Literature DB >> 33214501

PROGRESSION OF ABCA4-RELATED RETINOPATHY: Prognostic value of demographic, functional, genetic, and imaging parameters.

Philipp L Müller1,2,3, Maximilian Pfau1, Tim Treis4, Isabel Pascual-Camps5, Johannes Birtel1,2, Moritz Lindner1,6, Philipp Herrmann1,2, Frank G Holz1,2.   

Abstract

PURPOSE: To investigate the prognostic value of demographic, functional, genetic, and imaging parameters on retinal pigment epithelium atrophy progression secondary to ABCA4-related retinopathy.
METHODS: Patients with retinal pigment epithelium atrophy secondary to ABCA4-related retinopathy were examined longitudinally with fundus autofluorescence imaging. Lesion area, perimeter, circularity, caliper diameters, and focality of areas with definitely decreased autofluorescence were determined. A model was used to predict the lesion enlargement rate based on baseline variables. Sample size calculations were performed to model the power in a simulated interventional study.
RESULTS: Sixty-eight eyes of 37 patients (age range, 14-78 years) with a follow-up time of 10 to 100 months were included. The mean annual progression of retinal pigment epithelium atrophy was 0.89 mm. The number of atrophic areas, the retina-wide functional impairment, and the age-of-onset category constituted significant predictors for future retinal pigment epithelium atrophy growth, explaining 25.7% of the variability. By extension of a simulated study length and/or specific patient preselection based on these baseline characteristics, the required sample size could significantly be reduced.
CONCLUSION: Trial design based on specific shape-descriptive factors and patients' baseline characteristics and the adaption of the trial duration may provide potential benefits in required cohort size and absolute number of visits.

Entities:  

Year:  2020        PMID: 33214501     DOI: 10.1097/IAE.0000000000002747

Source DB:  PubMed          Journal:  Retina        ISSN: 0275-004X            Impact factor:   4.256


  5 in total

1.  Inferred retinal sensitivity in recessive Stargardt disease using machine learning.

Authors:  Philipp L Müller; Alexandru Odainic; Tim Treis; Philipp Herrmann; Adnan Tufail; Frank G Holz; Maximilian Pfau
Journal:  Sci Rep       Date:  2021-01-14       Impact factor: 4.379

2.  Reliability of Retinal Pathology Quantification in Age-Related Macular Degeneration: Implications for Clinical Trials and Machine Learning Applications.

Authors:  Philipp L Müller; Bart Liefers; Tim Treis; Filipa Gomes Rodrigues; Abraham Olvera-Barrios; Bobby Paul; Narendra Dhingra; Andrew Lotery; Clare Bailey; Paul Taylor; Clarisa I Sánchez; Adnan Tufail
Journal:  Transl Vis Sci Technol       Date:  2021-03-01       Impact factor: 3.283

3.  Photoreceptor degeneration in ABCA4-associated retinopathy and its genetic correlates.

Authors:  Maximilian Pfau; Catherine A Cukras; Laryssa A Huryn; Wadih M Zein; Ehsan Ullah; Marisa P Boyle; Amy Turriff; Michelle A Chen; Aarti S Hinduja; Hermann Ea Siebel; Robert B Hufnagel; Brett G Jeffrey; Brian P Brooks
Journal:  JCI Insight       Date:  2022-01-25

4.  SIBLING CONCORDANCE IN SYMPTOM ONSET AND ATROPHY GROWTH RATES IN STARGARDT DISEASE USING ULTRA-WIDEFIELD FUNDUS AUTOFLUORESCENCE.

Authors:  Rachael C Heath Jeffery; Jennifer A Thompson; Johnny Lo; Tina M Lamey; Terri L McLaren; John N De Roach; Dimitar N Azamanov; Ian L McAllister; Ian J Constable; Fred K Chen
Journal:  Retina       Date:  2022-04-24       Impact factor: 3.975

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

Authors:  Philipp L Müller; Tim Treis; Alexandru Odainic; Maximilian Pfau; Philipp Herrmann; Adnan Tufail; Frank G Holz
Journal:  J Clin Med       Date:  2020-07-29       Impact factor: 4.241

  5 in total

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