A Meta-Analysis of Intravitreal Ranibizumab versus Laser Photocoagulation for the Treatment of Retinopathy of Prematurity
Bibliographic record
Abstract
PURPOSE: Laser photocoagulation (LPC) has been a traditional treatment for retinopathy of prematurity (ROP). However, intravitreal anti-VEGF agents such as bevacizumab and intravitreal ranibizumab (IVR) have also been increasingly used. This meta-analysis aims to rigorously compare IVR to LPC in the treatment of ROP. DESIGN: Meta-analysis. PARTICIPANTS: One thousand nine hundred forty-seven eyes from 1007 infants were included. METHODS: Medline, Embase, and Cochrane CENTRAL were used to identify studies comparing IVR monotherapy to LPC (PROSPERO ID: CRD42023390855). The primary outcome was ROP regression. Secondary outcomes included likelihood of additional treatment, time from treatment to reactivation or retreatment, refractive outcomes, and adverse events such as retinal detachment, cataract, macular dragging/ectopia, vitreous or retinal hemorrhage, glaucoma, and endophthalmitis. A random-effects meta-analysis was designed. RESULTS: A total of 2361 articles were identified. One thousand nine hundred forty-seven eyes from 7 cohort studies, 1 case-control study, and 2 randomized controlled trials were included with a median follow-up of 21 months (range, 11-75 months). There was no significant difference in disease regression between IVR and LPC (risk ratio [RR], 0.96; 95% confidence interval [CI], 0.83-1.10; P = 0.52); however, eyes that underwent IVR were associated with a higher likelihood of requiring additional treatment (RR, 2.70; CI, 1.55-4.68; P < 0.001). Although less frequent, retreatment occurred earlier with LPC compared with IVR (weighted mean difference [WMD], -4.29 weeks; CI, -6.48 to -2.10; P < 0.001). Furthermore, eyes that received IVR had a lower refractive error, with a WMD of -0.93 diopters (CI, -1.54 to -0.32; P = 0.003) at a median age of assessment of 5.0 years (range, 1.5-6.3 years). There was no difference in the rate of adverse events between LPC and IVR (P > 0.05 for RD, MDR, VH, and cataract). Quality of evidence was rated moderate for likelihood and time of additional treatment, as well as refractive error, but was considered low for disease regression and adverse events. CONCLUSIONS: Compared with LPC, IVR was associated with a higher likelihood of requiring additional treatment but a lower risk of myopia. More studies are needed to evaluate dose-response relationships and temporal trends in ROP regression after these treatments. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".