Machine Learning to Predict Response to Ranibizumab in Neovascular Age-Related Macular Degeneration.

ABSTRACT:

Purpose

Neovascular age-related macular degeneration (nAMD) shows variable treatment response to intravitreal anti-VEGF. This analysis compared the potential of different artificial intelligence (AI)-based machine learning models using OCT and clinical variables to accurately predict at baseline the best-corrected visual acuity (BCVA) at 9 months in response to ranibizumab in patients with nAMD.

Design

Retrospective analysis.

Participants

Baseline and imaging data from patients with subfoveal choroidal neovascularization secondary to age-related macular dengeration.

Methods

Baseline data from 502 study eyes from the HARBOR (NCT00891735) prospective clinical trial (monthly ranibizumab 0.5 and 2.0 mg arms) were pooled; 432 baseline OCT volume scans were included

SUBMITTER: Maunz A 

PROVIDER: S-EPMC10251067 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature