Emmanuel Eric Pazo

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

Fuhua Yang, Yi Gong, Xiaoying Pan, Jinzhi Zhao, Rongguo Yu, Liangzhang Tan, Emmanuel Eric Pazo, Xiaomin Zhang, Xiaorong Li

Eye and Vision, 2026 · article · doi:10.1186/s40662-026-00479-z · Open access (CC BY)

Retina & vascular imagingAI & deep learning

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.

Keywords: diabetic macular edema; anti-VEGF therapy; aqueous humor cytokines; predictive biomarkers; treatment response prediction; angiogenesis; angiopoietin-2; interleukin-6

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How to cite

Yang, F., Gong, Y., Pan, X., Zhao, J., Yu, R., Tan, L., Pazo, E. E., Zhang, X., Li, X. (2026). Development of a predictive model based on aqueous cytokines data for response to anti-VEGF therapy in diabetic macular edema. Eye and Vision. https://doi.org/10.1186/s40662-026-00479-z

@article{yang2026development,
  title = {{Development of a predictive model based on aqueous cytokines data for response to anti-VEGF therapy in diabetic macular edema}},
  author = {Yang, Fuhua and Gong, Yi and Pan, Xiaoying and Zhao, Jinzhi and Yu, Rongguo and Tan, Liangzhang and Pazo, Emmanuel Eric and Zhang, Xiaomin and Li, Xiaorong},
  journal = {Eye and Vision},
  year = {2026},
  doi = {10.1186/s40662-026-00479-z},
  url = {https://doi.org/10.1186/s40662-026-00479-z},
}

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