Summary of findings: bevacizumab vs ranibizumab: Serious systemic adverse events at one year
Summary of findings: bevacizumab showed no clear difference in serious systemic adverse events at 1 yearb compared with ranibizumab (moderate certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Summary of findings: bevacizumab vs ranibizumab Serious systemic adverse events at 1 yearb · people with neovascular age‐related macular degeneration Summary of findings: bevacizumab showed no clear difference in serious systemic adverse events at 1 yearb compared with ranibizumab (moderate certainty). Anti‐vascular endothelial growth factor for neovascular age‐related macular degeneration (2019) · Cochrane Headline outcomes only | RR 1.15 [0.99, 1.34] | 6 studies · 3365 participants | Moderate |
Summary of findings: bevacizumab vs ranibizumab Serious systemic adverse events at one year2 · people with neovascular age‐related macular degeneration Summary of findings: bevacizumab probably leads to higher serious systemic adverse events at one year2 compared with ranibizumab (moderate certainty). Anti‐vascular endothelial growth factor for neovascular age‐related macular degeneration (2014) · Cochrane Headline outcomes onlyearlier version CD005139.PUB3, superseded | RR 1.27 [1.06, 1.52] | 4 studies · 2597 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Anti‐vascular endothelial growth factor for neovascular age‐related macular degeneration 2019 · Cochrane Headline outcomes only | Not reported | list not extracted yet | Not assessed |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.