What question did this study set out to answer?

This research aims to identify cytokine biomarkers that predict response to anti-VEGF therapy in diabetic macular edema.

March 14, 2026Eye and Vision0 citationsOpen Access

Development of a predictive model based on aqueous cytokines data for response to anti-VEGF therapy in diabetic macular edema

FYFuhua YangKarlsruhe Institute of Technology YGYi GongTianjin Medical University Eye Hospital XPXiaoying PanNankai University

Key Points

This research aims to identify cytokine biomarkers that predict response to anti-VEGF therapy in diabetic macular edema.
Conducted a luminex assay to measure cytokine levels in aqueous humor
Developed a predictive model using baseline cytokines from a discovery set of responders and non-responders
Validated the model with an additional set and assessed performance using AUC and goodness of fit tests
Baseline cytokines like VEGF, IL-6, Ang-2, MCP-1, and ICAM-1 were significantly elevated in non-responders
The predictive model achieved an AUC of 0.85 in the discovery set and 0.84 in internal validation
Cytokine levels remained elevated in non-responders after anti-VEGF treatment at 6 months

Abstract

Abstract Background Intravitreal anti-vascular endothelial growth factor (VEGF) agents improve visual acuity in diabetic macular edema (DME). However, resistance, non-response, or recurrence occurs in many patients. Predictive biomarkers for anti-VEGF response are lacking. We aim to identify cytokine markers predictive of anti-VEGF response and elucidate cytokines involved in poor-response DME pathogenesis. Methods A luminex assay was carried out to measure the concentration of cytokines in the aqueous humor. A predictive model based on baseline cytokines was constructed in a discovery set that comprised 46 responders and 20 non-responders. In addition, an analysis of baseline cytokines of 15 responders and 12 non-responders was conducted as a validation set. The performance of the nomogram was determined using the area under the receiver operating characteristic curve (AUC) and Hosmer–Lemeshow goodness of fit test. Results Baseline concentrations of angiogenesis-related cytokines VEGF ( P < 0.0001), placenta growth factor (PIGF) ( P < 0.0001), angiopoietin-2 (Ang-2) ( P < 0.0001), inflammatory factor interleukin-6 (IL-6) ( P < 0.0001), IL-8 ( P < 0.0001), chemokine monocyte chemoattractant protein-1 (MCP-1) ( P < 0.0001), and adhesion factor intercellular adhesion molecule-1 (ICAM-1) ( P < 0.001) were significantly increased compared to controls. The prediction nomogram model included five baseline cytokines: VEGF, IL-6, Ang-2, MCP-1, and ICAM-1 were constructed. The AUC for the discovery set was 0.85 (95% CI: 0.74–0.96) and for the internal validation was 0.84, indicating that the prediction model has good predictive accuracy. The Hosmer–Lemeshow goodness of fit test showed good model calibration ( P = 0.295). The levels of Ang-2 ( P = 0.0042), IL-6 ( P < 0.0001), IL-8 ( P < 0.0001), MCP-1 ( P < 0.0001), and PIGF ( P < 0.0001) were still significantly increased at the 6-month timepoint after multiple injections of anti-VEGF drugs for non-response group patients. Conclusion The baseline cytokine-based model helped to assess the individual probability of response to anti-VEGF therapy. There are cytokines beyond VEGF that are involved in the pathogenesis of DME, therapeutic regimens targeting these cytokines may improve the visual acuity and reduce macular edema.

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