Effectiveness and safety of tocilizumab in refractory noninfectious uveitis: a systematic review and meta-analysis
Bibliographic record
Abstract
Purpose: The aim of this study was to comprehensively evaluate the efficacy and safety of tocilizumab in patients with refractory noninfectious uveitis (NIU) through a systematic review and meta-analysis. Methods: A comprehensive literature search was conducted across PubMed, Embase, Web of Science, Cochrane Library, and ClinicalTrials.gov from inception to 13 July 2025. Eligible studies included case series and cohort studies evaluating clinical outcomes of tocilizumab in NIU. Study quality was assessed using the Joanna Briggs Institute Case Series Checklist and Newcastle-Ottawa Scale. A single-arm meta-analysis was performed using a random-effects model. Results: Thirteen studies involving 374 patients were included. The pooled rate of sustained inactive uveitis was 57.08% (95% CI: 46.94%-66.96%), and the overall inflammation remission rate at the final follow-up was 75.23% (95% CI: 64.04%-85.09%). Macular edema resolved in 93.22% of patients (95% CI: 86.76%-98.01%), with a mean reduction in a central macular thickness of 143.57 µm. Mean visual acuity improved by -0.29 logarithm of the minimum angle of resolution (logMAR) (95% CI: -0.55 to -0.04). The pooled glucocorticoid discontinuation rate was 40.25% (95% CI: 13.43%-70.27%). During the follow-up period, the pooled incidence of adverse events and serious adverse events was 13.05% (95% CI: 8.88%-17.78%) and 4.41% (95% CI: 1.08%-9.16%), respectively. Subgroup analysis suggested greater efficacy among patients treated for ≥9 months. Conclusion: Tocilizumab provides meaningful clinical benefit with acceptable safety in refractory NIU related to autoimmune and inflammatory diseases, particularly in patients with macular edema. These results support the use of tocilizumab as a viable second-line therapeutic option following the failure of conventional immunosuppressants and antitumor necrosis factor alpha agents. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251069626, identifier CRD420251069626.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.039 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".