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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

2016· article· en· W6977506768 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsnot available
Fundersnot available
KeywordsOndansetronPalonosetronGranisetronNauseaTropisetronAdverse effectJadad scale

Abstract

fetched live from OpenAlex

<b>Introduction</b>: 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. <b>Areas covered</b>: 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. <b>Expert commentary</b>: 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.050
GPT teacher head0.308
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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