Predictive Role of Complete Blood Count-Derived Inflammation Indices and Optical Coherence Tomography Biomarkers for Early Response to Intravitreal Anti-VEGF in Diabetic Macular Edema

<b>Background:</b> Diabetic macular edema (DME) is the leading cause of vision impairment in diabetic patients, with intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections being the first-line therapy. However, one-third of patients exhibit persistent DME despite treatment, suggesting additional pathogenic factors. This study aimed to evaluate the predictive value of complete blood count (CBC)-based inflammation indexes and optical coherence tomography (OCT) parameters in determining early anti-VEGF treatment effectiveness in DME. <b>Methods:</b> One hundred and four naïve patients with DME, treated with 0.05 mL of intravitreal aflibercept were retrospectively analyzed. Blood parameters analyzed included neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). Baseline OCT biomarkers included subretinal fluid (SRF), intraretinal cysts (IRC), hyperreflective retinal spots (HRS), and disorganization of retinal inner layers (DRIL). Treatment response was defined as a minimum 10% reduction in central macular thickness (CMT) at one month post-injection. <b>Results:</b> NLR, MLR, PLR, and SII were significantly higher in non-responders (<i>p</i> < 0.001), but their predictive value was fair, with an area under the ROC curve ranging between 0.704 (MLR) and 0.788 (SII). A multivariate model including SII, initial CMT, and the presence of IRC showed an excellent prediction value for early anatomical response (AUC ROC of 0.911). At the same time, lower PLR, DRIL, SRF, and the absence of HRF were correlated with early gain in BCVA. <b>Conclusions:</b> CBC-derived inflammation indices and OCT biomarkers have prognostic value in predicting early response to anti-VEGF therapy in DME in terms of functional and anatomical outcomes. These findings could help identify poor responders and guide personalized treatment strategies.