CHOOSING WISELY IN PROPHYLACTIC NEUROKININ-1 RECEPTOR ANTAGONIST USE AMONG WOMEN WITH BREAST CANCER: A RETROSPECTIVE COHORT STUDY
Bibliographic record
Abstract
Breast cancer is the second most common cancer among women in the United States (US) with 297,790 new cases expected in 2023. Survival rates for breast cancer have significantly improved over the past decade due to effective screening, diagnosis, and advancement in multimodal therapy, including surgery, radiotherapy, and chemotherapy. In the US, the treatment cost for breast cancer increased substantially from $16.5 billion in 2010 to $23.8 billion in 2020. Moreover, in the US, female breast cancer contributes to 14% of all cancer treatment costs. Unnecessary use of certain oncology services increases the cost of cancer care without improving the quality and value of cancer care. In April 2012, the American Board of Internal Medicine (ABIM) Foundation launched a national campaign, “Choosing Wisely (CW)” to reduce the use of medical services that do not improve patient’s health. CW is a clinician-led campaign that began in the US but quickly spread to Canada, Australia, Japan, and most parts of Europe. As a part of the CW campaign, the American Society of Clinical Oncology (ASCO) issued the top five measures in 2012 to identify the areas of low-value utilization to promote cost reductions. Later, on October 29, 2013, ASCO issued another set of five measures, including the one focused on chemotherapy-induced nausea vomiting (CINV) and antiemetic use stating: “Don’t give patients starting on a chemotherapy regimen that has low or moderate risk of nausea and vomiting antiemetic drugs intended for use with a regimen that has a high risk of causing nausea and vomiting”. While chemotherapy has contributed substantially to improved health outcomes, certain chemotherapy regimens are associated with severe nausea and vomiting. Antiemetic prophylaxis is an effective treatment to prevent CINV in the majority of cancer patients. The main prophylactic antiemetics classes include corticosteroids, serotonin receptor antagonists (5HT3-RAs), and Neurokinin-1 receptor antagonists (NK1-RAs). NK1-RAs are clinically efficacious as evident from the clinical trials and were thus rapidly incorporated into antiemetic guidelines for CINV prophylaxis for patients who receive high emetogenic chemotherapy. To promote the appropriate use of antiemetics, several oncology organizations worldwide have developed clinical guidelines. In the US, these antiemesis guidelines published by ASCO and the National Comprehensive Cancer Network (NCCN) have categorized chemotherapy agents based on their emetogenic potential (high, moderate, or low risk). Both guidelines recommend against using NK1-RAs for low and moderate emetogenic chemotherapy regimens, particularly because these antiemetics are expensive and may not provide any additional
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".