Background

Each inherited retinal disorder is rare, but together, they affect millions of people worldwide. No treatment is currently available for these blinding diseases, but promising new options-including gene therapy-are emerging. Arguably, the most prevalent retinal dystrophy is Stargardt disease. In each case, the specific combination of ABCA4 variants (> 900 identified to date) and modifying factors is virtually unique. It accounts for the vast phenotypic heterogeneity including variable rates of functional and structural progression, thereby potentially limiting the ability of phase I/II clinical trials to assess efficacy of novel therapies with few patients. To accommodate this problem, we developed and validated a sensitive and reliable composite clinical trial endpoint for disease progression based on structural measurements of retinal degeneration.

Methods and findings

We used longitudinal data from early-onset Stargardt patients from the Netherlands (development cohort, n = 14) and the United Kingdom (external validation cohort, n = 18). The composite endpoint was derived from best-corrected visual acuity, fundus autofluorescence, and spectral-domain optical coherence tomography. Weighting optimization techniques excluded visual acuity from the composite endpoint. After optimization, the endpoint outperformed each univariable outcome, and showed an average progression of 0.41° retinal eccentricity per year (95% confidence interval, 0.30-0.52). Comparing with actual longitudinal values, the model accurately predicted progression (R2, 0.904). These properties were largely preserved in the validation cohort (0.43°/year [0.33-0.53]; prediction: R2, 0.872). We subsequently ran a two-year trial simulation with the composite endpoint, which detected a 25% decrease in disease progression with 80% statistical power using only 14 patients.

Conclusions

These results suggest that a multimodal endpoint, reflecting structural macular changes, provides a sensitive measurement of disease progression in Stargardt disease. It can be very useful in the evaluation of novel therapeutic modalities in rare disorders.