Neovascular glaucoma as a chronic neuroischemic optic neuropathy: the impact of cumulative burden on vision-related quality of life in a 36-month prospective study

Abstract

Purpose. To evaluate the impact of treatment burden as a functional marker of chronic neuroischemic optic neuropathy progression on vision-related quality of life in patients with neovascular glaucoma. Methods. This prospective cohort study included 351 patients (351 eyes) with secondary neovascular glaucoma associated with proliferative diabetic retinopathy or retinal vein occlusion. Patients were followed for 36 months. Vision-related quality of life was assessed using the validated NEI VFQ-25 questionnaire at baseline, 12 months, and 36 months. Cumulative Burden Index (CBI) was defined as a composite cumulative measure incorporating both treatment intensity (number of transscleral cyclophotocoagulation (TSCPC) procedures) and disease-related burden (severity of complications present at baseline and during follow-up). Statistical analysis included descriptive statistics, linear and logistic regression, ROC analysis, and multilayer perceptron (MLP) neural network modeling. Results. Patients with successful treatment outcomes (n = 282; 80.3%) demonstrated improvement in vision-related quality of life (ΔQoL = +10.26 ± 6.18), whereas patients with resistant disease (n = 69; 19.7%) showed significant deterioration (ΔQoL = −7.43 ± 6.97; p < 0.001). Higher CBI values were independently associated with lower NEI VFQ-25 scores (β = −1.78; 95% CI −2.57 to −0.99; p < 0.001). The between-group difference corresponded to a very large clinical effect size (Cohen’s d = 2.77). In the logistic regression model, CBI remained an independent predictor of unfavorable treatment outcome (OR = 0.48; 95% CI 0.34–0.68; p < 0.001). The neural network model demonstrated good discriminative performance for outcome prediction (AUC = 0.83; 95% CI 0.78–0.88). Conclusions. The CBI was independently associated with vision-related quality of life in patients with neovascular glaucoma and may serve as an integrated marker of chronic neurovascular disease burden. Increased CBI values were associated with significant functional impairment and a poorer clinical prognosis. Integration of composite clinical indices with machine learning approaches may improve risk stratification, personalized treatment planning, and digital clinical decision support in patients with neovascular glaucoma.