Update on the management of chemotherapy-induced nausea and vomiting – focus on palonosetron
Bibliographic record
Abstract
PURPOSE: Nausea and vomiting are major adverse effects of chemotherapy and can greatly impact patients' quality of life. Although chemotherapy-induced nausea and vomiting (CINV) prevalence is high, treatment remains difficult. Palonosetron is a 5-hydroxytryptamine receptor antagonist (5-HT3RA) approved for treatment of CINV. The purpose of this review is to discuss existing and emerging therapeutic options, and examine studies focusing on palonosetron with regards to efficacy, pharmacology, tolerability, safety, and patient-derived outcomes. METHODS: A literature search was conducted using Ovid MEDLINE and EMBASE to identify relevant studies using palonosetron alone or in combination with other antiemetics. Studies were extracted if they included complete response (CR), complete control (CC), no nausea, no vomiting, and no rescue medications as an endpoint. Studies were also included if safety endpoints were examined. RESULTS: Palonosetron alone has been shown to improve CR and CC rates for patients receiving low, moderate, or high emetogenic chemotherapy. Rates were further improved with the addition of dexamethasone, a corticosteroid. Furthermore, the addition of neurokinin-1 receptor antagonists, such as netupitant markedly improved efficacy profiles compared to palonosetron alone. Aprepitant is an antiemetic that has exhibited positive results in combination with palonosetron. Recently, a new drug consisting of netupitant and palonosetron (NEPA) has demonstrated significantly more efficacious prevention of CINV. Regardless of the combination, palonosetron has been well tolerated. The most common adverse events were constipation, headache, fatigue, and dizziness, with the majority of patients describing them as only mild or moderate. CONCLUSION: Palonosetron, alone or with other antiemetics, has improved CINV treatment due to its ability to significantly reduce delayed phases of CINV, compared to similar 5-HT3RAs. Palonosetron is both more effective than first generation 5-HT3RAs and safer, as it results in a smaller prolongation of the QTc interval, compared to other 5-HT3RAs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".