Magliano DJ, Boyko EJ, editors. IDF Diabetes Atlas. 11th ed. Brussels (Belgium): International Diabetes Federation; 2025.

Antonetti DA, Klein R, Gardner TW. Diabetic retinopathy. N Engl J Med. 2012;366(13):1227–39. https://doi.org/10.1056/NEJMra1005073.

Article  CAS  PubMed  Google Scholar 

Zhu H, Li B, Huang T, et al. Update in the molecular mechanism and biomarkers of diabetic retinopathy. Biochim Biophys Acta Mol Basis Dis. 2025;1871(5):167758. https://doi.org/10.1016/j.bbadis.2025.167758.

Article  CAS  PubMed  Google Scholar 

Stielow M, Fijalkowski L, Alaburda A, et al. SGLT2 inhibitors: from molecular mechanisms to clinical outcomes in cardiology and diabetology. Molecules. 2025;30(15):3112. https://doi.org/10.3390/molecules30153112.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Seidu S, Alabraba V, Davies S, et al. SGLT2 inhibitors—the new standard of care for cardiovascular, renal and metabolic protection in type 2 diabetes: a narrative review. Diabetes Ther. 2024;15(5):1099–124. https://doi.org/10.1007/s13300-024-01550-5.

Article  PubMed  PubMed Central  Google Scholar 

O’Hara DV, Jardine MJ. A review of the safety of sodium–glucose co-transporter-2 inhibitors. Diabetes Obes Metab. 2025;27(7):3598–606. https://doi.org/10.1111/dom.16385.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xu B, Kang B, Tang F, et al. Association between sodium–glucose cotransporter 2 inhibitors and eye disorders: a systematic review and meta-analysis. Expert Rev Clin Pharmacol. 2024. https://doi.org/10.1080/17512433.2024.2399073.

Article  PubMed  Google Scholar 

Ma Y, Lin C, Cai X, et al. The association between the use of sodium–glucose cotransporter 2 inhibitor and the risk of diabetic retinopathy and other eye disorders: a systematic review and meta-analysis. Expert Rev Clin Pharmacol. 2022;15(7):877–86. https://doi.org/10.1080/17512433.2022.2102973.

Article  PubMed  Google Scholar 

Zhou B, Shi Y, Fu R, et al. Relationship between SGLT-2i and ocular diseases in patients with type 2 diabetes mellitus: a meta-analysis of randomized controlled trials. Front Endocrinol (Lausanne). 2022;13:907340. https://doi.org/10.3389/fendo.2022.907340.

Article  PubMed  Google Scholar 

Li C, Zhou Z, Neuen BL, et al. Sodium–glucose co-transporter-2 inhibition and ocular outcomes in patients with type 2 diabetes: a systematic review and meta-analysis. Diabetes Obes Metab. 2021;23(1):252–7. https://doi.org/10.1111/dom.14197.

Article  CAS  PubMed  Google Scholar 

Malyszczak A, Przezdziecka-Dolyk J, Szydelko-Pasko U, et al. Novel antidiabetic drugs and the risk of diabetic retinopathy: a systematic review and meta-analysis of randomized controlled trials. J Clin Med. 2024;13(6):1797. https://doi.org/10.3390/jcm13061797.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tang H, Li G, Zhao Y, et al. Comparisons of diabetic retinopathy events associated with glucose-lowering drugs in patients with type 2 diabetes mellitus: a network meta-analysis. Diabetes Obes Metab. 2018;20(5):1262–79. https://doi.org/10.1111/dom.13232.

Article  CAS  PubMed  Google Scholar 

Tan L, Wang Z, Okoth K, et al. Associations of antidiabetic drugs with diabetic retinopathy in people with type 2 diabetes: an umbrella review and meta-analysis. Front Endocrinol (Lausanne). 2024;14:1303238. https://doi.org/10.3389/fendo.2023.1303238.

Article  PubMed  Google Scholar 

Barkhordari S, Ghaffariyan S, Banei F, et al. The association between the utilization of SGLT2 inhibitors and diabetic retinopathy: a systematic review and meta-analysis of cohort studies. J Nephropharmacol. 2024;13(2):e12688. https://doi.org/10.34172/npj.2024.12688.

Article  CAS  Google Scholar 

Liang L, Yu L, He Y, et al. Sodium–glucose cotransporter 2 inhibitors and risk of diabetic retinopathy: systematic review and meta-analysis. Can J Ophthalmol. 2025. https://doi.org/10.1016/j.jcjo.2025.08.009.

Article  PubMed  Google Scholar 

Goodarzi S, Soltani Abhari F, Azarinoush G, et al. SGLT2 inhibitors for delaying diabetic retinopathy: a systematic review and meta-analysis. Int Ophthalmol. 2025;45(1):406. https://doi.org/10.1007/s10792-025-03768-z.

Article  PubMed  Google Scholar 

Sadeghi E, Rahmanipour E, Valsecchi N, et al. An update on ocular effects of antidiabetic medications. Surv Ophthalmol. 2025. https://doi.org/10.1016/j.survophthal.2025.01.010.

Article  PubMed  Google Scholar 

Ntentakis DP, Correa V, Ntentaki AM, et al. Effects of newer-generation anti-diabetics on diabetic retinopathy: a critical review. Graefes Arch Clin Exp Ophthalmol. 2024;262(3):717–52. https://doi.org/10.1007/s00417-023-06236-5.

Article  PubMed  Google Scholar 

Rajagopal R, McGill JB. Novel agents in the management of diabetes and risk of worsening diabetic retinopathy. Retina. 2024;44(11):1851–9. https://doi.org/10.1097/IAE.0000000000004252.

Article  PubMed  Google Scholar 

Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019;366:l4898. https://doi.org/10.1136/bmj.l4898.

Article  PubMed  Google Scholar 

McGuinness LA, Higgins JPT. Risk-of-bias VISualization (robvis): an R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021;12(1):55–61. https://doi.org/10.1002/jrsm.1411.

Article  PubMed  Google Scholar 

Papakonstantinou T, Nikolakopoulou A, Higgins JPT, et al. CINeMA: software for semiautomated assessment of the confidence in the results of network meta-analysis. Campbell Syst Rev. 2020;16(1):e1080. https://doi.org/10.1002/cl2.1080.

Article  PubMed  PubMed Central  Google Scholar 

Nikolakopoulou A, Higgins JPT, Papakonstantinou T, et al. CINeMA: an approach for assessing confidence in the results of a network meta-analysis. PLoS Med. 2020;17(4):e1003082. https://doi.org/10.1371/journal.pmed.1003082.

Article  PubMed  PubMed Central  Google Scholar 

Dankers M, Nelissen-Vrancken M, Hart BH, et al. Alignment between outcomes and minimal clinically important differences in the Dutch type 2 diabetes mellitus guideline and healthcare professionals’ preferences. Pharmacol Res Perspect. 2021;9(3):e00750. https://doi.org/10.1002/prp2.750.

Article  PubMed  PubMed Central  Google Scholar 

Chiocchia V, Nikolakopoulou A, Higgins JPT, et al. ROB-MEN: a tool to assess risk of bias due to missing evidence in network meta-analysis. BMC Med. 2021;19(1):304. https://doi.org/10.1186/s12916-021-02166-3.

Article  PubMed  PubMed Central  Google Scholar 

Ortiz-Seller A, Martorell P, Barranco H, et al. Comparison of different agents and doses of anti-vascular endothelial growth factors (aflibercept, bevacizumab, conbercept, ranibizumab) versus laser for retinopathy of prematurity: a network meta-analysis. Surv Ophthalmol. 2024;69(4):585–605. https://doi.org/10.1016/j.survophthal.2024.02.005.

Article  PubMed  Google Scholar 

Morris T, Nevill J, Nevill C, et al. Network meta-regression including baseline risk analysis and interactive visualizations as implemented by the MetaInsight web application. J Clin Epidemiol. 2025;184:111839. https://doi.org/10.1016/j.jclinepi.2025.111839.

Article  PubMed  Google Scholar 

Achana FA, Cooper NJ, Dias S, et al. Extending methods for investigating the relationship between treatment effect and baseline risk from pairwise meta-analysis to network meta-analysis. Stat Med. 2013;32(5):752–71. https://doi.org/10.1002/sim.5539.

Article  PubMed  Google Scholar 

Pedder H. MBNMAdose: dose-response model-based network meta-analysis. The Comprehensive R Archive Network; 2022. https://doi.org/10.5281/zenodo.8221452. Accessed 06 Nov 2025.

Ortiz-Seller A, Martorell P, Rosello P, et al. Comparison of different doses of oral and ocular propranolol for retinopathy of prematurity: a network meta-analysis. Paediatr Drugs. 2024;26(5):499–518. https://doi.org/10.1007/s40272-024-00647-5.

Article  PubMed  PubMed Central  Google Scholar 

Dias S, Sutton AJ, Welton NJ, et al. NICE DSU technical support document 3: heterogeneity: subgroups, meta-regression, bias and bias-adjustment. Sheffield (UK): National Institute for Health and Clinical Excellence, University of Bristol, Decision Support Unit, ScHARR, University of Sheffield; 2011.

Araki E, Tanizawa Y, Tanaka Y, et al. Long-term treatment with empagliflozin as add-on to oral antidiabetes therapy in Japanese patients with type 2 diabetes mellitus. Diabetes Obes Metab. 2015;17(7):665–74. https://doi.org/10.1111/dom.12464.