Delivery of bleomycin among patients with testicular cancer: A population-based study of pulmonary monitoring and toxicity.
Bibliographic record
Abstract
e16056 Background: Bleomycin is commonly used to treat testicular cancer and can be associated with severe pulmonary toxicity. There is limited information about how clinicians monitor patients during treatment and the incidence of pulmonary toxicity in routine practice. Methods: The Ontario Cancer Registry was linked to electronic records of treatment to identify all incident cases of testicular cancer treated with orchiectomy and bleomycin, etoposide, and cisplatin (BEP) chemotherapy in the province of Ontario during 2005-2010. Health-administrative databases were used to describe use of pulmonary function tests (PFTs), chest imaging and physician visits. Results: 475 patients were treated with orchiectomy and chemotherapy. Complete chemotherapy records were available for 93% (368/394) of men treated with BEP. Bleomycin was omitted among 32% (116/368) of patients. PFTs were performed in 17% (63/368), 17% (61/368) and 29% (106/368) of patients before BEP, during BEP, and within 2 years of finishing BEP, respectively. During chemotherapy, 62% of patients (227/368) had chest imaging. In the two years following BEP, 23% (85/368) had a physician visit for respiratory symptoms; this rate was substantially higher among men with greater exposure to bleomycin; 40% (24/60) for 10-12 doses bleomycin vs 21% (53/250) for 7-9 doses vs 14% (8/58) for 1-6 doses (p = 0.002). Two percent of men (8/368) had visit codes for pulmonary fibrosis. Conclusions: A substantial proportion of men treated with BEP will seek medical attention after chemotherapy for respiratory symptoms and this is associated with cumulative dose of bleomycin. Use of PFTs and chest imaging during treatment is common. Whether PFT test results or clinical symptoms are leading to bleomycin dose omission is uncertain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".