The study adhered to the tenets of the Declaration of Helsinki and received institutional ethics committee approval (KY2025-133-01). Written informed consent for data use was obtained from all participants. The study followed STROBE guidelines for observational research and incorporated key items from the RECORD checklist (Supplementary File 1).
Database query and patient screening algorithm
An initial digital screening of the hospital’s electronic medical record (EMR) system was performed to identify potential participants treated between January 2021 and December 2023. A query algorithm based on ICD-10 diagnostic codes for Type 1 (E10.3) or Type 2 (E11.3) diabetes mellitus accompanied by macular edema was utilized.
A certified ophthalmologist conducted manual verification of the identified clinical charts. The presence of center-involved DME was confirmed, which was strictly defined as a central retinal thickness (CRT) ≥ 300 µm on spectral-domain OCT, accompanied by intraretinal or subretinal fluid.
The following exclusion checkpoints were applied during chart review: (1) macular edema secondary to non-diabetic conditions (e.g., retinal vein occlusion) were identified and excluded; (2) eyes with a history of vitreoretinal surgery or active ocular inflammation were excluded; (3) OCT image quality was verified using a quantitative checkpoint of signal strength ≥ 20 (Heidelberg standard); (4) patients with > 20% missing follow-up data were excluded.
A standardized study eye selection rule was implemented for bilateral cases. The eye with the worse baseline best-corrected visual acuity (BCVA) was selected. If BCVA was identical, the eye with the higher CRT was selected. If both parameters were tied, a pre-programmed random number generator was utilized to assign the study eye.
Group allocation and standardized treatment procedures
Group allocation was documented based on clinical records. Patients were categorized into the anti-VEGF group (n = 166) or the non-biologic control group (n = 137). The control group criteria were clearly defined as patients receiving focal/grid laser or observation due to documented medical contraindications, financial constraints, or patient refusal of injections.
Standardized Anti-VEGF Injection Protocol: The pharmacological agents prepared included ranibizumab (0.5 mg / 0.05 mL), aflibercept (2.0 mg / 0.05 mL), or conbercept (0.5 mg / 0.05 mL). Topical anesthesia was administered using proparacaine hydrochloride 0.5%. Antisepsis of the conjunctival sac and eyelids was performed with 5% povidone-iodine. A transscleral injection was performed 3.5 - 4.0 mm from the limbus using a 30-gauge needle in a dedicated sterile room. A “3 + PRN” regimen was executed. Retreatment was triggered if any of the following checkpoints were met: CRT increase ≥ 50 µm, loss of ≥ 5 ETDRS letters, or persistent fluid on OCT.
Standardized Control Interventions: For laser photocoagulation, a 532 nm solid-state laser was utilized. The spot size was set to 50–100 µm and the duration to 0.1 s. Power was titrated to achieve a barely visible, mild white burn. For observation, systemic glycemic and blood pressure regulation were monitored under a standardized endocrinology department protocol.
Longitudinal assessment and image grading workflow
Follow-up visits were organized at 1, 3, 6, 12, and 24 months. Visit tolerance windows of ± 7 days for monthly visits and ± 14 days for annual visits were implemented to ensure data temporal consistency.
BCVA was measured using a standardized retro-illuminated ETDRS chart at a 4 m distance. Controlled room luminance was ensured, and certified technicians masked to the treatment allocation were utilized.
OCT imaging was executed using the Spectralis OCT device. The acquisition protocol was set to a 20° × 20° macular volume scan with 49 continuous B-scans. Automatic Real-Time (ART) mode was enabled with an averaging setting of 9 frames.
A masked grading workflow was implemented, in which two independent specialists manually graded all images. In case of disagreement regarding fluid presence or structural biomarkers, a third senior specialist was involved as an adjudicator to establish consensus.
Advanced statistical implementation workflow
Normality and Descriptive Analysis: Data distribution was tested using the Shapiro-Wilk test. Continuous data were summarized as mean ± SD.
Propensity Score Weighting Procedure: A logistic regression model was constructed to calculate propensity scores. The included covariates were age, sex, diabetes duration, HbA1c, and baseline OCT features. Inverse Probability of Treatment Weighting (IPTW) was implemented using the Average Treatment Effect (ATE) method. As a verification checkpoint, covariate balance was assessed using Standardized Mean Differences (SMD), with robust balance considered achieved if SMD < 0.10.
Mixed-Effects Model Implementation: Longitudinal changes were analyzed using a Mixed-Effects Model for Repeated Measures (MMRM). An unstructured covariance matrix was specified, and a random intercept for each patient was included. The analysis was performed using R software (version 4.2.2) with the WeightIt and cobalt packages.