Olanzapine for the prophylaxis and rescue of chemotherapy-induced nausea and vomiting (CINV): a retrospective study
Bibliographic record
Abstract
BACKGROUND: While the efficacy of olanzapine in the prophylaxis of chemotherapy-induced nausea and vomiting (CINV) has been documented, the literature on the use of olanzapine as a rescue medication for breakthrough CINV has been scarce. The following study retrospectively evaluated the safety and efficacy of olanzapine for the treatment of breakthrough CINV. The efficacy and safety of olanzapine in the prophylactic setting was also examined in a smaller cohort. METHODS: Electronic medical records of adult patients aged >17 years receiving a prescription for olanzapine from the Odette Cancer Centre Pharmacy at Sunnybrook Hospital between January 2013 and June 2015 were reviewed retrospectively. Inclusion criteria required receiving one or more doses of olanzapine for the rescue or prophylaxis of CINV and documentation of the outcome. RESULTS: A total of 154 patients and 193 treatment cycles were included in the breakthrough setting, while a total of 16 patients and 20 treatment cycles were included in the prophylaxis setting. In the breakthrough setting, 88% of cases experienced improved nausea, while 21% of cases reported improved vomiting. In the prophylactic setting, 100% of cases experienced improved nausea, while 65% achieved improved vomiting. A total of 43% of cases in the breakthrough setting and 65% of cases in the prophylactic setting experienced sedation. CONCLUSIONS: Olanzapine is effective in improving CINV in both the prophylactic and breakthrough settings. The safety, efficacy, and appropriate dosage of olanzapine for the rescue of breakthrough CINV should be prospectively evaluated in a randomized controlled trial (RCT).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".