Cargando…
A model to quantify the influence of treatment patterns and optimize outcomes in nAMD
Neovascular age-related macular degeneration (nAMD) is a progressive retinal disease that often leads to severe and permanent vision loss. Early initiation of anti-vascular endothelial growth factor (anti-VEGF) therapy has been shown to preserve vision in nAMD patients. Concurrently, treatment outco...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857272/ https://www.ncbi.nlm.nih.gov/pubmed/35181697 http://dx.doi.org/10.1038/s41598-022-06362-w |
_version_ | 1784654006952394752 |
---|---|
author | Ziemssen, Focke Agostini, Hansjürgen Feltgen, Nicolas Finger, Robert P. Haritoglou, Christos Hoerauf, Hans Iwersen, Matthias Porstner, Martina Clemens, Andreas Gmeiner, Benjamin |
author_facet | Ziemssen, Focke Agostini, Hansjürgen Feltgen, Nicolas Finger, Robert P. Haritoglou, Christos Hoerauf, Hans Iwersen, Matthias Porstner, Martina Clemens, Andreas Gmeiner, Benjamin |
author_sort | Ziemssen, Focke |
collection | PubMed |
description | Neovascular age-related macular degeneration (nAMD) is a progressive retinal disease that often leads to severe and permanent vision loss. Early initiation of anti-vascular endothelial growth factor (anti-VEGF) therapy has been shown to preserve vision in nAMD patients. Concurrently, treatment outcomes in real-world are inferior to those reported in clinical trials. The most likely reasons observed are fewer treatment-intensity in routine clinical practice than in clinical trials. The other possibility could be the delay in starting treatment and the re-treatment interval. Although a negative impact of aforementioned parameters seems obvious, quantitative impact measures remain elusive in a real-world setting due to a lack of an ‘optimal treatment’ control group. To overcome this shortcoming, we developed, validated, and applied a model to assess and quantify the impact of anti-VEGF administration variables on visual acuity development in a prospective nAMD patient cohort. The model was further applied to probe the impact of the COVID-19 pandemic on visual progressions in nAMD patients. The presented model paves the way to systematically explore and evaluate realistic interventions in the current treatment paradigm, that can be adopted in routine clinical care. |
format | Online Article Text |
id | pubmed-8857272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88572722022-02-22 A model to quantify the influence of treatment patterns and optimize outcomes in nAMD Ziemssen, Focke Agostini, Hansjürgen Feltgen, Nicolas Finger, Robert P. Haritoglou, Christos Hoerauf, Hans Iwersen, Matthias Porstner, Martina Clemens, Andreas Gmeiner, Benjamin Sci Rep Article Neovascular age-related macular degeneration (nAMD) is a progressive retinal disease that often leads to severe and permanent vision loss. Early initiation of anti-vascular endothelial growth factor (anti-VEGF) therapy has been shown to preserve vision in nAMD patients. Concurrently, treatment outcomes in real-world are inferior to those reported in clinical trials. The most likely reasons observed are fewer treatment-intensity in routine clinical practice than in clinical trials. The other possibility could be the delay in starting treatment and the re-treatment interval. Although a negative impact of aforementioned parameters seems obvious, quantitative impact measures remain elusive in a real-world setting due to a lack of an ‘optimal treatment’ control group. To overcome this shortcoming, we developed, validated, and applied a model to assess and quantify the impact of anti-VEGF administration variables on visual acuity development in a prospective nAMD patient cohort. The model was further applied to probe the impact of the COVID-19 pandemic on visual progressions in nAMD patients. The presented model paves the way to systematically explore and evaluate realistic interventions in the current treatment paradigm, that can be adopted in routine clinical care. Nature Publishing Group UK 2022-02-18 /pmc/articles/PMC8857272/ /pubmed/35181697 http://dx.doi.org/10.1038/s41598-022-06362-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Ziemssen, Focke Agostini, Hansjürgen Feltgen, Nicolas Finger, Robert P. Haritoglou, Christos Hoerauf, Hans Iwersen, Matthias Porstner, Martina Clemens, Andreas Gmeiner, Benjamin A model to quantify the influence of treatment patterns and optimize outcomes in nAMD |
title | A model to quantify the influence of treatment patterns and optimize outcomes in nAMD |
title_full | A model to quantify the influence of treatment patterns and optimize outcomes in nAMD |
title_fullStr | A model to quantify the influence of treatment patterns and optimize outcomes in nAMD |
title_full_unstemmed | A model to quantify the influence of treatment patterns and optimize outcomes in nAMD |
title_short | A model to quantify the influence of treatment patterns and optimize outcomes in nAMD |
title_sort | model to quantify the influence of treatment patterns and optimize outcomes in namd |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857272/ https://www.ncbi.nlm.nih.gov/pubmed/35181697 http://dx.doi.org/10.1038/s41598-022-06362-w |
work_keys_str_mv | AT ziemssenfocke amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT agostinihansjurgen amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT feltgennicolas amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT fingerrobertp amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT haritoglouchristos amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT hoeraufhans amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT iwersenmatthias amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT porstnermartina amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT clemensandreas amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT gmeinerbenjamin amodeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT ziemssenfocke modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT agostinihansjurgen modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT feltgennicolas modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT fingerrobertp modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT haritoglouchristos modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT hoeraufhans modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT iwersenmatthias modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT porstnermartina modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT clemensandreas modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd AT gmeinerbenjamin modeltoquantifytheinfluenceoftreatmentpatternsandoptimizeoutcomesinnamd |