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Record W4247927423 · doi:10.21203/rs.3.rs-318837/v1

Olanzapine 5mg vs 10mg for the Prophylaxis of Chemotherapy-Induced Nausea and Vomiting – A Network Meta-Analysis

2021· preprint· en· W4247927423 on OpenAlexaff
Ronald Chow, Rudolph M. Navari, Bryan Terry, Carlo DeAngelis, Elizabeth Pršić

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOlanzapineVomitingMeta-analysisNauseaChemotherapy-induced nausea and vomitingMedicineChemotherapyInternal medicineAntiemeticPsychiatrySchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

Abstract Introduction: Olanzapine administered at a 10mg dosage for prophylaxis of chemotherapy-induced nausea and vomiting may be associated with fatigue, drowsiness and reduced general activity. Therefore, a 5mg dose may be preferred, to reduce the occurrence of adverse events. The aim of this study was to conduct a network meta-analysis, and report on the efficacy of olanzapine administered at 5mg, relative to when administered at 10 mg. Methods: We used previously-published data from the systematic review by Chow et al which identified 17 adult trials which used 10mg doses, 3 which used 5mg doses, and 1 which used a mix of 5 and 10mg doses. A multivariate network meta-analysis using a restricted maximum likelihood model was used. Results: The complete response rate in the acute phase is not statistically different, between 5mg and 10mg doses of olanzapine – RR 0.97, 95% CI: 0.83 – 1.13. Additionally, in the overall phase, 5mg olanzapine is similarly as efficacious as 10mg olanzapine – RR 0.95, 95% CI: 0.56 – 1.60. Evaluation of data demonstrated that there was inadequate information to compare the toxicities of the two doses. Conclusion: Our analyses support individual published trials, and the rationale for future trials to compare 5mg to 10mg olanzapine regimens in head-to-head comparisons.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.249
GPT teacher head0.448
Teacher spread0.199 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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
Published2021
Admission routes1
Has abstractyes

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