A nomogram based on peripheral blood inflammatory indices and optical coherence tomography biomarkers for early prediction of anti-VEGF response in diabetic macular edema

Clinical relevance The pathogenesis of diabetic macular edema (DME) involves inflammation. Identifying relevant biomarkers can guide more effective treatment strategies.Background This study evaluated peripheral blood indices and optical coherence tomography (OCT) biomarkers in DME patients, constructing a nomogram to predict anti-vascular endothelial growth factor (VEGF) response based on inflammatory features.Methods A total of 140 eyes from 93 DME patients were included in this study. Data on OCT and haematologic parameters were collected. Logistic regression analyses with generalised estimating equations (GEE) identified risk factors for poor visual-functional response to anti-VEGF therapy, and a nomogram was constructed.Results Forty percent (56/140) of the eyes from DME patients exhibited a poor visual-functional response. Multivariate regression analyses with GEE revealed that older age (odds ratio [OR]: 1.07; 95% confidence interval [CI]: 1.07–1.12; p = 0.005), lower best-corrected visual acuity (BCVA) (OR: 0.07; 95% CI: 0.02–0.27; p < 0.001), neutrophil-to-lymphocyte ratio (NLR) > 2.57 (OR: 2.93; 95% CI: 1.93–9.21; p = 0.16), platelet-to-lymphocyte ratio (PLR) > 98.93 (OR: 12.64; 95% CI: 2.17–73.7; p = 0.018), presence of subretinal fluid (SRF) (OR: 3.59; 95% CI: 1.96–13.42; p = 0.034), a greater number of hyperreflective foci (HRF) in the outer retinal layers (OR: 1.31; 95% CI: 1.08–1.6; p = 0.001), and the grading of external limiting membrane integrity (OR: 6.57; 95% CI: 1.71–25.27; p = 0.005) were risk factors for poor response. The nomogram achieved an area under the curve of 0.866. Calibration and Hosmer – Lemeshow tests confirmed the model fit (p = 0.685). Clinical decision curve analysis demonstrated substantial clinical utility.Conclusions An NLR > 2.57 and PLR > 98.93 serve as circulating biomarkers, while SRF and HRF act as imaging biomarkers that can function as inflammatory markers for DME. The nomogram based on these inflammatory features effectively predicts the visual-functional response in DME.