September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Progression of late-onset Stargardt disease
Author Affiliations & Notes
  • Stanley Lambertus
    Department of Ophthalmology, Radboud university medical center, Nijmegen, Netherlands
  • Moritz Lindner
    Department of Ophthalmology and GRADE Reading Center, University of Bonn, Bonn, Germany
  • Nathalie Bax
    Department of Ophthalmology, Radboud university medical center, Nijmegen, Netherlands
  • Matthias Marten Mauschitz
    Department of Ophthalmology and GRADE Reading Center, University of Bonn, Bonn, Germany
  • Matthias Schmid
    Informatics and Epidemiology, Institute for Medical Biometry, Bonn, Germany
  • Steffen Schmitz-Valckenberg
    Department for Health Evidence, Radboud university medical center, Nijmegen, Netherlands
  • Bernhard HF Weber
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany
  • Frank G Holz
    Department of Ophthalmology and GRADE Reading Center, University of Bonn, Bonn, Germany
  • Gert Jan van der Wilt
    Department for Health Evidence, Radboud university medical center, Nijmegen, Netherlands
  • Monika Fleckenstein
    Department of Ophthalmology and GRADE Reading Center, University of Bonn, Bonn, Germany
  • Carel C B Hoyng
    Department of Ophthalmology, Radboud university medical center, Nijmegen, Netherlands
  • Footnotes
    Commercial Relationships   Stanley Lambertus, None; Moritz Lindner, Alimera Sciences (R), Carl Zeiss Meditec (F), Genentech (F), Heidelberg Engineering (F), Heidelberg Engineering (R), Optos (F); Nathalie Bax, None; Matthias Mauschitz, None; Matthias Schmid, None; Steffen Schmitz-Valckenberg, Allergan (F), Bayer (F), Bayer (R), Carl Zeiss Meditec (F), Genentech (F), Heidelberg Engineering (F), Heidelberg Engineering (R), Merz (F), Novartis (F), Novartis (C), Novartis (R), Optos (F), Optos (R), Quintiles Commercial (R), Roche (F); Bernhard Weber, None; Frank Holz, Acucela (C), Allergan (C), Bayer (F), Bayer (C), Bayer (R), Boehringer Ingelheim (C), Carl Zeiss Meditec (F), Genentech (F), Genentech (C), Genentech (R), Heidelberg Engineering (F), Heidelberg Engineering (C), Heidelberg Engineering (R), Merz (C), Novartis (F), Novartis (C), Novartis (R), Optos (F), Optos (C); Gert Jan van der Wilt, None; Monika Fleckenstein, Bayer (R), Carl Zeiss Meditec (F), Genentech (F), Genentech (R), Heidelberg Engineering (F), Heidelberg Engineering (R), Merz (C), Novartis (R), Optos (F), US20140303013 A1 pending (P); Carel Hoyng, None
  • Footnotes
    Support  This study was supported by the Stichting A.F. Deutman Researchfonds Oogheelkunde, Nijmegen, The Netherlands; Deutsche Forschungsgemeinschaft, Bonn, Germany, Grant No FL 658/4-1 and Ho1926/3-1; BONFOR GEROK Program, Faculty of Medicine, University of Bonn, Grant No O-137.0020; and by the following foundations that contributed through UitZicht: Stichting MD fonds, Landelijke Stichting voor Blinden en Slechtzienden, and Oogfonds. The funding organizations had no role in the design or conduct of this research. They provided unrestricted grants.
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 2693. doi:
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    • Get Citation

      Stanley Lambertus, Moritz Lindner, Nathalie Bax, Matthias Marten Mauschitz, Matthias Schmid, Steffen Schmitz-Valckenberg, Bernhard HF Weber, Frank G Holz, Gert Jan van der Wilt, Monika Fleckenstein, Carel C B Hoyng; Progression of late-onset Stargardt disease. Invest. Ophthalmol. Vis. Sci. 2016;57(12):2693.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Accurate biomarkers are crucial to determine potential effects of emerging therapeutic trials for Stargardt disease. The natural course of late-onset Stargardt includes a typical phenotype of retinal pigment epithelium (RPE) atrophy that often spares the fovea, and is surrounded by yellow-white flecks. To this end, areas of RPE atrophy could serve as a sensitive monitor for this disease. We therefore performed a retrospective cohort study to show the accuracy of this outcome measure and calculated sample sizes for a simulated trial.

Methods : We analyzed retinal features, visual acuity, and RPE atrophy progression using fundus autofluorescence and near-infrared reflectance imaging in 47 late-onset Stargardt patients (disease onset ≥45 years). Endpoints of visual acuity were observed using Turnbull’s estimators. Progression of RPE atrophy was analyzed by a two-level random effects linear mixed model. Sample size calculations were performed for a 2-year study duration and a dropout rate of 15%.

Results : Survival analysis yielded a median interval between disease onset and a decline in visual acuity to 20/32, 20/80, and 20/200 of 2.74 (95% confidence interval, 0.54-4.41), 10.15 (95% CI, 6.13-11.38), and 11.38 (95% CI, 6.13-13.34) years, respectively. Over time, progression of RPE atrophy was observed (mean, 0.22±0.02 mm/year; p<0.001). If only patients with bilateral RPE atrophy are included in a 2-year study, 32 patients are needed to reach a power of 80% (95% CI, 79.3-82.4), assuming a fixed therapeutic effect size of 30%.

Conclusions : The development of RPE atrophy reflects the most prominent feature of disease progression in late-onset Stargardt. Expansion rates appeared to be fairly slow. Nonetheless, measurements of RPE atrophy resulted in a robust biomarker for disease progression.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

 

Statistical power of a simulated 2-year interventional study in late-onset Stargardt as a function of sample size. Calculations were performed for an expected effect size of 50 % (red), 40 % (blue) and 30 % (green) reduction of atrophy progression. Shown are means (±95% confidence intervals) of 10000 simulations per data point.

Statistical power of a simulated 2-year interventional study in late-onset Stargardt as a function of sample size. Calculations were performed for an expected effect size of 50 % (red), 40 % (blue) and 30 % (green) reduction of atrophy progression. Shown are means (±95% confidence intervals) of 10000 simulations per data point.

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