2023 updated MASCC/ESMO consensus recommendations: prevention of nausea and vomiting following high-emetic-risk antineoplastic agents
Bibliographic record
Abstract
Abstract Purpose This systematic review updates the MASCC/ESMO recommendations for high-emetic-risk chemotherapy (HEC) published in 2016–2017. HEC still includes cisplatin, carmustine, dacarbazine, mechlorethamine, streptozocin, and cyclophosphamide in doses of > 1500 mg/m2 and the combination of cyclophosphamide and an anthracycline (AC) in women with breast cancer. Methods A systematic review report following the PRISMA guidelines of the literature from January 1, 2015, until February 1, 2023, was performed. PubMed (Ovid), Scopus (Google), and the Cochrane Database of Systematic Reviews were searched. The literature search was limited to randomized controlled trials, systematic reviews, and meta-analyses. Results Forty-six new references were determined to be relevant. The main topics identified were (1) steroid-sparing regimens, (2) olanzapine-containing regimens, and (3) other issues such as comparisons of antiemetics of the same drug class, intravenous NK1 receptor antagonists, and potentially new antiemetics. Five updated recommendations are presented. Conclusion There is no need to prescribe steroids (dexamethasone) beyond day 1 after AC HEC, whereas a 4-day regimen is recommended in non-AC HEC. Olanzapine is now recommended as a fixed part of a four-drug prophylactic antiemetic regimen in both non-AC and AC HEC. No major differences between 5-HT3 receptor antagonists or between NK1 receptor antagonists were identified. No new antiemetic agents qualified for inclusion in the updated recommendations.
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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 | 0.031 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.016 |
| Bibliometrics | 0.012 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".