Treatment of Neovascular AMD: Artificial Intelligence in Real-world Setting

Overview

The purpose of this study is to implement quantitative assessment tools for the treatment of active neovascular AMD patients in a real-world setting in order to provide advantages for both patients (treatment burden) and healthcare system (scheduling visits/treatments).

Neovascular age-related macular degeneration (nAMD) is a significant burden to health care systems in industrialized countries. Due to its chronic nature, continuous follow-up and treatment is needed to prevent significant loss of visual function in patients with nAMD. Vascular endothelial growth factor (VEGF) plays a major role in the pathomechanisms of nAMD and large multicenter trials have shown that intravitreal application of substances which intercept the VEGF pathway can interrupt the progression of nAMD and improve the visual outcome. As every single injection bears the risk of sight-threatening complications and increases the financial burden to health care providers, several studies have tested different treatment regimens, to decrease the number of applicated injections without compromising the gains in visual acuity. Thereby, strict protocols have been compared to flexible "as needed" regimens (pro re nata, PRN) and regimens with proactive increments of injection intervals (treat and extend, T\&E). Studies have indicated that the outcome of anti-VEGF treatment is better in standardized clinical trials than in so-called "real world settings". This is explained by tight exclusion criteria of sponsored trials, the shorter follow-up time and the small number of patients that are treated per center, resulting in a better standard of care. PRN as well as T\&E management showed disadvantages such as significant less vision gain in PRN and possible over treatment in T\&E. Recently, additional treatment criteria were described to improve the patients care. Advances in diagnostic precision by SD-OCT using automated algorithms to accurately measure fluid volumes in all compartments are solid tools to determine disease activity. They allow to precisely quantifying the impact of therapeutic parameters on disease activity. Multicenter study analyses have shown that the amount of intraretinal fluid has a significant effect on vision outcome. Subretinal fluid or Pigmentepithelial detachment have been described to be less important. These findings were the basis for designing an efficient point-of-care management. Automated quantification of the fluid amount using artificial intelligence (AI) may serve as a reliable and objective method to determine the personalized point-of-care. To prove the efficacy of point-of-care management, prospective studies in real-world settings are required. More data is required to assess the outcome of real-world settings and find ways to improve treatment results, when larger amounts of patients are treated and less resources are available for decision making. The purpose of this study is to implement quantitative assessment tools for the treatment of neovascular AMD patients in a real-world setting in order to provide advantages for both patients (treatment burden) and healthcare system (scheduling visits/treatments).

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Central Contacts