Efficacy, safety and effectiveness of ondansetron compared to other serotonin-3 receptor antagonists (5-HT<sub>3</sub>RAs) used to control chemotherapy-induced nausea and vomiting: systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: Chemotherapy-induced nausea and vomiting are adverse effects responsible for worsening quality of life in cancer patients. To assess the efficacy, safety and effectiveness of serotonin receptor antagonist in cancer patients undergoing chemotherapy, comparing ondansetron with granisetron, dolasetron, tropisetron and palonosetron. Areas covered: Systematic review and meta-analysis. The data were collected using CINAHL; CENTRAL; MEDLINE/PubMed; and LILACS databases; grey literature; and manual search. The methodological quality was assessed using the modified Jadad scale; Cochrane Collaboration’s tool for assessing risk of bias in randomized clinical trials and the Newcastle-Ottawa Scale for observational studies. The search was completed in November, 2015. 26 studies were included in the meta-analysis. Ondansetron exhibited similar efficacy than granisetron and tropisetron, as well as greater efficacy than dolasetron for acute vomiting. Palonosetron exhibited greater efficacy than ondansetron for delayed nausea and acute and delayed vomiting. The comparison of granisetron with ondansetron in the cohort studies showed no difference. Expert commentary: In this review, palonosetron had increased efficiency compared with ondansetron, except in the subgroup analysis and acute nausea. Few cohort studies have been published addressing this topic.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".