Question · asked by 1 review
Granulocyte-macrophage colony-stimulating factor (GM-CSF), higher dose (1260 to 12,600 micrograms) vs Granulocyte-macrophage colony-stimulating factor (GM-CSF), lower dose (12.6 to 126 micrograms): Oral mucositis (severe)
- Population
- breast cancer patients undergoing chemotherapy
- Intervention
- Granulocyte-macrophage colony-stimulating factor (GM-CSF), higher dose (1260 to 12,600 micrograms)
- Comparison
- Granulocyte-macrophage colony-stimulating factor (GM-CSF), lower dose (12.6 to 126 micrograms)
- Outcome
- Oral mucositis (severe)
Granulocyte-macrophage colony-stimulating factor (GM-CSF), higher… led to higher oral mucositis (severe) compared with granulocyte-macrophage colony-stimulating factor (GM-CSF), lower…; GRADE not reported.
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Granulocyte-macrophage colony-stimulating factor (GM-CSF), higher dose (1260 to 12,600 micrograms) vs Granulocyte-macrophage colony-stimulating factor (GM-CSF), lower dose (12.6 to 126 micrograms) Oral mucositis (severe) · Adults receiving chemotherapy alone for breast cancer Granulocyte-macrophage colony-stimulating factor (GM-CSF), higher… led to higher oral mucositis (severe) compared with granulocyte-macrophage colony-stimulating factor (GM-CSF), lower…; GRADE not reported. Interventions for preventing oral mucositis in patients with cancer receiving treatment: cytokines and… (2017) · Cochrane All outcomes | RR 2.75 [1.07, 7.04] | 1 study · 36 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Interventions for preventing oral mucositis in patients with cancer receiving treatment: cytokines and growth factors 2017 · Cochrane All outcomes | 2017-05 | Not listed | Not assessed |
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.