinelli

Rabiolo

Brambati

et al. 2020

Trans. Vis. Sci. Tech.

View full text Add to dashboard Cite

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“…It is characterized by a generally increased fundus autofluorescence (AF) intensity followed by distinct patterns of increased and decreased AF as well as thinning of retinal layers in the optic coherence tomography (OCT) associated with loss of function [3][4][5]. However, the clinical presentation and individual progression rate are highly variable [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…In the view of emerging interventional clinical trials, the ability to identify patients by rate of expected disease progression would be advantageous in order to maximize the potential of an intervention to demonstrate therapeutic effectiveness and improve the efficiency of future trials [7]. Several morphological and functional classifications have been proposed previously [9,10].…”

Section: Introductionmentioning

confidence: 99%

“…Several morphological and functional classifications have been proposed previously [9,10]. The full-field electroretinogram (ERG) based classification developed by Lois and colleagues has been shown to have prognostic value for disease progression and has been used in various studies to date [7][8][9]11]. However, the measurement of ERG is burdensome (i.e., time for dark adaptation), requires highly trained personnel, and is uncomfortable (e.g., due to corneal electrodes) [12].…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Function in ABCA4-Related Retinopathy Using Ensemble Machine Learning

Müller

Treis

Odainic

et al. 2020

JCM

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Full-field electroretinogram (ERG) and best corrected visual acuity (BCVA) measures have been shown to have prognostic value for recessive Stargardt disease (also called “ABCA4-related retinopathy”). These functional tests may serve as a performance-outcome-measure (PerfO) in emerging interventional clinical trials, but utility is limited by variability and patient burden. To address these limitations, an ensemble machine-learning-based approach was evaluated to differentiate patients from controls, and predict disease categories depending on ERG (‘inferred ERG’) and visual impairment (‘inferred visual impairment’) as well as BCVA values (‘inferred BCVA’) based on microstructural imaging (utilizing spectral-domain optical coherence tomography) and patient data. The accuracy for ‘inferred ERG’ and ‘inferred visual impairment’ was up to 99.53 ± 1.02%. Prediction of BCVA values (‘inferred BCVA’) achieved a precision of ±0.3LogMAR in up to 85.31% of eyes. Analysis of the permutation importance revealed that foveal status was the most important feature for BCVA prediction, while the thickness of outer nuclear layer and photoreceptor inner and outer segments as well as age of onset highly ranked for all predictions. ‘Inferred ERG’, ‘inferred visual impairment’, and ‘inferred BCVA’, herein, represent accurate estimates of differential functional effects of retinal microstructure, and offer quasi-functional parameters with the potential for a refined patient assessment, and investigation of potential future treatment effects or disease progression.

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Genotype–Phenotype Association in ABCA4-Associated Retinopathy

Pfau

Zein

Huryn

et al. 2023

Advances in Experimental Medicine and Biology

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Progression of Abca4-Related Retinopathy

Abstract: This study underscores the prognostic value of demographic, functional, genetic, and lesion geometry parameters in ABCA4-related retinopathy. Trial design including inclusion criteria based on these factors may provide economic benefits by selection of appropriate participants.

Cited by 14 publications

References 26 publications

Factors Influencing Retinal Pigment Epithelium-Atrophy Progression Rate in Stargardt Disease

Factors Influencing Retinal Pigment Epithelium-Atrophy Progression Rate in Stargardt Disease

Prediction of Function in ABCA4-Related Retinopathy Using Ensemble Machine Learning

Genotype–Phenotype Association in ABCA4-Associated Retinopathy

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