Anti-VEGF therapies in the treatment of choroidal neovascularisation secondary to non-age-related macular degeneration: a systematic review
Bibliographic record
Abstract
OBJECTIVES: The aim of this study is to systematically review the evidence for anti-vascular endothelial growth factor (VEGF) therapy in choroidal neovascularisation secondary to conditions other than age-related macular degeneration. DATA SOURCES: MEDLINE, MEDLINE in-process, EMBASE and CENTRAL databases and conference abstracts were searched (from inception to Jan 2014). STUDY ELIGIBILITY CRITERIA, PARTICIPANTS AND INTERVENTIONS: Randomised and non-randomised comparative studies with follow-up of at least 6 months were included and were used to assess clinical effectiveness. STUDY APPRAISAL AND SYNTHESIS METHOD: Risk of bias was assessed using the Cochrane risk of bias tool and modified Newcastle-Ottawa Scale. Meta-analysis was not possible due to methodological heterogeneity. RESULTS: 16 studies met the inclusion criteria (1091 eyes; 963 pathological myopia, 74 other conditions). There was large variation in risk of bias across studies. An improvement in best-corrected visual acuity in anti-VEGF arms over comparators was reported in all studies. The proportion of patients improving by at least 15 letters in anti-VEGF arms ranged from 27.3% to 70%. There were no significant differences between bevacizumab and ranibizumab. LIMITATIONS: Owing to the rarity of choroidal neovascularisation secondary to conditions other than age-related macular degeneration or pathological myopia, there are unlikely to ever be sufficiently powered trials in these populations. CONCLUSIONS: Bevacizumab and ranibizumab appear to be effective in improving visual acuity for patients with choroidal neovascularisation secondary to conditions other than age-related macular degeneration. The evidence base is strongest for choroidal neovascularisation secondary to pathological myopia, however, based on current evidence and likely pharmacological pathways, clinicians should consider treatment with either bevacizumab or ranibizumab for rarer causes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".