Visual Acuity Change Over 24 Months and Its Association With Foveal Phenotype and Genotype in Individuals With Stargardt Disease: ProgStar Study Report No. 10 | Genetics and Genomics | JAMA Ophthalmology | JAMA Network
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Figure.  Best-Corrected Visual Acuity (BCVA) by Fovea Involvement and Genotype
Best-Corrected Visual Acuity (BCVA) by Fovea Involvement and Genotype

A, Boxplots of BCVA showing the distributions of BCVA by fovea point lesion involvement status. B, Boxplots of baseline BCVA by genotype. In each boxplot, the lower and upper boundary of the box represents the first quartile (ie, 25th percentile) and the third quartile (ie, 75th percentile) of the data, respectively; the horizontal black line in the box is the median; the open circle in the box is the mean; the lower and upper whiskers are the lowest and highest values of the data that are not outliers. Any circle outside the whiskers is an outlier (ie, the data value is greater than 1.5 interquartile ranges away from the first and third quartiles). AF indicates autofluorescence; DDAF, definitely decreased AF; and QDAF, questionably decreased AF.

Table 1.  Genotype and Baseline Characteristics of Participants and Study Eyes of the Prospective ProgStar Study
Genotype and Baseline Characteristics of Participants and Study Eyes of the Prospective ProgStar Study
Table 2.  Cross-sectional Comparisons of Baseline Best-Corrected Visual Acuity (logMAR) by Foveal Phenotype and Participant Genotype
Cross-sectional Comparisons of Baseline Best-Corrected Visual Acuity (logMAR) by Foveal Phenotype and Participant Genotype
Table 3.  Rates of Visual Acuity Change (logMAR/y) by Participant Characteristics
Rates of Visual Acuity Change (logMAR/y) by Participant Characteristics
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Original Investigation
August 2018

Visual Acuity Change Over 24 Months and Its Association With Foveal Phenotype and Genotype in Individuals With Stargardt Disease: ProgStar Study Report No. 10

Author Affiliations
  • 1School of Public Health and Health Sciences, University of Massachusetts-Amherst, Amherst
  • 2Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
  • 3Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland
  • 4Laboratory of Visual Physiology, Division for Vision Research, National Institute of Sensory Organs, National Hospital Organization, Tokyo Medical Center, Tokyo, Japan
  • 5Department of Ophthalmology, Keio University, School of Medicine, Tokyo, Japan
  • 6Moorfields Eye Hospital, London, United Kingdom
  • 7UCL Institute of Ophthalmology, University College London, London, United Kingdom
  • 8Department of Ophthalmology, Johannes Kepler University (Clinic) Linz, Linz, Austria
  • 9Department of Ophthalmology, Medical University Graz, Graz, Austria
  • 10Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia
  • 11Foundation Fighting Blindness, Clinical Research Institute, Columbia, Maryland
  • 12Department of Ophthalmology, University of Basel, Basel, Switzerland
  • 13Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
JAMA Ophthalmol. 2018;136(8):920-928. doi:10.1001/jamaophthalmol.2018.2198
Key Points

Question  Is best-corrected visual acuity an appropriate outcome measure for treatment trials in Stargardt disease?

Findings  In this multicenter longitudinal cohort study (the ProgStar Study), the mean rate of best-corrected visual acuity loss was clinically small at 0.55 letters per year during 2 years. The rate varied by baseline best-corrected visual acuity and by fovea phenotype (defined as fovea with normal, increased, questionably decreased, or definitely decreased autofluorescence).

Meaning  For trials of Stargardt disease with 2 years of duration, it may be difficult to show efficacy using best-corrected visual acuity as an end point owing to its slow rate of change over this time.

Abstract

Importance  Limited data from prospective studies are available to understand the natural history of ABCA4-related Stargardt disease (STGD1). Such data are important for determining appropriate outcome measures for future STGD1 trials.

Objective  To estimate the rate of loss of best-corrected visual acuity (BCVA) during 2 years and to estimate the associations of BCVA loss with foveal phenotype and genotype in patients with STGD1.

Design, Setting, and Participants  This multicenter prospective cohort study included 259 participants (489 study eyes) with molecularly confirmed STGD1 who were 6 years or older. The participants were enrolled at 9 centers in the United States and Europe and were followed up every 6 months for 2 years.

Exposures  Baseline BCVA and presence and type of foveal lesion (determined via fundus autofluorescence images) and genotype (classified into 4 groups based on the number and pathogenicity of ABCA4 mutations).

Main Outcomes and Measures  Rate of BCVA change per year.

Results  The mean (SD) age was 33 (15) years. Of 259 the participants, 141 (54%) were female, and 222 (85%) were white. The overall rate of BCVA loss was 0.55 (95% CI, 0.20-0.90) letters per year during the 2 years. Eyes with baseline BCVA worse than 20/200 showed an improvement of 0.65 (95% CI, 0.1-1.2) letters per year. At baseline, the mean BCVA for eyes without foveal lesion was 20/32, and their BCVA change rate over time was 0.1 (95% CI, −1.2 to 1.35) letters per year (P = .89). Eyes with a foveal lesion but having BCVA of 20/70 or better at baseline lost BCVA at a rate of 3 (95% CI, 1.5-4.4) letters per year (P < .001). Genotype was neither associated with baseline BCVA nor with the rate of BCVA change during the follow-up.

Conclusions and Relevance  A clinically small BCVA loss was observed during 2 years, and the change rate varied depending on baseline BCVA. Eyes without lesion in the fovea had better BCVA at baseline and showed minimal change of BCVA throughout 2 years. Eyes with no or modest acuity impairment but with a foveal lesion at baseline had the fastest loss rate. For trials of STGD1 with 2 years of duration, it may be difficult to show efficacy using BCVA as an end point owing to its slow rate of change over this time.

Introduction

Stargardt disease (STGD1; OMIM: 248200) is the most common juvenile macular dystrophy.1 It is inherited as an autosomal-recessive trait associated with mutations in the ABCA4 gene,2 and more than 900 disease-associated sequence variants are reported.3 Clinically, STGD1 is characterized by fundus flecks in the retinal pigment epithelium and by macular atrophic lesions. Visual acuity (VA) in individuals with STGD1 often deteriorates progressively in a nonlinear fashion,4-9 with a faster rate of loss at the early stage when a degree of foveal vision is still present. Some patients may present with a fovea sparing phenotype in which the fovea is not involved with any lesion initially, and such patients may maintain relatively good VA for decades.3,9

Currently there is no approved treatment for STGD1. The international multicenter Progression of Atrophy Secondary to Stargardt Disease (ProgStar) Study aimed to understand the natural history of disease progression to help determine appropriate outcome measures for future treatment trials.3,10-14 Previously, we have reported no significant change of best-corrected VA (BCVA) during a 12-month follow-up in the ProgStar study.6 Herein we reported the rate of BCVA loss throughout 2 years, assessed whether BCVA loss was linear throughout 2 years, and identified associated risk factors. In particular, we estimated the associations of BCVA loss with baseline foveal involvement and with genotype group defined by the pathogenicity and the number of ABCA4 variants detected.

Methods

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.

Details of the prospective ProgStar study have been described elsewhere.14 In brief, participants were enrolled at 9 sites from September 2013 to March 2015. Eligibility criteria included patients 6 years or older, those with 2 pathogenic mutations in the ABCA4 gene, or those with 1 pathogenic mutation in the ABCA4 gene at the time of genetic testing plus a typical Stargardt phenotype.14 Relevant inclusion criteria for the current analysis were study eyes with BCVA of 20 or higher Early Treatment of Diabetic Retinopathy Study letter score (ie, 20/400 Snellen equivalent or better), and at least 1 well-demarcated area of atrophy on fundus autofluorescence (AF) imaging with a diameter of 300 μm or more and the sum of all lesions of 12 mm2 or less. All participants gave written informed consent prior to study enrollment and were followed semiannually for 2 years.

At each visit, refraction and BCVA were obtained following the Early Treatment of Diabetic Retinopathy Study protocol.15 Baseline fovea lesion status was assessed by 2 graders independently (R.W.S. and E.S.) (adjudicated by a third senior grader [M.A.]) using fundus AF images,14,16 and near-infrared reflectance images were referenced for eyes with decreased foveal AF, to tease out the confounding AF decrease due to normal macular pigmentation.17 Then presence of a lesion in the foveal center and type of the lesion (increased AF, definitely decreased AF [DDAF], or questionably decreased AF [QDAF]), as previously described,4 was recorded to define fovea phenotypes.

Data on participant genetic characteristics were abstracted from genetic screening reports. Screenings were conducted for clinical diagnosis between 2000 and 2014, using polymerase chain reaction enrichment–based targeted next-generation sequencing, gene chip array, single-strand conformation polymorphism, or direct sequencing technology. All detected variants were confirmed by direct sequencing in 2016 for the ProgStar study, and their pathogenicity was predicted through in silico analysis. Owing to the large number of ABCA4 variants identified, participants’ genetic characteristics were categorized into 4 groups based on the estimated pathogenicity reported in the literature (as of June 2017) and the number and the severity of the predicted functional impact of the ABCA4 variants (Box).18

Box Section Ref ID
Box.

Genotypes Defined Based on the Pathogenicity, Number, and Severity of the Predicted Functional Impact of Detected ABCA4 Mutationsa

  • Genotype A: Patients with ≥2 severe/null variants.b

  • Genotype B: Patients with 1 severe/null variant and ≥1 variant that are missense or in-frame insertion/deletion.

  • Genotype C: Patients with no severe/null variant, but ≥2 variants that are missense or in-frame insertion/deletion.

  • Genotype D: Patients with 1 missense or in-frame insertion/deletion variant or with only variants predicted as less likely pathogenic or uncertain.

a All variants refer to mutations on the ABCA4 gene.

b Severe/null variants were defined as those that were predicted to affect splicing or to introduce a premature truncating codon in the protein if translated, such as stop, frame shift, intronic variants in splice regions with significant splice site alteration, exonic synonymous variants with significant splice site alteration, or missense variants with significant splice site alteration (eg, nucleotide change at the start/end of exon).

Statistical Analysis

Early Treatment of Diabetic Retinopathy Study letter scores of BCVA were converted to the logMAR scale for analysis. Best-corrected VA was used as a continuous variable and also categorized per the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (Table 1).19

Cross-sectional analysis of baseline data used bivariable linear models with generalized estimating equations to compare BCVA by genotype group and by fovea lesion status. If the variable had a P value of more than .10 in the bivariable model, a multivariable model was built to adjust for factors associated with baseline BCVA identified in our prior report,6 including age at symptom onset, duration of symptoms, presence of retinal pigment epithelium pigmentary abnormality, and presence of flecks outside arcades.

To estimate the longitudinal BCVA change rate (logMAR/y), linear mixed-effects modeling (LMM) with a random intercept was used, accounting for intereye and intraeye correlations. To assess whether BCVA change was linear during a 2-year period, a piecewise LMM was used to compare the BCVA change rate during the first and second year.

To further identify baseline variables associated with the BCVA change rate, LMMs were used by including each variable and its interaction with time. The baseline variables included participant demographics, genotype group, and clinical characteristics, as well as the baseline BCVA level. The univariate association of each variable with the BCVA change rate was first estimated. Adjusted associations were also estimated using multivariable LMMs including variables either associated with BCVA change at P less than .10 or associated with baseline BCVA at P less than .10.

All analyses were conducted in SAS version 9.3 (SAS Institute Inc), and 2-sided P values from Wald tests were reported. For multivariable models, raw P values with no adjustment for multiple comparisons were reported. Model fit was assessed using aggregated residuals for generalized estimating equations models20 and was inspected visually and based on plots of scaled residuals for LMMs.21

Results

The prospective ProgStar study enrolled 259 participants with 489 study eyes. Retention rate was more than 88% at all visits (eFigure 1 in the Supplement). There were 200 sequence ABCA4 variants identified, including 166 variants predicted as likely pathogenic.

Table 1 summarizes genotype, demographics, and baseline clinical characteristics. The median (interquartile range [IQR]) age at baseline was 31 (21-44) years, 141 (54%) were female, and 222 (86%) were white. The median (IQR) age at symptom onset was 19 (12-29) years, and the median (IQR) duration since symptom onset at baseline was 9 (5-15) years. Eight participants (3.1%) were in genotype group A, 98 (37.8%) in group B, 99 (38.2%) in group C, and 54 (20.9%) in group D. In the foveal center, 36 eyes (8%) had no lesion (normal AF), 130 eyes (29%) had DDAF, 260 eyes (58%) had QDAF, and 21 (5%) had increased AF. The median (IQR) BCVA was 41 (35-52) letters (logMAR = 0.88), and 100 eyes (21%) had no or mild impairment, 267 eyes (55%) were moderately impaired, and 122 eyes (25%) were severely impaired.

Cross-sectionally at baseline, compared with eyes without a foveal lesion, eyes with abnormal foveal AF had worse BCVA (Figure, A and Table 2). In adjusted analysis, the mean BCVA for eyes with increased AF, QDAF, and DDAF at the fovea was 0.36 (95% CI, 0.17-0.55), 0.47 (95% CI, 0.38-0.56), and 0.50 (95% CI, 0.40-0.60) logMAR worse than the mean BCVA for eyes without foveal lesion, respectively. Best-corrected VA was not significantly different by genotype group (Figure, B and Table 2).

Longitudinally, during the 2 years, 71 eyes (16.4%) lost 1 or more lines (ie, ≥5 letters) and 16 eyes (3.7%) lost 3 or more lines (≥15 letters). Overall, BCVA declined at a rate of 0.011 logMAR per year (−0.55 letters/y) (95% CI, 0.004-0.018; P = .004). The BCVA change rate was 0.006 logMAR per year (−0.3 letters/y) (95% CI, −0.009 to 0.021) during the first year and 0.015 logMAR per year (−0.75 letters/y) (95% CI, 0-0.031) during the second year. However, the rate difference between the second and the first year (0.009 logMAR/y) was not significant (95% CI, −0.01758 to 0.03592; P = .50).

Table 3 presents the rates of BCVA change by subgroups. The BCVA loss rate differed by baseline BCVA level (eFigure 2 in the Supplement): the rate was 0.025 logMAR per year (−1.3 letters/y) (95% CI, −0.002 to 0.051; P = .07), 0.038 logMAR per year (−1.9 letters/y) (95% CI, 0.025-0.050; P < .001), and 0.012 logMAR per year (−0.6 letters/y) (95% CI, 0.004-0.019; P = .002) in eyes with no VI, mild VI, and moderate VI, respectively. Eyes with severe visual impairment at baseline showed a gain of BCVA (rate = −0.013 logMAR/y [0.65 letters/y]; 95% CI, −0.023 to −0.002; P = .02).

Eyes with normal foveal AF did not have significant BCVA change (rate = 0.002 logMAR/y [−0.2 letters/y]; P = .89) (Table 3 and eFigure 3 in the Supplement). Eyes with a DDAF foveal lesion also showed no significant change (rate = 0.003 logMAR/y [−0.15 letters/y]; P = .62). Eyes with increased foveal AF lost 1 letter per year (rate = 0.020 logMAR/y [−1 letter/y]; P = .23), but it was not statistically significant. The rate of BCVA loss was 0.015 logMAR per year ( −0.8 letters/y) (95% CI, 0.006-0.024; P = .002) in eyes with a QDAF foveal lesion at baseline. After adjusting for baseline BCVA status, the rates of BCVA loss in eyes with QDAF, DDAF, and increased AF foveal lesion were 0.064 logMAR per year (95% CI, 0.020-0.107; P = .004), 0.066 (95% CI, 0.034-0.098; P < .001), and 0.066 (95% CI, 0.032-0.100, P < .001) faster, respectively, than the rate in eyes with normal foveal AF (Table 3).

Considering that a foveal lesion and no or mild visual impairment at baseline were both associated with faster loss of BCVA, a subset analysis was conducted for the eyes with no or mild visual impairment but with abnormal foveal AF at baseline, and the estimated rate of BCVA loss was 0.059 logMAR per year (−3 letters/y) (95% CI, 0.0307-0.088; P < .001).

The rate of BCVA change was not significantly associated with genotype group, age at baseline, sex, or race/ethnicity (Table 3). While age at symptom onset, duration since symptom onset, presence of retinal pigment epithelium pigmentary abnormality, and presence of flecks outside arcades were associated with baseline BCVA,6 they were not associated with BCVA change rate during the 2 years.

Discussion

We previously reported that BCVA did not change significantly during the first year of follow-up in the prospective ProgStar study.6 Over 2 years of follow-up, there was a statistically significant but clinically small loss of BCVA. Prior evidence has suggested that VA loss in STGD1 is not linear,5,6,9 where loss is faster when vision is minimally or mildly impaired despite accompanying retinal degeneration,22-24 followed by slower VA loss after foveal vision is lost and fixation becomes eccentric. In this analysis, the BCVA change rate during the second year more than doubled that during the first year, but the difference in the rate between the 2 years was not statistically different. This suggests that we may not have had the power to detect a nonlinear change of BCVA over 2 years and that using a linear model to describe the change process of BCVA for over 2 years may not be appropriate.

Consistent with our prior findings,4-6 the starting level of VA was predictive of subsequent speed of VA loss. For eyes worse than 20/25 at baseline, the better the starting VA, the faster the VA loss subsequently. For those with VA better than 20/25 at baseline, there was no significant loss of VA over 2 years. This was partly due to the small sample size in this group (n = 17), but it may also be attributable to the greater proportion in this subgroup that had no foveal lesion (eTable in the Supplement). For the subset of eyes with no or mild VA loss (ie, BCVA, ≤20/70) but having foveal lesion involvement, their BCVA loss was approximately 3 letters per year, suggesting patients with STGD1 with such attributes are likely to lose vision more quickly.

Patients with STGD1 with a foveal sparing phenotype often can maintain good VA3,25-27 over a long time. Such clinical observations are supported by our data showing that at baseline, eyes with no lesion in the fovea had much better BCVA than eyes with abnormal AF (Figure, A) and that these eyes had minimal change in VA during the follow-up.

Visual acuity as a measure of central vision highly depends on the intactness of the fovea. This is supported by the dose-response association between foveal lesion status and BCVA (Figure, A), in which eyes with no lesion in the fovea had the best BCVA, followed by eyes with increased AF, QDAF, and DDAF in the fovea. Increased AF is thought to reflect the early stage of pathogenesis in STGD1, which involves accumulation of lipofuscin fluorophores.28 Such accumulation, detectable on AF images as increased intensity, can lead to loss of photoreceptor cells, which were graded in this study into 2 levels: QDAF (ie, partial loss) and DDAF (ie, complete loss).

This analysis of 2-year data estimated a statistically significant rate of BCVA change of 0.011 logMAR per year (ie, 0.55 letters/y), which was slower than the VA loss rate (0.03 logMAR or 1.5 letters/y) estimated from the retrospective ProgStar cohort. The rates in the subgroups of eyes with no impairment (0.025 logMAR/y) or mild impairment at baseline (0.038 logMAR/y) were also slower than the rates of these subgroups in the retrospective cohort (0.096 and 0.094 logMAR/y, respectively).5 These differences are most likely owing to the retrospective cohort having longer and variable follow-up times (range, 1-6 and median, 3.6 years), plus the potential problem of lack of standardization in VA measures in the retrospective study, which were obtained from review of medical records.

Consistent with our prior findings,5,6 we found a clinically small but statistically significant improvement of VA in eyes with severe impairment at baseline (VA worse than 20/200). Measuring vision reliably in this group is difficult, and regression to the mean is likely. The improvement for some eyes could also be a result of change of the location of the preferred retinal locus, as observed in geographic atrophy and inherited macular dystrophies.29-32 In STGD1, fixation stability may improve33 as the preferred retinal locus moves to the parapapillary region while scotoma expands,34 and VA with poor fixation stability may improve once fixation stabilizes. The rate of BCVA improvement over 2 years (0.65 letters/y) was smaller than the rate of improvement that we reported in the first year (2.3 letters/y),6 suggesting with longer time since baseline and more measurements to estimate change, the estimate of improvement becomes more stable and closer to 0.

We did not find any association of genotype with baseline VA or with the VA change rate. Understanding the genotype-phenotype correlation in STGD1 is challenging because of the large number of ABCA4 mutations having been associated with STGD1. In silico analysis predicting the potential impact of each variant on protein functioning is a necessary step for further examining the clinical impact of the genotype. Following prior literature,35 we classified our participants into 4 genotype groups based on the number of mutations identified and their predicted pathogenicity. The prevalence of genotype A, the group for which the pathogenicity of the mutations is best known and expected to have the most severe clinical manifestations, was low (8 [3%]). We found no evidence of differences in VA at baseline by genotype group.

Limitations

The above observations may reflect our imperfect knowledge of the pathogenicity of certain mutations and also the limitations in our genetic data. Additionally, the genotype grouping criteria adopted here are clearly a simplification to summarize the complex genetic profiles of the participants and may not be sensitive enough to capture differences in VA loss over 2 years. A limitation in our genetic data is that the data were abstracted from participants’ genetic screening reports. The screenings occurred during 2000 to 2014 for clinical diagnosis and used different sequencing platforms depending on the clinical center. All detected mutations were confirmed by direct sequencing in 2016 through ProgStar, but because the sensitivity in identifying mutations and the sequencing target regions of ABCA4 had changed over time and varied across platforms, it is still possible that disease-relevant mutations were missed in screening. Additionally, it is also possible that participants carry disease-causing mutations in other genes that were not screened but were associated with Stargardt (eg, ELOVL4, PRPH2, or PROM1).36,37 For example, genotype D participants had a large range of baseline BCVA (Figure, B), suggesting they could carry disease-causing mutations in ABCA4 or other relevant genes, which were not screened in our cohort. These limitations emphasize the importance of considering the enrollment criteria of ProgStar participants when generalizing the results to all patients with Stargardt disease in the population.

Earlier age at symptom onset was associated with worse VA in our cross-sectional analyses5,6 and it was associated with faster VA decline in our ProgStar retrospective cohort.5 However, in our current analysis of the prospective cohort, the VA change rate did not differ significantly by age at symptom onset. This may be because compared with the early-onset cases in the retrospective cohort, the early-onset cases in the prospective cohort had poorer vision at baseline, and thus their VA change was also slower. Moreover, 2 years of follow-up may not be long enough to observe the effect of age of onset on the speed of VA decline.

Conclusions

Although BCVA is an important visual function outcome directly associated with participants’ daily activities38 and is often the primary end point in trials for retinal diseases,39 it is probably not a practical outcome measure for STGD1 treatment trials of 2-year duration given the very small rate of change during the period. For a new therapy or treatment aiming to slow down acuity loss in STGD1, the clinical trial should consider no less than 3 years of follow-up and enroll patients with only moderate loss of VA at the outset to optimize the chance of showing efficacy. Such trials should also be careful in using models with linear assumptions on the change process when estimating efficacy on visual acuity. Although BCVA may not show a clinically significant change over 2 years, this reflects the relatively slow course of the natural history of the disease. Even if a large change may be observed within a structural parameter (eg, increased AF40), the structural change may not be correlated with a functional decline of BCVA. Therefore, it remains important to examine whether and under what situations structural changes entail functional impact in STGD1. The associations of foveal phenotype and current BCVA level with subsequent rate of BCVA change may be also important for future trial designs. Fast progressors in STGD1 (in terms of BCVA) are most likely those who currently have good or mildly impaired acuity but have foveal lesion involved in the eyes. For patients with a relatively intact fovea, other visual function measures (eg, macular sensitivity) may be needed to track their visual function change.

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Article Information

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

Accepted for Publication: April 7, 2018.

Published Online: June 14, 2018. doi:10.1001/jamaophthalmol.2018.2198

Author Contributions: Drs Kong and West had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Dr Kong and Dr Fujinami contributed equally as co–first authors.

Concept and design: Kong, Strauss, Michaelides, Ervin, Schönbach, Scholl.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Kong, Fujinami, Michaelides.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Kong, Munoz, West.

Obtained funding: Strauss, Michaelides, Schönbach, Scholl.

Administrative, technical, or material support: Kong, Fujinami, Strauss, Cideciyan, Michaelides, Ahmed, Ervin, Schönbach, Cheetham, Scholl.

Supervision: Strauss, Michaelides, Scholl.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Kong reports grants from Foundation Fighting Blindness and the National Institute of Allergy and Infectious Diseases during the conduct of the study. Dr Fujinami is a paid consultant of Astellas Pharma US, Inc. Dr Munoz reports grants from Foundation Fighting Blindness during the conduct of the study. Dr Ahmed reports grants from Foundation Fightling Blindness during the conduct of the study. Dr Elvin reports grants from Foundation Fightling Blindness during the conduct of the study. Dr Schönbach reports grants from German National Academy of Sciences during the conduct of the study. Dr Cheetham is a contractor for Foundation Fighting Blindness. Dr Scholl is a paid consultant of Boehringer Ingelheim Pharma KG, Daiichi Sankyo, Gerson Lehrman Group, Guidepoint, and Shire; a member of the Scientific Advisory Board of the Astellas Institute for Regenerative Medicine, GenSight Biologics SA, Intellia Therapeutics, ReNeuron Group Plc/Ora Inc, Vision Medicines; Data Monitoring and Safety Board/Committee of Genentech Inc/F. Hoffmann-La Roche Ltd, and ReNeuron Group Plc/Ora Inc; and is principal investigator of grants at the University of Basel (Universitätsspital Basel, USB) sponsored by Acucela Inc, NightstaRx Ltd, Novelion Therapeutics, Spark Therapeutics, Ltd Grants at USB are negotiated and administered by the institution (USB) that receives them on its proper accounts. These arrangements have been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. Johns Hopkins University and Bayer Pharma AG have an active research collaboration and option agreement. These arrangements have also been reviewed and approved by the USB in accordance with its conflict of interest policies. Individual investigators who participate in the sponsored project(s) are not directly compensated by the sponsor but may receive salary or other support from the institution to support their effort on the project(s). No other disclosures are reported.

Funding/Support: The ProgStar studies are supported by the Foundation Fighting Blindness Clinical Research Institute (FFB CRI) and a grant to FFB CRI by the US Department of Defense USAMRMC TATRC (grants W81-XWH-07-1-0720 and W81XWH-09-2-0189).

Role of the Funder/Sponsor: The funder oversaw the design and conduct of the study. The funder had no role in data collection, management, analysis and interpretation of the data nor in preparation of the manuscript and in decision to submit the manuscript for publication. The funder reviewed and approved the manuscript.

The ProgStar Study Group: The ProgStar study is supported by a contract from the Foundation Fighting Blindness. The ProgStar Study Group members are as follows: 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, MS; Nikki Burgnoni, MS; Greater Baltimore Medical Center, Towson: Janet S. Sunness, MD; Carol Applegate, MLA, COT; Leslie Russell, MAc; Moorfields Eye Hospital, London, England: Michel Michaelides, MD; Simona Degli Esposti, MD; Anthony Moore, MD; 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, PhD; 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, MS; Karine Girard-Claudon, MST; Hilary Swann, BSc; Avani Rughani, BSc; Charles Amoah, NVQ; Dominic Carrington, BS; Kanom Bibi, BSc; Emerson Ting Co, DMD; Mohamed Nafaz Illiyas, BS; Hamida Begum, BSc; Andrew Carter, BSc; Anne Georgiou, PhD; Selma Lewis, 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, Texas: 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, BS; Susanne Kramer, Dipl. Biol.; 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: Sheila K. West, PhD; Ann-Margret Ervin, PhD; Beatriz Munoz, MS; Kong Kong, PhD; Kurt Dreger, BS; Jennifer Jones, BA; Robert Burke, BA; Doheny Image Reading Center: 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; and Monika Smith, HS.

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