Question · asked by 1 review
Deferasirox vs deferoxamine: Overall discontinuation (
- Population
- patients with managing transfusional iron overload in people with sickle cell disease
- Intervention
- Deferasirox
- Comparison
- deferoxamine
- Outcome
- Overall discontinuation (
Deferasirox may leads to lower discontinuations compared with deferoxamine (low certainty).
What each review found
Current versions onlyNo studies found 0 · 0%GRADE not reported 0 · 0%Very low 0 · 0%Low 1 · 50%Moderate 1 · 50%High 0 · 0%
| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Deferasirox vs deferoxamine Discontinuations · patients with sickle cell disease and transfusional iron overload Deferasirox may leads to lower discontinuations compared with deferoxamine (low certainty). Deferasirox for managing transfusional iron overload in people with sickle cell disease (2014) · Cochrane Headline outcomes only | RR 0.53 [0.31, 0.92] | 2 studies · 398 participants | Low |
Deferasirox vs Deferoxamine Discontinuations · patients with managing transfusional iron overload in people with sickle cell disease Deferasirox showed no clear difference in discontinuations compared with deferoxamine (moderate certainty). Deferasirox for managing transfusional iron overload in people with sickle cell disease (2010) · Cochrane Headline outcomes onlyearlier version CD007477.PUB2, superseded | RR 1.67 [0.36, 7.81] | 1 study · 195 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Deferasirox for managing transfusional iron overload in people with sickle cell disease 2014 · Cochrane Headline outcomes only | Not reported | Not extracted | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Deferasirox vs deferoxamine · People with thalassaemia and secondary iron overload · 0 reviews
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.