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Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease
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 dis...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5371327/ https://www.ncbi.nlm.nih.gov/pubmed/28355279 http://dx.doi.org/10.1371/journal.pone.0174020 |
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author | Lambertus, Stanley Bax, Nathalie M. Fakin, Ana Groenewoud, Joannes M. M. Klevering, B. Jeroen Moore, Anthony T. Michaelides, Michel Webster, Andrew R. van der Wilt, Gert Jan Hoyng, Carel B. |
author_facet | Lambertus, Stanley Bax, Nathalie M. Fakin, Ana Groenewoud, Joannes M. M. Klevering, B. Jeroen Moore, Anthony T. Michaelides, Michel Webster, Andrew R. van der Wilt, Gert Jan Hoyng, Carel B. |
author_sort | Lambertus, Stanley |
collection | PubMed |
description | 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 (R(2), 0.904). These properties were largely preserved in the validation cohort (0.43°/year [0.33–0.53]; prediction: R(2), 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. |
format | Online Article Text |
id | pubmed-5371327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53713272017-04-07 Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease Lambertus, Stanley Bax, Nathalie M. Fakin, Ana Groenewoud, Joannes M. M. Klevering, B. Jeroen Moore, Anthony T. Michaelides, Michel Webster, Andrew R. van der Wilt, Gert Jan Hoyng, Carel B. PLoS One Research Article 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 (R(2), 0.904). These properties were largely preserved in the validation cohort (0.43°/year [0.33–0.53]; prediction: R(2), 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. Public Library of Science 2017-03-29 /pmc/articles/PMC5371327/ /pubmed/28355279 http://dx.doi.org/10.1371/journal.pone.0174020 Text en © 2017 Lambertus et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lambertus, Stanley Bax, Nathalie M. Fakin, Ana Groenewoud, Joannes M. M. Klevering, B. Jeroen Moore, Anthony T. Michaelides, Michel Webster, Andrew R. van der Wilt, Gert Jan Hoyng, Carel B. Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease |
title | Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease |
title_full | Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease |
title_fullStr | Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease |
title_full_unstemmed | Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease |
title_short | Highly sensitive measurements of disease progression in rare disorders: Developing and validating a multimodal model of retinal degeneration in Stargardt disease |
title_sort | highly sensitive measurements of disease progression in rare disorders: developing and validating a multimodal model of retinal degeneration in stargardt disease |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5371327/ https://www.ncbi.nlm.nih.gov/pubmed/28355279 http://dx.doi.org/10.1371/journal.pone.0174020 |
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