Amifostine vs placebo/no treatment: Oral mucositis (severe)
- Population
- Patients with cancer receiving radiotherapy, chemotherapy or targeted therapies
- Intervention
- Amifostine
- Comparison
- placebo/no treatment
- Outcome
- Oral mucositis (severe)
It is very uncertain whether amifostine changes oral mucositis (severe) compared with placebo/no treatment (very low certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Amifostine vs Placebo/no treatment Oral mucositis (severe) · Patients with cancer receiving radiotherapy, chemotherapy or targeted therapies · Median 28 days It is very uncertain whether amifostine changes oral mucositis (severe) compared with placebo/no treatment (very low certainty). Interventions for preventing oral mucositis for patients with cancer receiving treatment (2011) · Cochrane All outcomes | RR 0.68 [0.45, 1.03] | 9 studies · 845 participants | Very low |
Amifostine vs Placebo/no treatment Oral mucositis (severe) · Patients with cancer receiving radiotherapy, chemotherapy or targeted therapies · Median 28 days Amifostine showed no clear difference in oral mucositis (severe) compared with placebo/no treatment; GRADE not reported. Interventions for preventing oral mucositis for patients with cancer receiving treatment (2010) · Cochrane All outcomesearlier version CD000978.PUB4, superseded | RR 0.68 [0.45, 1.03] | 9 studies | GRADE not reported |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 for patients with cancer receiving treatment 2011 · Cochrane All outcomes | 2011-02 | Not listed | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Amifostine vs placebo/no treatment · Patients with cancer receiving chemotherapy and/or radiotherapy · 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.