Progression of Stargardt Disease as Determined by Fundus Autofluorescence Over a 12-Month Period: ProgStar Report No. 11

Rupert W Strauss; Xiangrong Kong; Alexander Ho; Anamika Jha; Sheila West; Michael Ip; Paul S Bernstein; David G Birch; Artur V Cideciyan; Michel Michaelides; José-Alain Sahel; Janet S Sunness; Elias I Traboulsi; Eberhart Zrenner; Sean Pitetta; Dennis Jenkins; Amir Hossein Hariri; SriniVas Sadda; Hendrik P N Scholl

doi:10.1001/jamaophthalmol.2019.2885

. 2019 Aug 1;137(10):1134–1145. doi: 10.1001/jamaophthalmol.2019.2885

Progression of Stargardt Disease as Determined by Fundus Autofluorescence Over a 12-Month Period

ProgStar Report No. 11

Rupert W Strauss ^1,^2,^3,⁴, Xiangrong Kong ^1,⁵, Alexander Ho ⁶, Anamika Jha ⁶, Sheila West ¹, Michael Ip ⁶, Paul S Bernstein ⁷, David G Birch ⁸, Artur V Cideciyan ⁹, Michel Michaelides ², José-Alain Sahel ¹⁰, Janet S Sunness ¹¹, Elias I Traboulsi ¹², Eberhart Zrenner ¹³, Sean Pitetta ⁶, Dennis Jenkins ⁶, Amir Hossein Hariri ⁶, SriniVas Sadda ⁶, Hendrik P N Scholl ^1,^14,^15,^✉, for the ProgStar Study Group

¹Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland

²Moorfields Eye Hospital National Health Services Foundation Trust and UCL Institute of Ophthalmology, University College London, London, United Kingdom

³Department of Ophthalmology, Johannes Kepler University Clinic Linz, Linz, Austria

⁴Department of Ophthalmology, Medical University Graz, Graz, Austria

⁵Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst

⁶Doheny Eye Institute, David Geffen School of Medicine, University of California, Los Angeles

⁷Moran Eye Center, University of Utah School of Medicine, Salt Lake City

⁸Retina Foundation of the Southwest, Dallas, Texas

⁹Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia

¹⁰Sorbonne Universités, University Pierre et Marie Curie Université de Paris 06, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la Vision, Centre Hospitalier National d’Ophtalmologie des Quinze-Vingts, Paris, France

¹¹Hoover Low Vision Rehabilitation Services, Greater Baltimore Medical Center, University of Maryland School of Medicine, Baltimore, Maryland

¹²Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio

¹³Center for Ophthalmology, Eberhard-Karls University Hospital, Tübingen, Germany

¹⁴Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland

¹⁵Department of Ophthalmology, University of Basel, Basel, Switzerland

Group Information: The ProgStar Study Group members appear at the end of the article.

Accepted for Publication: June 6, 2019.

^✉

Corresponding Author: Hendrik P. N. Scholl, MD, MA, Institute of Molecular and Clinical Ophthalmology Basel, Mittlere Strasse 91, CH-4031 Basel, Switzerland (hendrik.scholl@iob.ch).

Published Online: August 1, 2019. doi:10.1001/jamaophthalmol.2019.2885

Author Contributions: Dr Scholl had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Strauss, Birch, Michaelides, Sahel, Traboulsi, Hariri, Scholl.

Acquisition, analysis, or interpretation of data: Strauss, Kong, Ho, Jha, West, Ip, Bernstein, Birch, Cideciyan, Michaelides, Sunness, Zrenner, Pitetta, Jenkins, Hariri, Sadda, Scholl.

Drafting of the manuscript: Strauss, Kong, Jha, Michaelides, Scholl.

Critical revision of the manuscript for important intellectual content: Strauss, Kong, Ho, West, Ip, Bernstein, Birch, Cideciyan, Michaelides, Sahel, Sunness, Traboulsi, Zrenner, Pitetta, Jenkins, Hariri, Sadda, Scholl.

Statistical analysis: Kong, West, Ip, Jenkins.

Obtained funding: Scholl.

Administrative, technical, or material support: Strauss, Ho, Jha, West, Birch, Cideciyan, Michaelides, Sahel, Sunness, Traboulsi, Pitetta, Hariri, Scholl.

Supervision: Strauss, Ip, Birch, Michaelides, Zrenner, Sadda, Scholl.

Conflict of Interest Disclosures: Dr Bernstein reports grants from the Foundation Fighting Blindness during the conduct of the study and personal fees from Spark, Acucela, Makindus, and Science Based Health, outside the submitted work. Dr Birch reports serving as a consultant for and receiving grants from Applied Genetic Technologies Corporation, Ionis, Genentech, Nightstar, 4D Molecular Therapeutics, and the Foundation Fighting Blindness; receiving personal fees from Nacuity and Editas Medicine; and receiving grants from Allergan, Second Sight Medical Products, the National Institutes of Health (grant ET09076), and the Foundation Fighting Blindness. Dr Sadda reports personal fees from Heidelberg Engineering, Centervue, Novartis, Genentech/Roche, Allergan, and Amgen; grants and personal fees from Optos; grants from Carl Zeiss Meditec; and nonfinancial support from Nidek and Topcon Medical Systems during the conduct of the study. Dr West reports membership in scientific technical advisory committee for Alcon Research Institute and Research to Prevent Blindness Inc. Dr Scholl is a paid consultant of Boehringer Ingelheim Pharma GmbH & Co, Gerson Lehrman Group, and Guidepoint; a member of the scientific advisory board of the Astellas Institute for Regenerative Medicine, ReNeuron Group plc/Ora Inc, and Vision Medicines Inc; and a member of the data monitoring and safety board/committee of Genentech Inc, Hoffmann–La Roche Ltd, and ReNeuron Group plc/Ora Inc. Dr Hendrik Scholl is a principal investigator of grants at the Universitätsspital Basel, which is sponsored by Acucela Inc, NightstaRx Ltd, and Ophthotech Corporation. Dr Strauss reports receiving stipends from the Austrian Science Fund (project number J 3383-B23) and the Foundation Fighting Blindness Clinical Research Institute. Dr Cideciyan reports receiving grants from the National Institutes of Health (grant EY013203). Dr Michaelides reports receiving career development award via the Foundation Fighting Blindness Career Development Award, the Macular Society, Retinitis Pigmentosa Fighting Blindness, Fight for Sight, and the National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital National Health Services Foundation Trust and UCL Institute of Ophthalmology. Michael Ip reports serving as a consultant of Allergan, Thrombogenics, Omeros, Genentech, Quark, Alimera, and Boehringer Ingelheim. Dr Sahel reports grants from LabEx Lifesenses (grant ANR-10-LABX-65) and the Foundation Fighting Blindness during the conduct of the study; grants from ERC Synergy “Helmholtz” and Banque Publique d'Investissement outside the submitted work; and fees associated with work as a consultant for Pixium Vision, GenSight Biologics, and Genesignal, outside the submitted work; with additional personal financial interests in GenSight Biologics, Chronocam, Chronolife, Pixium Vision, Tilak Healthcare, and Sparing Vision. Dr Sunness reports personal fees from Acucela and Cell Cure, outside the submitted work. Dr Traboulsi reports serving on the data and safety monitoring committee for a study on gene therapy in Stargardt disease outside the submitted work. No other disclosures were reported.

Funding/Support: The ProgStar studies are supported by the Foundation Fighting Blindness Clinical Research Institute and a grant to the Foundation Fighting Blindness Clinical Research Institute by the US Department of Defense US Army Medical Research & Materiel Command Telemedicine and Advanced Technology Research Center Research (grants W81-XWH-07-1-0720 and W81XWH-09-2-0189); Dr Scholl is supported by the Foundation Fighting Blindness Clinical Research Institute. Shulsky Foundation, National Centre of Competence in Research Molecular Systems Engineering (University of Basel and Eidgenössische Technische Hochschule Zürich), and Swiss National Science Foundation. Dr Strauss is supported by the Austrian Science Fund (project number J 3383-B23) and the Foundation Fighting Blindness Clinical Research Institute.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: The ProgStar study is supported by a contract from the Foundation Fighting Blindness. The ProgStar studies consist of the Chair’s Office, 9 clinics, 2 resource centers, and 2 affiliated centers with the following members: Chair’s Office: Hendrik P. N. Scholl, MD; Rupert W. Strauss, MD; Yulia Wolfson, MD; Millena Bittencourt, MD; Syed Mahmood Shah, MD; Mohamed Ahmed, MD; Etienne Schönbach, MD; Kaoru Fujinami, MD, PhD; Cole Eye Institute, Cleveland, Ohio: Elias Traboulsi, MD; Justis Ehlers, MD; Meghan Marino, MS; Susan Crowe, BS; Rachael Briggs, COA; Angela Borer, BS; Anne Pinter, CRA; Tami Fecko; Nikki Burgnoni, MS; Greater Baltimore Medical Center, Towson, Maryland: Janet S. Sunness, MD; Carol Applegate, MLA, COT; Leslie Russell, MAc; Moorfields Eye Hospital, London, United Kingdom: Michel Michaelides, MD; Simona Degli Esposti, MD; Anthony Moore; Andrew Webster, MD; Sophie Connor, BSc; Jade Barnfield, BA; Zaid Salchi, MD; Clara Alfageme, MD; Victoria McCudden; Maria Pefkianaki, MD; Jonathan Aboshiha, MA, MB; Gerald Liew; Graham Holder, PhD; Anthony Robson, PhD; Alexa King, BA; Daniela Ivanova Cajas Narvaez, MSc; Katy Barnard, BS; Catherine Grigg, BSc; Hannah Dunbar, PhD; Yetunde Obadeyi; Karine Girard-Claudon, MST; Hilary Swann, BSc; Avani Rughani, BSc; Charles Amoah, NVQ; Dominic Carrington; Kanom Bibi, BSc; Emerson Ting Co, DMD; Mohamed Nafaz Illiyas; Hamida Begum, BSc; Andrew Carter, BSc; Anne Georgiou, PhD; Selma Lewism BSc; Saddaf Shaheen, PGDip, BSc; Harpreet Shinmar, MSc; Linda Burton, BSc; Moran Eye Center, Salt Lake City, Utah: Paul Bernstein, MD, PhD; Kimberley Wegner, BS; Briana Lauren Sawyer, MS; Bonnie Carlstrom, COA; Kellian Farnsworth, COA; Cyrie Fry, AS, CRA, OCT-C; Melissa Chandler, BS, CRC, OCT-a; Glen Jenkins, BS, COA, CRC, OCT-a; Donnel Creel, PhD. Retina Foundation of the Southwest, Dallas: David Birch, PhD; Yi-Zhong Wang, PhD; Luis Rodriguez, BS; Kirsten Locke, BS; Martin Klein, MS; Paulina Mejia, BS; Scheie Eye Institute, Philadelphia, Pennsylvania: Artur V. Cideciyan, PhD; Samuel G. Jacobson, MD, PhD; Sharon B. Schwartz, MS, CGC; Rodrigo Matsui, MD; Michaela Gruzensky, MD; Jason Charng, OD, PhD; Alejandro J. Roman, MS; University of Tübingen, Tübingen, Germany: Eberhart Zrenner, PhD; Fadi Nasser, MD; Gesa Astrid Hahn, MD; Barbara Wilhelm, MD; Tobias Peters, MD; Benjamin Beier, BSc; Tilman Koenig; Susanne Kramer, DiplBiol; The Vision Institute, Paris, France: José-Alain Sahel, MD; Saddek Mohand-Said, MD, PhD; Isabelle Audo, MD, PhD; Caroline Laurent-Coriat, MD; Ieva Sliesoraityte, MD, PhD; Christina Zeitz, PhD; Fiona Boyard, BS; Minh Ha Tran, BS; Mathias Chapon, COT; Céline Chaumette, COT; Juliette Amaudruz, COT; Victoria Ganem, COT; Serge Sancho, COT; Aurore Girmens, COT. The Wilmer Eye Institute, Baltimore, Maryland: Hendrik P. N. Scholl, MD; Rupert W. Strauss, MD; Yulia Wolfson, MD; Syed Mahmood Shah, MD; Mohamed Ahmed, MD; Etienne Schönbach, MD; Robert Wojciechowski, PhD; Shazia Khan, MD; David G. Emmert, BA; Dennis Cain, CRA; Mark Herring, CRA; Jennifer Bassinger, COA; Lisa Liberto, COA; Dana Center Data Coordinating Center at the Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland, United States: Sheila K. West, PhD; Ann-Margret Ervin, PhD; Beatriz Munoz, MS; Xiangrong Kong, PhD; Kurt Dreger, BS; Jennifer Jones, BA; Robert Burke, BA; Doheny Image Reading Center, Los Angeles, California: Srinivas Sadda, MD; Michael S. Ip, MD; Anamika Jha, MBS; Alex Ho, BS; Brendan Kramer, BA; Ngoc Lam, BA; Rita Tawdros, BS; Yong Dong Zhou, MD, PhD; Johana Carmona, HS; Akihito Uji, MD, PhD; Amirhossein Hariri, MD; Amy Lock, BS; Anthony Elshafei, BS; Anushika Ganegoda, BS; Christine Petrossian, BS; Dennis Jenkins, MPH; Edward Strnad, BS; Elmira Baghdasaryan, MD; Eric Ito, OD; Feliz Samson, BS; Gloria Blanquel, BS; Handan Akil, MD, FEBOpht; Jhanisus Melendez, MS; Jianqin Lei, MD; Jianyan Huang, MD, PhD; Jonathan Chau, BS; Khalil G. Falavarjani, MD; Kristina Espino, BS; Manfred Li, BS; Maria Mendoza, BS; Muneeswar Gupta Nittala, MPhil Opt; Netali Roded, BS; Nizar Saleh, MD; Ping Huang, MD, PhD; Sean Pitetta, BS; Siva Balasubramanian, MD, PhD; Sophie Leahy, BA; Sowmya J. Srinivas, MBBS; Swetha B. Velaga, B Opt; Teresa Margaryan, BA; Tudor Tepelus, PhD; Tyler Brown, BS; Wenying Fan, MD; Yamileth Murillo, BA; Yue Shi, MD, PhD; Katherine Aguilar, BS; Cynthia Chan, BS; Lisa Santos, HS; Brian Seo, BA; Christopher Sison, BS; Silvia Perez, BS; Stephanie Chao, HS; Kelly Miyasato, MPH; Julia Higgins, MS; Zoila Luna, MHA; Anita Menchaca, BS; Norma Gonzalez, MA; Vicky Robledo, BS; Karen Carig, BS; Kirstie Baker, HS; David Ellenbogen, BS; Daniel Bluemel, AA; Theo Sanford, BS; Daisy Linares, HS; Mei Tran, BA; Lorane Nava, HS; Michelle Oberoi, BS; Mark Romero, HS; Vivian Chiguil, HS; Grantley Bynum-Bain, BA; Monica Kim, BS; Carolina Mendiguren, MEM; Xiwen Huang, MPH; Monika Smith, HS. A list of study members also appears in the eAppendix in the Supplement.

Additional Contributions: We thank Melissa Kasilian, BA, University College London Institute of Ophthalmology, for assistance with editing the figures of this article. She did not receive any compensation.

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Corresponding author.

PMCID: PMC6681653 PMID: 31369039

Key Points

Question

What is the growth rate of atrophic lesions in patients with Stargardt disease?

Findings

In this cohort study, the mean progression of definitely decreased autofluorescence lesions was 0.76 mm² per year, and the mean progression of the area of total decreased fundus autofluorescence was 0.64 mm² per year. Rates of progression depended on initial lesion size.

Meaning

The growth rate of atrophic lesions as determined by fundus autofluorescence may be a suitable outcome measure of treatment trials for patients with Stargardt disease.

This cohort study estimates the progression rate of atrophic lesions over a 12-month period in the eyes of individuals with Stargardt disease.

Abstract

Importance

Sensitive outcome measures for disease progression are needed for treatment trials of Stargardt disease.

Objective

To estimate the progression rate of atrophic lesions in the prospective Natural History of the Progression of Atrophy Secondary to Stargardt Disease (ProgStar) study over a 12-month period.

Design, Setting, and Participants

This multicenter prospective cohort study was conducted in an international selection of tertiary referral centers from October 21, 2013, to February 15, 2017. Patients who were affected by Stargardt disease, aged 6 years and older at baseline, and harboring disease-causing variants of the ABCA4 gene were enrolled at 9 centers in the United States, United Kingdom, and continental Europe. Data analysis occurred from November 2016 to January 2017.

Exposures

Autofluorescence images obtained with a standard protocol were sent to a central reading center, and areas of definitely decreased autofluorescence, questionably decreased autofluorescence, and the total combined area of decreased autofluorescence were outlined and quantified. Progression rates were estimated from linear mixed models with time as the independent variable.

Main Outcomes and Measures

Yearly rate of progression, using the growth of atrophic lesions measured by autofluorescence imaging.

Results

A total of 259 study participants (488 eyes; 230 individuals [88.8%] were examined in both eyes) were enrolled (mean [SD] age at first visit, 33.3 [15.1] years; 118 [54.4%] female). Gradable images were available for evaluation for 480 eyes at baseline and 454 eyes after 12 months. At baseline, definitely decreased autofluorescence was present in 306 eyes, and the mean (SD) lesion size was 3.93 (4.37) mm². The mean total area of decreased autofluorescence at baseline was 4.07 (4.04) mm². The estimated progression of definitely decreased autofluorescence was 0.76 (95% CI, 0.54-0.97) mm² per year (P < .001), and the total area of both questionably and definitely decreased autofluorescence was 0.64 (95% CI, 0.50-0.78) mm²per year (P < .001). Both progression rates depended on initial lesion size.

Conclusions and Relevance

In Stargardt disease, autofluorescence imaging may serve as a monitoring tool and definitely decreased autofluorescence and total area as outcome measures for interventional clinical trials that aim to slow disease progression. Rates of progression depended mainly on initial lesion size.

Introduction

Autosomal-recessive Stargardt macular dystrophy (STGD1; OMIM: 248200) attributable to disease-causing variants in the ABCA4 gene is the most common form of juvenile macular degeneration.^1,2 Although there are no approved therapies available, possible treatment approaches, including pharmacotherapy, gene augmentation therapy, and stem cell therapy, are all in early clinical development.^2,3 However, the natural history of STGD1 remains poorly characterized, and sensitive, reliable, and clinically relevant outcome measures are needed for clinical trials.⁴ Hence, the retrospective and prospective multicenter Natural History of the Progression of Atrophy Secondary to Stargardt Disease (ProgStar) studies were launched to characterize the natural history of the disease.⁵ In both studies, the primary outcome measure is the yearly rate of progression of STGD1 as reflected by the growth or the development of atrophic lesions measured by autofluorescence (AF) imaging.⁵ There is precedence of this outcome measure in clinical trials and natural history studies in geographic atrophy secondary to age-related macular degeneration (AMD),^6,7 especially as regulatory agencies have accepted the growth of atrophy as a primary outcome measure.⁸ While data on the incidence of atrophic lesions and growth rates of such lesions in the retrospective study were previously reported,^9,10 we present herein the data derived from AF imaging over a 12-month period of the prospective ProgStar cohort.

Methods

The prospective ProgStar study is a multicenter, observational cohort study conducted at 9 centers in the United States, the United Kingdom, and continental Europe. The study design with inclusion and exclusion criteria has been described in detail previously,⁵ and therefore we focus here on key points relevant to AF imaging analysis. Eligible patients had to have at least 2 disease-causing variants in ABCA4; however, patients with 1 variant could be enrolled, as long as they had a clinical phenotype typical for STGD1. Further inclusion criteria were a minimum age at the first visit of 6 years or older, a willingness to undergo examinations every 6 months for a 2-year period, and the ability to undergo and perform all examinations. Patients needed to have a well-demarcated lesion of atrophy measuring at least 300 μm and less than 5 standard disc areas (equal to 12 mm²). The main exclusion criterion was previous or current participation in any interventional study to treat STGD1. The schedule consisted of a baseline visit and 4 planned follow-up visits every 6 months (with a time window for each visit of ±5 weeks). Relevant patient data including age at enrollment, sex, race, smoking history, and vitamin A supplementation (alone or in multivitamins) were collected. In addition, full-field electroretinograms (ERG) obtained according to International Society for Clinical Electrophysiology of Vision standards¹¹ were recorded once at the baseline visit, or results were submitted if examinations were performed within 5 years of the baseline visit or during follow-up. Electroretinograms were evaluated by the local principal investigators in comparison with the locally healthy cohort established at each of the participating centers. Scotopic and/or photopic responses were graded as abnormal when amplitudes were reduced or implicit times were delayed.

This analysis used data from the prospective ProgStar study (ClinicalTrials.gov identifier: NCT01977846), which was approved by the Western institutional review board, local institutional review boards, and the Human Research Protection Office of the United States Army Medical Research and Materiel Command. Written informed consent was obtained from each participant or their representative prior to enrollment in the study.

Image Acquisition

The AF imaging protocol in the prospective ProgStar study resulted from a number of considerations.⁵ To prevent possible confounding effects on disease progression by serial imaging in this longitudinal study, short-wavelength, reduced-illuminance autofluorescence imaging created by reducing laser power, as proposed by Cideciyan et al,¹² was implemented in the study design. The detailed acquisition protocol was previously published.⁵ The use of this approach compared with conventional AF imaging with respect to grading results was evaluated in a pilot study, and comparable results were revealed.¹³

Grading of Atrophic Lesions on Fundus Autofluorescence

The grading protocols applied in the retrospective ProgStar studies were used as previously described in the grading of AF images.^5,9,13,14,15 Additional details are available in eMethods 1 in the Supplement.

Qualitative and Quantitative Parameters

Qualitative parameters (as previously published^9,10,13) included background heterogeneity, presence of flecks, increased AF at the lesion edge, and the number of lesions of definitely decreased autofluorescence (DDAF). A semiautomated software tool (RegionFinder [Heidelberg Engineering]) was used for quantitatively grading atrophic lesions on AF images, and 2 distinct types of decreased autofluorescence (DAF) were quantified: the level of darkness of an area of DAF was defined qualitatively as definite or questionable, based on its appearance in comparison with blood vessels or the optic nerve head (a reference point for the 100% level of darkness) and the retinal background seen in the periphery as the opposite reference point (0% blackness; Figure 1). The term definitely decreased autofluorescence was defined for areas in which the level of darkness was at least 90% in reference to the optic nerve head, while regions with levels between 50% and 90% darkness were termed questionably decreased AF (QDAF; Figure 1).

Figure 1. — A, A lesion of definitely decreased autofluorescence (7.87 mm²) at baseline. B, The same eye after 12 months; the lesion is enlarged to 8.48 mm². C, A lesion of questionably decreased autofluorescence at baseline (2.45 mm²). D, The same eye after 12 months, with the lesion enlarged to 2.90 mm². Red indicates an excluded area without definitely decreased autofluorescence.

Statistical Methods

Statistical methods are provided in eMethods 2 in the Supplement. Linear models with generalized estimating equations were used to estimate the associations of baseline DAF lesion areas with participant characteristics. Longitudinally, linear mixed models with time as the independent variable were used to estimate the yearly change for each outcome. The models include random effects for the intercept and the slope for time, which take into account the potential correlations between eyes and between repeated measurements of the same eye. The rate of lesion area change associated with each variable was first estimated in an univariate analysis. Multivariate analysis was further run by including variables that were significantly associated with the rate of area change with P values less than .10 in univariate analyses.

Exploratory inspection of lesion growth over time showed a strong dependency on lesion size at the first visit in the retrospective cohort of ProgStar.⁵ For both DDAF and total DAF lesion area, stratified analyses by lesion size at the first visit were performed for eyes with small lesions (ie, ≤1.90 mm²), eyes with intermediate lesions (>1.9-5.0 mm²), and eyes with large lesions (>5.0 mm²). All analyses were conducted using SAS version 9.3 (SAS Institute), and P values for 2-sided tests are reported, with those less than .05 considered significant.

Results

A total of 489 eyes of 259 participants (including 230 individuals [88.8%] who were examined in both eyes) were enrolled in the prospective ProgStar study between October 21, 2013, and January 30, 2015. Their mean (SD) age at first visit was 33.3 (15.1) years; 118 (54.4%) were female. The eTable in the Supplement further summarizes the patient characteristics and demographics at the baseline visit.

The AF images were gradable for 480 eyes at the baseline visit. (An image was not available for 1 eye, 5 eyes had ungradable images, and 1 AF image for another eye was captured without following the study protocol.) Of these, AF images were gradable for 447 eyes at the 6-month visit (after excluding 3 ungradable images) and 455 eyes (after excluding 4 ungradable images) at the 12-month visit.

Characteristics of Eyes With DDAF

At the baseline visit, a DDAF lesion was present in 306 eyes (62.3%), with a mean (SD) area of 3.93 (4.37) mm². Flecks were present in 285 eyes and absent in 13 eyes. There was no difference in mean lesion size between the groups. Mean lesion size did also not differ between eyes with unifocal or multifocal lesions. (In eyes with multifocal lesions, this lesion size was the sum of all DDAF lesions.) Eyes with flecks present outside the arcades had significantly larger lesions at baseline (absent, 2.65 [95% CI, 1.91-3.40] mm²; present, 4.81 [95% CI, 3.89-5.73] mm²; P < .001), as did eyes with a heterogenous background (homogenous, 2.58 [95% CI, 1.87-3.29] mm²; heterogenous, 4.97 [95% CI, 4.03-5.92] mm²; P < .001; Table 1). Further baseline characteristics regarding ERG responses (normal, 3.07 [95% CI, 2.40-3.74] mm²; abnormal, 4.75 [95% CI, 3.58-5.92] mm²; P = .02) and nonsignificant differences in contiguity of DDAF lesions, smoking history, and use of vitamin A supplementation of these eyes are summarized in Table 1.

Table 1. Association Between Baseline Characteristics and Areas of Definitely Decreased Autofluorescence and Total Area of the Lesions.

Characteristic	Definitely Decreased Autofluorescence at First Visit			Definitely and/or Questionably Decreased Autofluorescence, Combined
Characteristic	Patients, No. (%)	Area, Mean (95% CI), mm²	P Value^a	Patients, No. (%)	Total Area, Mean (95% CI), mm²	P Value^b
Eyes, No.	306	NA	NA	480	NA	NA
Demographics
Age at baseline, y
<18	47 (15.4)	3.18 (2.22-4.14)	.005	83 (17.3)	4.14 (3.12-5.16)	.003
≥18-<50	194 (63.4)	3.14 (2.48-3.80)		318 (66.2)	3.57 (3.04-4.11)
≥50	65 (21.2)	6.72 (4.86-8.59)		79 (16.5)	6.72 (5.13-8.31)
Age at onset of symptoms, y^c
<18	130 (42.5)	3.34 (2.58-4.10)	.12	204 (42.5)	3.92 (3.26-4.59)	.36
≥18	153 (50.0)	4.37 (3.33-5.41)	.12	241 (50.2)	4.39 (3.63-5.16)	.36
Duration of onset of symptoms, y
≤2	15 (5.3)	1.87 (0.49-3.25)	.13	52 (11.6)	1.80 (1.10-2.50)	<.001
>2-5	37 (13.0)	4.30 (2.19-6.40)		86 (19.1)	3.35 (2.23-4.48)
>5	233 (81.7)	3.94 (3.21-4.68)		311 (69.3)	4.75 (4.12-5.38)
Sex
Male	136 (55.6)	3.57 (2.92-4.21)	.30	267 (55.6)	3.84 (3.26-4.41)	.17
Female	170 (44.4)	4.20 (3.18-5.21)	.30	213 (44.4)	4.51 (3.74-5.29)	.17
Qualitative autofluorescence grading parameters
Flecks
Absent	13 (4.3)	3.65 (2.68-4.61)	.51	39 (8.1)	3.24 (2.37-4.10)	.02
Present	285 (93.1)	3.98 (3.32-4.65)		424 (88.3)	4.37 (3.84-4.90)
Questionable/ ungradable	8 (2.6)	NA		17 (3.6)	NA
Flecks beyond the arcades^d
Absent	124 (40.8)	2.65 (1.91-3.40)	<.001	254 (53.6)	2.81 (2.32-3.29)	<.001
Present	179 (58.9)	4.81 (3.89-5.73)	<.001	219 (46.2)	5.81 (4.99-6.64)	<.001
Questionable/ ungradable	1 (0.3)	NA	NA	1 (0.2)	NA	NA
Increased autofluorescence at DDAF lesion edge
Absent	182 (59.5)	4.08 (3.37-4.78)	.81	250 (52.1)	4.43 (3.83-5.03)	.41
Present	82 (26.8)	3.90 (2.51-5.30)	.81	159 (33.1)	4.04 (3.18-4.91)	.41
Questionable/ ungradable	42 (13.7)	NA	NA	71 (14.8)	NA	NA
Background
Homogenous	134 (43.8)	2.58 (1.87-3.29)	<.001	274 (57.1)	2.71 (2.24-3.18)	<.001
Heterogenous	172 (56.2)	4.97 (4.03-5.92)	<.001	206 42.9)	6.11 (5.27-6.95)	<.001
No. of lesions of definitely decreased autofluorescence
Unifocal	233 (76.1)	3.93 (3.29-4.57)	.95	233 (48.5)	5.28 (4.66-5.91)	<.001^b
Multifocal	73 (23.9)	3.90 (2.97-4.83)		73 (15.2)	5.28 (4.36-6.20)
Not present	NA	NA		174 (36.3)	2.19 (1.80-2.58)
Other
Vitamin A supplementation
Yes	39 (12.7)	6.10 (3.59-8.62)	.07	64 (13.3)	5.81 (3.99-7.64)	.06
No	267 (87.3)	3.61 (2.99-4.22)	.07	416 (86.7)	3.96 (3.47-4.46)	.06
Smoking
Never	211 (68.9)	3.49 (2.78-4.19)	.12	353 (73.5)	3.88 (3.33-4.43)	.05
Former	55 (18.0)	5.52 (3.77-7.27)		68 (14.2)	4.06 (2.67-5.46)
Current	40 (13.1)	4.13 (2.21-6.05)		59 (12.3)	6.00 (4.49-7.52)
Full-field electroretinogram^e
Normal	178 (61.8)	3.07 (2.40-3.74)	.02	302 (66.5)	3.44 (2.92-3.97)	.001
Abnormal^f	110 (38.2)	4.75 (3.58-5.92)	.02	152 (33.5)	5.33 (4.35-6.32)	.001

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Abbreviations: DDAF, definitely decreased autofluorescence; NA, not applicable.

^{^a}

Comparisons between subgroups.

^{^b}

P value indicates testing for any difference among groups.

^{^c}

Unknown for 21 patients, of whom 2 were asymptomatic (with definitely decreased autofluorescence); unknown for 31 patients, of whom 4 were asymptomatic (with respect to the total area of questionably decreased autofluorescence).

^{^d}

The presence of flecks outside the arcades was assessed using information derived from clinical examinations.

^{^e}

Not performed at baseline or not available in 24 eyes.

^{^f}

Not known for 2 eyes.

Characteristics of Eyes With Any Lesion

The mean (SD) area lesion size of QDAF lesions was 4.07(4.04) mm². Flecks were present in 424 eyes (88.3%) and absent in 39 eyes (8.1%), and eyes with flecks present had larger lesions than eyes without any flecks (absent, 3.24 [95% CI, 2.37-4.10] mm²; present, 4.37 [95% CI, 3.84-4.90] mm²; P = .02); eyes with flecks beyond the arcades also had larger lesions than eyes without flecks (absent, 2.81 [95% CI, 2.32-3.29] mm²; present, 5.81 [95% CI, 4.99-6.64] mm²; P < .001; Table 1). Additional characteristics at baseline in eyes with any lesions of DAF are also summarized in Table 1.

Rates of Lesion Progression

In eyes presenting with DDAF at baseline, the rate of DDAF growth was 0.76 (95% CI, 0.54-0.97) mm² per year (P < .001). However, growth rates were dependent on initial lesion size (Figure 2): the estimated growth rate in eyes with small lesion sizes (≤1.90 mm²) was 0.40 (95% CI, 0.16-0.64) mm² per year; it was 0.72 (95% CI, 0.44-0.99) mm² per year in intermediate-sized DDAF lesions (>1.90-5 mm²) and 1.41 (95% CI, 1.10-1.73) mm² per year in large lesions (>5.0 mm²; Table 2). The estimated difference in the rate of DDAF growth was 0.31 (95% CI, −0.05 to 0.68) mm² per year (P = .09) between eyes with smaller lesions and those with intermediate-sized DDAF lesions and 1.01 (95% CI, 0.62-1.40) mm² per year (P < .001) between eyes with small and large lesions.

Figure 2. — Estimated growth rates of lesions of definitely decreased autofluorescence are shown as overall growth rates (A) and subgroups of lesion size at baseline: small lesions (≤1.90 mm²) (B); intermediate-sized lesions (>1.90-5 mm²) (C), and large lesions (>5.0 mm²) (D).

Table 2. Estimates of Yearly Growth Rates for Definitely Decreased Autofluorescence and the Total Area by Baseline Lesion Size and Baseline Characteristics in Univariate Analysis and Multivariate Analysis, After Adjusting for Initial Lesion Size.

Baseline Characteristic	Definitely Decreased Autofluorescence (95% CI), mm²/y					Definitely and Questionably Decreased Autofluorescence (95% CI), mm²/y
	Estimated Progression Rate per Univariate Analysis	Estimated Rate Difference in Progression per Univariate Analysis		Estimated Rate Difference in Progression per Multivariate Analysis^a		Estimated Progression Rate per Univariate Analysis	Rate Difference per Univariate Analysis		Rate Difference per Multivariate Analysis^a
	Estimated Progression Rate per Univariate Analysis	Rate	P Value	Rate	P Value	Estimated Progression Rate per Univariate Analysis	Rate	P Value	Rate	P Value
Overall size, mm²
≤1.90	0.40 (0.16-0.64)	0.31 (−0.05 to 0.68)	.09	0.18 (−0.20 to 0.57)	.34	0.29 (0.10-0.48)	0.32 (0.05-0.59)	.02	0.14 (−0.37 to 0.65)	.53
>1.9-≤5.0	0.72 (0.44-0.99)	0.31 (−0.05 to 0.68)	.09	0.18 (−0.20 to 0.57)	.34	0.61 (0.43-0.80)	0.32 (0.05-0.59)	.02	0.14 (−0.37 to 0.65)	.53
>5.0	1.41 (1.10-1.73)	1.01 (0.62-1.40)^b	<.001^b	0.78 (0.36-1.20)^b	<.001^b	1.17 (0.94-1.39)^b	0.87 (0.58-1.17)^b	<.001^b	0.49 (−0.06 to 1.05)^b	.08^b
Age at baseline, y
<18	0.71 (0.17-1.24)	−0.07 (−0.67 to 0.53)	.82	NA	NA	0.55 (0.22-0.88)	0.01 (−0.36 to 0.38)	.95	NA	NA
18-50	0.64 (0.37-0.91)	−0.07 (−0.67 to 0.53)	.82	NA	NA	0.56 (0.39-0.74)	0.01 (−0.36 to 0.38)	.95	NA	NA
≥50	1.13 (0.67-1.59)	0.43 (−0.28 to 1.14)^c	.24^c	NA	NA	1.02 (0.68-1.36)	0.47 (−0.01 to 0.94)^c	.05^c	NA	NA
Age at onset of symptoms, y
<18	0.57 (0.25-0.90)	0.24 (−0.20 to 0.69)	.28	NA	NA	0.68 (0.36-0.99)	0.18 (−0.25 to 0.61)	.42	NA	NA
≥18	0.82 (0.51-1.13)	0.24 (−0.20 to 0.69)	.28	NA	NA	0.86 (0.56-1.15)	0.18 (−0.25 to 0.61)	.42	NA	NA
Duration of onset of symptoms, y
≤2	1.06 (0.11-2.02)	− 0.38 (−1.53 to 0.77)	.51	NA	NA	1.01 (0.10-1.93)	−0.16 (−1.27 to 0.95)	.78	NA	NA
>2-5	0.68 (0.04-1.33)	− 0.38 (−1.53 to 0.77)	.51	NA	NA	0.85 (0.23-1.47)	−0.16 (−1.27 to 0.95)	.78	NA	NA
>5	0.71 (0.46-0.96)	−0.35 (−1.33 to 0.63)^d	.48^d	NA	NA	0.77 (0.53-1.01)	−0.24 (−1.19 to 0.70)	.61	NA	NA
Definitely decreased autofluorescence lesions, No.
Unifocal	0.60 (0.36-0.84)	0.66 (0.16-1.15)	.01	0.62 (0.24-1.00)	.001	0.64 (0.41-0.88)^e	0.63 (0.15-1.11)	.01	0.55 (0.13 to 0.97)	.01
Multifocal	1.26 (0.82-1.69)	0.66 (0.16-1.15)	.01	0.62 (0.24-1.00)	.001	1.28 (0.86-1.70)^e	0.63 (0.15-1.11)	.01	0.55 (0.13 to 0.97)	.01
Flecks beyond the arcades
Absent	0.47 (0.14-0.81)	0.47 (0.04-0.91)	.03	0.12 (−0.34 to 0.58)	.61	0.42 (0.23-0.61)	0.49 (0.21-0.78)	<.001	0.23 (−0.28 to 0.74)	.38
Present	0.95 (0.67-1.23)	0.47 (0.04-0.91)	.03	0.12 (−0.34 to 0.58)	.61	0.91 (0.70-1.12)	0.49 (0.21-0.78)	<.001	0.23 (−0.28 to 0.74)	.38
Increased autofluorescence at lesion edge
Absent	0.82 (0.55-1.10)	−0.13 (−0.63 to 0.36)	.60	NA	NA	0.73 (0.53-0.92)	−0.22 (−0.53 to 0.09)	.17	NA	NA
Present	0.69 (0.28-1.10)	−0.13 (−0.63 to 0.36)	.60	NA	NA	0.51 (0.27-0.75)	−0.22 (−0.53 to 0.09)	.17	NA	NA
Questionable^f	0.59 (0.00-1.17)	−0.23 (−0.88 to 0.41)^f	.47^f	NA	NA	0.62 (0.25-0.98)	− 0.11 (−0.53 to 0.30)^f	.60^f	NA	NA
Background heterogeneity
Homogenous	0.45 (0.14-0.77)	0.56 (0.13-0.99)	.01	0.20 (−0.27 to 0.66)	.40	0.51 (0.21-0.82)	0.53 (0.11-0.94)	.01	0.16 (−0.36 to 0.69)	.54
Heterogenous	1.02 (0.73-1.31)	0.56 (0.13-0.99)	.01	0.20 (−0.27 to 0.66)	.40	1.04 (0.76-1.32)	0.53 (0.11-0.94)	.01	0.16 (−0.36 to 0.69)	.54
Vitamin A use
No	0.72 (0.49-0.95)	0.40 (−0.36 to 1.16)	.31	NA	NA	0.62 (0.47-0.77)	0.13 (−0.34 to 0.60)	.59	NA	NA
Yes	1.12 (0.40-1.84)	0.40 (−0.36 to 1.16)	.31	NA	NA	0.75 (0.31-1.19)	0.13 (−0.34 to 0.60)	.59	NA	NA
Smoking
Never	0.65 (0.41-0.92)	0.37 (−0.20 to 0.94)	.20	NA	NA	0.58 (0.42-0.74)	0.27 (−0.13 to 0.67)	.19	NA	NA
Former	1.04 (0.53-1.54)	0.37 (−0.20 to 0.94)	.20	NA	NA	0.85 (0.48-1.22)	0.27 (−0.13 to 0.67)	.19	NA	NA
Current^g	0.65 (0.02-1.28)	−0.02 (−0.70 to 0.67)^g	.96^g	NA	NA	0.63 (0.19-1.08)	0.05 (−0.42 to 0.53)^g	.82^g	NA	NA
Electroretinograms
Normal	0.62 (0.34-0.90)	0.33 (−0.12 to 0.79)	.15	NA	NA	0.58 (0.40-0.76)	0.18 (−0.13 to 0.49)	.26	NA	NA
Abnormal	0.95 (0.59-1.31)	0.33 (−0.12 to 0.79)	.15	NA	NA	0.76 (0.50-1.01)	0.18 (−0.13 to 0.49)	.26	NA	NA

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Abbreviation: NA, not applicable.

^{^a}

After adjusting for initial lesion size in variables associated with lesion growth rate in univariate analysis at significance level of less than or equal to .10.

^{^b}

Rate difference between eyes with lesions of 1.90 mm² or less and those with lesions of more than 5.0 mm².

^{^c}

Rate difference between eyes of patients younger than 18 years and older than 50 years at baseline visit.

^{^d}

Rate difference between eyes of patients with onset of symptoms less than 2 years ago and those with symptom onset more than 5 years ago.

^{^e}

Growth rates based on contiguity of definitely decreased area within the total area lesion of decreased autofluorescence.

^{^f}

Rate difference between eyes with questionable vs absent increased autofluorescence at the lesion edge.

^{^g}

Rate difference between eyes of those who currently smoke and those who have never smoked.

The growth rate of total DAF lesion size overall was 0.64 (95% CI, 0.50-0.78) mm² per year. However, this varied significantly with initial lesion size (Figure 3): for small lesions, the rate was 0.29 (95% CI, 0.10-0.48) mm² per year; for intermediate-sized lesions, the rate was 0.61 (95% CI, 0.43-0.80) mm² per year; and for large lesions, the rate was 1.17 (95% CI, 0.94-1.39) mm² per year (Table 2).

Figure 3. — Overall growth rates (A), with subgroups according to lesion size at baseline: small lesions (≤1.90 mm²) (A); intermediate-sized lesions (>1.90-5 mm²) (B), and large lesions (>5.0 mm²) (C).

The DDAF and total DAF growth rates were estimated for different subgroups. There were no significant differences in estimated progression rate based on demographic features, including age at baseline, age at onset of symptoms, duration of disease at baseline, smoking status, or vitamin A supplementation (Table 2). There was also no significant difference between subcohorts with normal vs abnormal full-field ERG responses (Table 2). However, the rates of DDAF and total DAF growth were significantly faster in eyes with flecks beyond the arcades compared with eyes without flecks beyond the arcades (DDAF, 0.47 [95% CI, 0.04-0.91] mm²/y; P = .03; total DAF, 0.49 [95% CI, 0.21-0.78] mm²/y; P < .001) and eyes with heterogenous backgrounds at baseline compared with eyes with homogenous backgrounds (DDAF, 0.56 [95% CI, 0.13-0.99] mm²/y; P = .01; DAF, 0.53 [95% CI, 0.11-0.94] mm²/y; P = .01). In eyes with multifocal DDAF lesions (whether alone or in combination with QDAF) at baseline, those with multifocal lesions had faster growth rates compared with eyes with a unifocal DDAF lesion (alone: unifocal DDAF, 0.60 [95% CI, 0.36-0.84] mm²/y; multifocal DDAF, 1.26 [95% CI, 0.82-1.69] mm²/y; P = .01; combined with QDAF: unifocal DAF, 0.64 [95% CI, 0.41-0.88] mm²; multifocal DAF, 1.28 [95% CI, 0.86-1.70] mm²; P = .01; Table 2).

After applying multivariate models and adjusting for initial lesion size, the difference in growth rates were no longer significant between eyes for absent or present flecks outside the arcades (estimated differences in rate progression: DDAF, 0.09 [95% CI, −0.36 to 0.55; P = .69]; DAF, 0.12 [95% CI, −0.26 to 0.50]; P = .62) and between eyes with homogenous and heterogeneous background (estimated differences in rate progression: DDAF, 0.17 [95% CI, −0.28 to 0.63]; P = .46; DAF, 0.19 [95% CI, −0.20 to 0.59]; P = .95). The difference in DDAF growth rates remained significant between eyes with a unifocal lesion of DDAF vs eyes with multifocal lesions of DDAF (estimated rate difference: DDAF, 0.61 [95% CI, 0.23-0.98]; P = .001) mm²/y; DAF, 0.54 [95% CI, 0.12-0.96] mm²/y; P = .01).

Incidence of DDAF Lesion From Baseline to 12 Months’ Visit

There were 174 eyes without any DDAF lesions at baseline, of which 161 (of 163) eyes had gradable images at month 12. At month 12, 43 of 161 eyes (26.7%) had a new DDAF lesion observed, with a mean (SD) lesion size of 1.02 (1.70) mm².

Discussion

ProgStar is, to our knowledge, the first international, multicenter study to evaluate the natural history of STGD1 prospectively and was designed as a hybrid study with a retrospective review of medical records and/or a prospective follow-up of patients.⁵ In this article, we report on ProgStar’s primary outcome measure: namely, the prospective growth rate as determined by AF. Because the lesion growth rate is also characterized by loss of photoreceptors, it is considered a surrogate end point for vision loss.⁸ The estimation of growth rates in STGD1 using AF was first proposed by Chen et al,¹⁶ who observed a mean (SD) rate of 0.94 (0.87) mm² per year, and then in multiple reports originating from single centers that suggested a wide range of growth rates, from 0.45 mm² per year (in 67 patients [range, 0.06-4.37 mm²/y for different subgroups])¹⁴ to 1.58 mm² per year (range, 0.13-5.27 mm²/y).¹⁷ Of note, all these studies only assessed lesions corresponding to DDAF lesions. The grading protocols of ProgStar also included the grading of QDAF lesions in addition to DDAF lesions, especially as these may represent early stages of disease and may still be rescuable by gene augmentation therapy or pharmacotherapy, for example.^2,3

Additionally, short-wavelength, reduced-illuminance autofluorescence imaging was applied in a multicenter setting for the first time. Accumulation of N-retinylidene-N-retinyethanolamine and lipofuscin are believed to be cytotoxic, resulting in dysfunction and cell death of the retinal pigment epithelium (RPE) and photoreceptors. One mechanism is the mediation through blue light–induced damage to RPE cells by photooxidative damage,^13,18,19 and an increased rate of lipofuscin accumulation and/or its toxicity could be triggered by the high-intensity and short-wavelength excitation light used in conventional AF imaging.¹² A recent comprehensive simulation of photooxidative stress in the RPE in vivo suggested that lipofuscin granules have a 3-fold higher oxygen uptake and light absorption in patients with STGD1 than age-matched control individuals, with the RPE being at increased risk of photooxidative stress, which is amplified by exposure during short-wavelength autofluorescence imaging.²⁰ Furthermore, ophthalmic imaging equipment operates safely below retinal light-damage thresholds; however, those thresholds are mainly based on unaffected retinas, while diseased retinas may have lower light-damage thresholds.^12,20

One of the key findings of the analysis of the retrospective medical records review in 215 patients was that growth rates were strongly dependent on initial lesion size and taking into account initial size when reporting progression rates (in mm² per year) is important.¹⁰ As previously reported, 145 of 259 patients enrolled in the prospective study had already been followed up retrospectively. Hence, mean (SD) lesion size at baseline in the retrospective study (DDAF, 2.2 [2.7] mm²; DAF, 2.6 [2.8] mm²) was smaller than in the prospective study (DDAF, 3.92 [4.38] mm²; DAF, 4.09 [4.04] mm²). This may be the reason that the estimated mean progression (DDAF, 0.67 [95% CI, 0.44-0.90] mm²/y; DAF, 0.62 [95% CI, 0.47-0.76] mm²/ year) was greater in the prospective than in the retrospective study (DDAF, 0.51 [95% CI, 0.42-0.61] mm²/y; DAF, 0.35 [95% CI, 0.28-0.43] mm²/ year). One possible explanation could be that a larger initial lesion would have a larger surface area for further growth and thus had a larger rate of growth.

Previous studies from single centers reported slower progression rates for eyes with a homogenous background, although these were not stratified for initial lesion size.^14,17 A report on the progression of geographic atrophy secondary to AMD showed that the mean change in lesion size from baseline to month 12 was significantly larger in patients who had eyes with multifocal atrophic spots compared with those with unifocal spots,⁷ in keeping with these results on patients with STGD1. There may be shared pathways of both diseases, such as photooxidative stress caused by RPE bisretinoid accumulation and possible links to light exposure in both STGD1 and AMD.²¹ However, STGD1 and AMD clearly differ in atrophy progression, which was recently found to be significantly faster in AMD compared with late-onset STGD1 (ie, cases in which patients are at least 45 years old at self-reported symptom onset).²²

A previous study included electrophysiological assessment and suggested faster progression in patients with abnormal ERGs at baseline; however, the study cohort was very small and did not include genotypic confirmation.¹⁷ We could not detect a significant difference in progression rates between eyes with normal and abnormal responses in full-field ERG, although there was a significant difference in lesion size at baseline; however, there was a numerically higher but nonsignificant faster progression rates in eyes with abnormal ERGs. One possible explanation for this difference with previous work is that ProgStar has some bias, based on its inclusion criteria⁵: to be able to track lesion growth by AF, the maximum lesion size was set to be less than 12 mm², which inevitably lead to the exclusion of eyes with more severe types of STGD1 both genotypically and phenotypically.

This investigation did not analyze genotypes and rates of progression in part because ABCA4 is a large, complex gene with approximately 1000 disease-causing variants currently reported. Future studies appear warranted regarding a proper genotype-phenotype correlation on progression rates.

The use of vitamin A has potential detrimental effects in patients with disease-causing ABCA4 mutations, at least based on results derived from animal research.^23,24 However, 37 of 250 patients (14.3%) took vitamin A in addition to their usual nutrition at baseline; this was surprising, because literally all study investigators advised patients not to take vitamin A supplements. Although we could see a trend toward a faster progression rate in DDAF lesions, this was not significant over a 12-month period.

Limitations

One limitation is the recording of vitamin A intake because a general nutrition diary that would document entire vitamin A intake was beyond the limits of this natural history study. This might be of relevance for upcoming treatment trials for compounds interacting with vitamin A metabolism, however.^2,3,25

Smoking has been associated with a myriad of negative ocular effects.²⁶ Recently, subclinical nicotine induced foveal changes in the absence of clinically apparent foveal toxicity in healthy young people who smoked.²⁷ In the limited number of individuals who formerly or currently smoke in this cohort, we did not detect a significant difference in growth rate, at least over the 12-month period. Future studies might potentially explore the possible detrimental outcomes of smoking further.

One essential difference between the retrospective and the prospective study has been the mean observational period. Whereas in the retrospective study, it was 3.9 (1.6) years (range, 0.7-12.1 years), we report herein a follow-up period of 12 months. However, 43 of 161 eyes (26.7%) without a lesion at baseline developed at least 1 DDAF lesion over these 12 months. In the retrospective study, the median time to develop DDAF lesions was 4.9 (95% CI, 4.3-5.6) years, and by 3.0 years, 24% had developed such a lesion.⁹ This difference in incidence of DDAF lesions can be attributed to the different observational period and the difference in inclusion criteria.

This report provides data on structural changes over a 1-year period, and we cannot determine at this time whether the structural changes correlate with functional changes, such as best-corrected visual acuity and microperimetry-derived retinal light sensitivity.^{28,29,30,31,32} Furthermore, the outcome of genetic variants on disease progression will be explored over a 2-year period.

Conclusions

In conclusion, AF is a suitable tool to track disease progression in STGD1, especially of DDAF lesions. It may be used in interventional trials that aim to slow down disease progression.

Supplement.

eMethods 1. Grading of atrophic lesions on fundus autofluorescence

eMethods 2. Statistical methods

eReferences.

eTable. Demographic characteristics at baseline visit of patients in the prospective ProgStar study

eAppendix. ProgStar study team

Click here for additional data file.^{(281.4KB, pdf)}

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19.Boulton M, Dontsov A, Jarvis-Evans J, Ostrovsky M, Svistunenko D. Lipofuscin is a photoinducible free radical generator. J Photochem Photobiol B. 1993;19(3):201-204. doi: 10.1016/1011-1344(93)87085-2 [DOI] [PubMed] [Google Scholar]
20.Teussink MM, Lambertus S, de Mul FF, et al. . Lipofuscin-associated photo-oxidative stress during fundus autofluorescence imaging. PLoS One. 2017;12(2):e0172635. doi: 10.1371/journal.pone.0172635 [DOI] [PMC free article] [PubMed] [Google Scholar]
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22.Lindner M, Lambertus S, Mauschitz MM, et al. ; Foveal sparing Atrophy Study Team (FAST) . Differential disease progression in atrophic age-related macular degeneration and late-onset Stargardt disease. Invest Ophthalmol Vis Sci. 2017;58(2):1001-1007. doi: 10.1167/iovs.16-20980 [DOI] [PubMed] [Google Scholar]
23.Sparrow JR, Gregory-Roberts E, Yamamoto K, et al. . The bisretinoids of retinal pigment epithelium. Prog Retin Eye Res. 2012;31(2):121-135. doi: 10.1016/j.preteyeres.2011.12.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Radu RA, Yuan Q, Hu J, et al. . Accelerated accumulation of lipofuscin pigments in the RPE of a mouse model for ABCA4-mediated retinal dystrophies following vitamin A supplementation. Invest Ophthalmol Vis Sci. 2008;49(9):3821-3829. doi: 10.1167/iovs.07-1470 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Charbel Issa P, Barnard AR, Herrmann P, Washington I, MacLaren RE. Rescue of the Stargardt phenotype in Abca4 knockout mice through inhibition of vitamin A dimerization. Proc Natl Acad Sci U S A. 2015;112(27):8415-8420. doi: 10.1073/pnas.1506960112 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Galor A, Lee DJ. Effects of smoking on ocular health. Curr Opin Ophthalmol. 2011;22(6):477-482. doi: 10.1097/ICU.0b013e32834bbe7a [DOI] [PubMed] [Google Scholar]
27.El-Shazly AA, Farweez YA, Elzankalony YA, Elewa LS, Farweez BA. Effect of smoking on macular function and structure in active smokers versus passive smokers. Retina. 2018;38(5):1031-1040. [DOI] [PubMed] [Google Scholar]
28.Strauss RW, Kong X, Bittencourt MG, et al. ; for the SMART Study Group . Scotopic Microperimetric Assessment of Rod Function in Stargardt Disease (SMART) study: design and baseline characteristics (report No. 1). Ophthalmic Res. 2019;61(1):36-43. doi: 10.1159/000488711 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Ervin AM, Strauss RW, Ahmed MI, et al. ; ProgStar Study Group . A workshop on measuring the progression of atrophy secondary to stargardt disease in the ProgStar studies: findings and lessons learned. Transl Vis Sci Technol. 2019;8(2):16. doi: 10.1167/tvst.8.2.16 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Kong X, Fujinami K, Strauss RW, et al. ; ProgStar Study Group . Visual acuity change over 24 months and its association with foveal phenotype and genotype in individuals with Stargardt disease: ProgStar study report No. 10. JAMA Ophthalmol. 2018;136(8):920-928. doi: 10.1001/jamaophthalmol.2018.2198 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Kong X, Strauss RW, Cideciyan AV, et al. ; ProgStar Study Group . Visual acuity change over 12 months in the prospective progression of atrophy secondary to Stargardt disease (ProgStar) study: ProgStar report No. 6. Ophthalmology. 2017;124(11):1640-1651. doi: 10.1016/j.ophtha.2017.04.026 [DOI] [PubMed] [Google Scholar]
32.Schönbach EM, Strauss RW, Kong X, et al. ; ProgStar Study Group . Longitudinal changes of fixation location and stability within 12 months in Stargardt disease: ProgStar report No. 12. Am J Ophthalmol. 2018;193:54-61. doi: 10.1016/j.ajo.2018.06.003 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eMethods 1. Grading of atrophic lesions on fundus autofluorescence

eMethods 2. Statistical methods

eReferences.

eTable. Demographic characteristics at baseline visit of patients in the prospective ProgStar study

eAppendix. ProgStar study team

Click here for additional data file.^{(281.4KB, pdf)}

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[eoi190050r19] 19.Boulton M, Dontsov A, Jarvis-Evans J, Ostrovsky M, Svistunenko D. Lipofuscin is a photoinducible free radical generator. J Photochem Photobiol B. 1993;19(3):201-204. doi: 10.1016/1011-1344(93)87085-2 [DOI] [PubMed] [Google Scholar]

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[eoi190050r22] 22.Lindner M, Lambertus S, Mauschitz MM, et al. ; Foveal sparing Atrophy Study Team (FAST) . Differential disease progression in atrophic age-related macular degeneration and late-onset Stargardt disease. Invest Ophthalmol Vis Sci. 2017;58(2):1001-1007. doi: 10.1167/iovs.16-20980 [DOI] [PubMed] [Google Scholar]

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[eoi190050r32] 32.Schönbach EM, Strauss RW, Kong X, et al. ; ProgStar Study Group . Longitudinal changes of fixation location and stability within 12 months in Stargardt disease: ProgStar report No. 12. Am J Ophthalmol. 2018;193:54-61. doi: 10.1016/j.ajo.2018.06.003 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Progression of Stargardt Disease as Determined by Fundus Autofluorescence Over a 12-Month Period

Rupert W Strauss, MD

Xiangrong Kong, PhD

Alexander Ho, BSE

Anamika Jha, MBS

Sheila West, PhD

Michael Ip, MD

Paul S Bernstein, MD, PhD

David G Birch, PhD

Artur V Cideciyan, PhD

Michel Michaelides, MD

José-Alain Sahel, MD

Janet S Sunness, MD

Elias I Traboulsi, MD, MeEd

Eberhart Zrenner, MD

Sean Pitetta, BS

Dennis Jenkins, MPH

Amir Hossein Hariri, MD

SriniVas Sadda, MD

Hendrik P N Scholl, MD, MA

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Image Acquisition

Grading of Atrophic Lesions on Fundus Autofluorescence

Qualitative and Quantitative Parameters

Figure 1. Examples of Progression of Lesions of Definitely Decreased Autofluorescence and Questionably Decreased Autofluorescence.

Statistical Methods

Results

Characteristics of Eyes With DDAF

Table 1. Association Between Baseline Characteristics and Areas of Definitely Decreased Autofluorescence and Total Area of the Lesions.

Characteristics of Eyes With Any Lesion

Rates of Lesion Progression

Figure 2. Estimated Growth Rates of Lesions of Definitely Decreased Autofluorescence.

Table 2. Estimates of Yearly Growth Rates for Definitely Decreased Autofluorescence and the Total Area by Baseline Lesion Size and Baseline Characteristics in Univariate Analysis and Multivariate Analysis, After Adjusting for Initial Lesion Size.

Figure 3. Estimated Growth Rates of Lesions of Definitely Decreased Autofluorescence Plus Questionably Decreased Autofluorescence Combined.

Incidence of DDAF Lesion From Baseline to 12 Months’ Visit

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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