Secondary and cumulative meta-analysis of olanzapine for antiemetic prophylaxis for chemotherapy-induced nausea and vomiting: do we still need to study its effectiveness?
Bibliographic record
Abstract
BACKGROUND: Olanzapine has been found to have antiemetic properties due to its ability to inhibit multiple serotonergic, dopaminergic, alpha-1 adrenergic and histamine receptors. In 2016, a meta-analysis of 10 randomized controlled trials (RCTs) on olanzapine in the prophylactic setting found olanzapine to be more efficacious than other standard antiemetics in the prophylactic setting. However, since the review, many clinical trials using olanzapine for chemotherapy-induced nausea and vomiting (CINV) have been published-in many cases, contending that further trials would further help elucidate the efficacy of olanzapine for CINV given the continued paucity of literature. The primary aim of this study is to conduct a secondary, cumulative meta-analysis to assess the impact of the most recent trials on the published effect estimate of olanzapine and ultimately determine whether trials published since 2016 have significantly changed the summary estimate. METHODS: As reported previously, a literature search was conducted up until 2015, of Ovid Medline, Embase and the Cochrane Central Register of Controlled Trials; 10 RCTs with a total of over 1,000 patients were included, that compared olanzapine to other antiemetics in the prophylactic setting, which reported on at least one of two endpoints-no emesis and no nausea. The Mantel-Haenszel, random-effects analysis model was used to compute cumulative risk ratios (RR) and their accompanying 95% confidence intervals (CIs). RESULTS: For the endpoint of emetic control, the cumulative meta-analysis shows that the summary effect did not change noticeably with the inclusion of the most recent trials. In the acute phase, the RR shifted from 1.07 before 2011 to 1.10 after 2015, even after the inclusion of 7 trials. Similar small changes were noted in the delayed and overall phases. For the endpoint of nausea control, the cumulative meta-analysis does show a significant visual change in summary effect, except for nausea control in the acute phase. In the delayed phase, the RR shifts from 1.58 before 2011 to 1.50 after 2015. In the overall phase, the RR shifts from 1.642 before 2011 to 1.53 after 2015. CONCLUSIONS: Olanzapine's efficacy for the prophylaxis of CINV has been sufficiently documented, with respect to emetic control. There is, however, more limited data supporting its efficacy with respect to nausea control.
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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 | 0.048 | 0.095 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.091 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".