Prophylaxis of radiation-induced nausea and vomiting: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: The aim of this article was to systematically review the efficacy and safety of various antiemetics in prophylaxis of radiation-induced nausea and vomiting (RINV). METHODS: A literature search of Ovid MEDLINE, EMBASE and Cochrane CENTRAL was performed to identify randomized controlled trials (RCTs) that evaluated the efficacy of prophylaxis for RINV in patients receiving radiotherapy to abdomen/pelvis, including total body irradiation (TBI). Primary endpoints were complete control of nausea and complete control of vomiting during acute and delayed phases. Secondary endpoints included use of rescue medication, quality of life (QoL) and incidence of adverse events. RESULTS: Seventeen RCTs were identified. Among patients receiving radiotherapy to abdomen/pelvis, our meta-analysis showed that prophylaxis with a 5-hydroxytryptamine-3 receptor antagonist (5HT3 RA) was significantly more efficacious than placebo and dopamine receptor antagonists in both complete control of vomiting [OR 0.49; 95% confidence interval (CI): 0.33-0.72 and OR 0.17; 95% CI: 0.05-0.58 respectively] and complete control of nausea (OR 0.43; 95% CI: 0.26-0.70 and OR 0.46; 95% CI: 0.24-0.88 respectively). 5HT3 RAs were also more efficacious than rescue therapy and dopamine receptor antagonists plus dexamethasone. The addition of dexamethasone to 5HT3 RA compared to 5HT3 RA alone provides a modest improvement in prophylaxis of RINV. Among patients receiving TBI, 5HT3 RA was more effective than other agents (placebo, combination of metoclopramide, dexamethasone and lorazepam). CONCLUSIONS: 5HT3 RAs are more effective than other antiemetics for prophylaxis of RINV in patients receiving radiotherapy to abdomen/pelvis and TBI. Future RCTs should investigate the efficacy of newer agents such as substance P neurokinin 1 receptor antagonists in addition to 5HT3 RAs in prophylaxis of RINV during both acute and delayed phases.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.026 |
| 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".