Feasibility of using the Multinational Association of Supportive Care in Cancer Antiemesis Tool for assessment of chemotherapy-induced nausea and vomiting at the Tom Baker Cancer Centre
Bibliographic record
Abstract
INTRODUCTION: Chemotherapy-induced nausea and vomiting (CINV) has been shown to adversely impact patient anxiety, quality of life, treatment adherence, and use of health care resources. CINV control still remains a challenge, and lack of effective communication between the patient and clinician has been highlighted in the literature as the main barrier to optimal control. The Multinational Association of Supportive Care in Cancer (MASCC) has developed a tool (MASCC Antiemesis Tool (MAT)) to improve assessment and subsequent management of CINV by enhancing communication between patients and their clinicians. This study assessed the feasibility of using the MAT in patients at the Tom Baker Cancer Centre. The secondary objective was to describe the incidence of CINV as identified by the tool. METHODS AND MATERIALS: This study involved a prospective survey using the MAT in patients receiving intravenous chemotherapy. Subjects completed the MAT twice post-chemotherapy regarding CINV symptoms and returned it at their next clinic appointment. Participants were also surveyed to evaluate feasibility with regard to using the MAT. RESULTS: Of the 50 patients recruited, 56% returned surveys. The majority of patients reported that the MAT facilitated communication with their clinician, particularly those who had experienced CINV. Fifty-four percent of patients who returned the MAT reported CINV; however, less than half of them had received American Society of Clinical Oncology-recommended antiemetic regimens. Only four patients with CINV had antiemetic changes made for subsequent cycles. CONCLUSION: The MAT is a feasible tool which can improve communication of CINV symptoms between patients and clinicians, a foundational step toward improving CINV management.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".