A Population-Based Study of Pulmonary Monitoring and Toxicity for Patients with Testicular Cancer Treated with Bleomycin
Bibliographic record
Abstract
Background：Bleomycin is commonly used to treat advanced testicular cancer and can be associated with severe pulmonary toxicity. The primary objective of the present study was to describe the use of pulmonary function tests (PFTs) and chest imaging before, during, and after treatment with bleomycin. Methods: To identify all incident cases of testicular cancer treated with bleomycin-based chemotherapy in the Canadian province of Ontario during 2005–2010, the Ontario Cancer Registry was linked with chemotherapy treatment records. Health administrative databases were used to describe use of PFTs, chest imaging, and physician visits for respiratory complaints. Results: Of 394 patients treated with orchiectomy and chemotherapy who received at least 1 dose of bleomycin, 93% had complete chemotherapy records available. In the 4 weeks before, during, and within 2 years after finishing bleomycin-based chemotherapy, pfts were performed in 17%, 17%, and 29% of patients respectively. Chest imaging was performed in 68%, 62%, and 98% of patients in the same time periods. In the 2 years after bleomycin-based chemotherapy, 23% of treated patients had a physician visit for respiratory symptoms. That rate was substantially higher for men with greater exposure to bleomycin: 40% (24 of 60) for 10–12 doses bleomycin compared with 21% (53 of 250) for 7–9 doses and with 14% (8 of 58) for 1–6 doses (p = 0.002). Conclusions: Quality improvement initiatives are needed to increase baseline rates of chest imaging within 4 weeks of starting chemotherapy for testicular cancer; to understand why such a high proportion of men have chest imaging during bleomycin-based chemotherapy; and to mitigate the excess pulmonary toxicity seen with increasing exposure to bleomycin.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".