Canadian monitoring program of the surface contamination with 11 antineoplastic drugs in 122 centers
Bibliographic record
Abstract
Introduction Occupational exposure to antineoplastic drugs can lead to long-term adverse effects on workers’ health. Environmental monitoring is conducted once a year, as part of a Canadian monitoring program. The objective was to describe contamination with 11 antineoplastic drugs measured on surfaces. Methods Six standardized sites in oncology pharmacy and six in outpatient clinic were sampled in each hospital. Samples were analyzed by ultra-performance liquid chromatography coupled with tandem mass spectrometry (non-platinum drugs) and by inductively coupled plasma mass spectrometry (platinum-based drugs). The limits of detection (in ng/cm 2 ) were: 0.0006 for cyclophosphamide; 0.001 for docetaxel; 0.04 for 5-fluorouracil; 0.0004 for gemcitabine; 0.0007 for irinotecan; 0.0009 for methotrexate; 0.004 for paclitaxel, 0.009 for vinorelbine, 0.02 for doxorubicine, 0.0037 for etoposide and 0.004 for the platinum. Sub-analyses were done with a Kolmogorov-Smirnov test Results 122 Canadian hospitals participated. Cyclophosphamide (451/1412, 32% of positive samples, 90 th percentile of concentration 0.0160 ng/cm 2 ) and gemcitabine (320/1412, 23%, 0.0036 ng/cm 2 ) were most frequently measured on surfaces. The surfaces most frequently contaminated with at least one drug were the front grille inside the biological safety cabinet (97/121, 80%) and the armrest of patient treatment chair (92/118, 78%).The distribution of cyclophosphamide concentration was higher for centers that prepared ≥ 5000 antineoplastic drug preparations/year (p < 0.0001). Conclusions This monitoring program allowed centers to benchmark their contamination with pragmatic contamination thresholds derived from the Canadian 90 th percentiles. Problematic areas need corrective measures such as decontamination. The program helps to increase the workers’ awareness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".