Incidence and Risk Factors of Platinum-Based Chemotherapy-Induced Nausea and Vomiting: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Platinum-based chemotherapy significantly increases the risk of nausea and vomiting, which can impair the treatment’s efficacy and the patient’s quality of life. This meta-analysis examines the incidence and risk factors of platinum-based chemotherapy-induced nausea and vomiting (PINV) in patients treated with this chemotherapy. Methods: This systematic review and meta-analysis were conducted in accordance with the PRISMA 2020 guidelines. We conducted a literature search in the databases PubMed, Embase, Web of Science, WanFang, China Science and Technology Journal Database (VIP), China National Knowledge Infrastructure (CNKI), and Chinese Medical Association Journal Database (CMAJD) through to 20 January 2025. Studies that reported the incidence and identified risk factors of nausea and vomiting specifically in patients receiving platinum-based chemotherapy were included in the review. The data were extracted independently by two reviewers. The odds ratios (ORs) for each risk factor were calculated from the included studies. Sensitivity analyses and additional subgroup analyses were performed to ensure the robustness of our findings. Results: This meta-analysis included 32 studies involving 14,207 participants. Female sex (OR = 2.363, 95% CI = 1.363–4.096, p = 0.002), anxiety (OR = 1.689, 95% CI = 1.057–2.700, p = 0.028), fatigue (OR = 1.413, 95% CI = 1.145–1.744, p = 0.001), motion sickness (OR = 1.816, 95% CI = 1.266–2.605, p = 0.001), and a history of vomiting during chemotherapy (OR = 2.728, 95% CI = 1.468–5.069, p = 0.002) were significantly associated with an increased risk of PINV. Conclusion: Female sex, anxiety, fatigue, motion sickness, and a history of vomiting during chemotherapy increase the risk of PINV during platinum-based treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".