The safety and efficacy of ferumoxytol in the treatment of iron deficiency: a systematic review and meta‐analysis
Bibliographic record
Abstract
INTRODUCTION: Ferumoxytol is an intravenous (IV) iron formulation for treatment of iron deficiency (ID) that faced post-marketing reports of serious adverse events (SAEs). OBJECTIVES: To determine the safety and efficacy of ferumoxytol compared to other iron formulations and placebo. METHODS: We searched the Cochrane Library, Medline, and EMBASE from inception until February 2018 as well as trial registries and reference lists of relevant articles for randomized or quasi-randomized controlled trials. RESULTS: The review included nine studies with 5691 participants. Studies were at low risk of bias. When comparing ferumoxytol to other IV iron formulations, there is moderate quality evidence (QE) of little to no difference in treatment emergent adverse events (TEAEs) (risk ratio [RR] 0.88, 95% confidence interval [CI] 0.80-0.97), treatment related adverse events (TRAEs) (RR 0.73, 95% CI 0.61-0.88), SAEs (RR 1.13, 95% CI 0.77-1.67), hypotension or hypersensitivity reactions (RR 0.58, 95% CI 0.31-1.09), or composite cardiovascular outcomes (RR 0.56, 95% CI 0.24-1.29), low QE of little to no difference in related SAEs (RR 0.55, 95% CI 0.05-6.16), and high QE of little to no difference in the number of patients with an increase in hemoglobin by at least 1 g/dL (RR 1.04, 95% CI 0.96-1.12). Ferumoxytol had less TEAEs compared to oral iron (RR 0.78, 95% CI 0.61-0.98), but more compared to placebo (RR 1.62, 95% CI 1.01-2.61). DISCUSSION: Ferumoxytol is as efficacious and safe as alternative IV iron formulations with no clear safety concerns.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.006 | 0.006 |
| 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) | 0.004 | 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".