Efficacy of Olanzapine, Netupitant, and Palonosetron in Controlling Nausea and Vomiting Associated with Highly Emetogenic Chemotherapy in Patients with Breast Cancer (OLNEPA)
Bibliographic record
Abstract
Abstract Purpose: Chemotherapy-induced nausea and vomiting is a highly prevalent adverse event that could lead to worse treatment adherence and decreased quality of life1,2. To our knowledge, total dexamethasone omission from any regimen to prevent nausea and vomiting has not been evaluated2-4. This study aimed to address the efficacy of a three-drug protocol in preventing nausea and vomiting, with no corticosteroids included. Methods: This was a prospective single-arm phase II study designed to evaluate the efficacy of olanzapine, netupitant, and palonosetron in controlling nausea and vomiting induced by highly emetogenic chemotherapy. Patients were assigned to take olanzapine on Days 1–5 and netupitant and palonosetron on Day 1. No corticosteroid use was allowed. The primary endpoint was complete control of nausea in the first 5 days after chemotherapy administration. Secondary endpoints were complete emesis control (no emesis and no use of rescue medication) and complete control (no emesis, no rescue, and no nausea). Results: For the primary endpoint, the complete nausea control rate was 46% (CI 32–59%), with p < 0.0001. The emesis control rate was 68% (IC 55–80%), and the overall control rate was 46% (IC 32–59%). Conclusion: Omitting dexamethasone for highly emetogenic chemotherapy is feasible and showed a nausea and vomiting control rate that was similar to that of the standard four-drug protocol. Trial registered by the number NCT04669132, on December 16, 2020, on clinicaltrials.gov platform.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".