O-242 Literature review of biological monitoring studies to assess healthcare worker’s exposure to antineoplastic drugs
Bibliographic record
Abstract
<h3>Introduction</h3> Antineoplastic drugs, also known as hazardous drugs, are used to treat cancer. Healthcare workers’ exposure to these agents may lead to DNA damage and adverse reproductive effects. Exposure to antineoplastic drugs can be assessed via biological monitoring. <h3>Objectives</h3> To conduct a literature review of studies examining biological monitoring of healthcare workers exposed to antineoplastic drugs to identify trends and knowledge gaps. <h3>Methods</h3> The literature search was performed on three databases: Proquest, Web of Science and PubMed. For inclusion, an article had to be in English and published between 2005 and 2020. Search terms included ‘antineoplastic drugs’ or ‘hazardous drugs’ AND ‘occupational’ or ‘healthcare workers’ or ‘pharmacist’ or ‘nurse’ AND ‘blood’ or ‘urine’ or ‘biomarkers’. <h3>Results</h3> Overall, the literature review resulted in 70 unique articles - 30 examined urine as the matrix, 31 had non-urine samples and nine papers collected both urine and non-urine samples. Regarding the urine sampling studies, researchers collected either spot samples or 24-hr voids. Cyclophosphamide was the most common analyte (69%) with a detection limit ranging from 0.09 to 0.20 ng/ml. Approximately 75% of the articles reported at least one urine sample had detectable levels of drug. In some instances, urinary drug contamination was found even though workers wore personal protective equipment. For those studies that collected other matrices, blood and exfoliated buccal cells were the most common specimens. A majority (81%) reported that there was a statistically significant difference in results between exposed and non-exposed populations. Many studies reported that safe work practices, which includes the use of personal protective equipment, may not be adequate to protect healthcare workers. <h3>Conclusion</h3> There is value in conducting biological monitoring to assess healthcare workers’ exposure to antineoplastic drugs. However, because of the variability in sampling and analytical methods, standardization is recommended to ensure biological monitoring results are comparable.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".