Biological monitoring of occupational exposure to antineoplastic drugs in hospital settings.

MEDICINA DEL LAVORO(2012)

引用 42|浏览1
暂无评分
摘要
Background: In view of the evidence of cytotoxicity of chemotherapic antineoplastic drugs (AD), current guidelines recommend the evaluation of the health risks of hospital personnel exposed to these compounds. Biological monitoring is the main tool to evaluate all possible drug intake and measure workers' real risk. Objectives: The aim of this study was to assess occupational exposure to AD in a large hospital in Northern Italy in order to verify the effectiveness of the structural and procedural improvements carried out over the last decade. Methods: Three biological monitoring campaigns were performed using LC-MS/MS analysis of cyclophosphamide (CP) and metotrexate (MTX) as biomarkers of internal dose in the urine of hospital workers. In the first two campaigns, 50 and 81 workers respectively were monitored during AD preparation operations. The last campaign, concerning AD administration activity, was performed after a centralized preparation unit had been set up. Two environmental monitoring campaigns were carried out as well, to complete AD exposure assessment. Results: During the first monitoring campaign we found positive urinary samples in all the wards studied (total positivity 36%), whereas in the second campaign 11% of the samples were positive and four departments showed negative results in all urine samples. The last campaign showed all urinary CP and MTX levels below the detection limit of the analytical method. Conclusion: Exposure of oncology ward nurses considerably decreased due to the centralization of AD preparation operations together with training and education of workers. The last biological monitoring results were reassuring; nevertheless, surface contamination still occurred and safety measures should be further improved in order to achieve the lowest reasonably possible contamination levels.
更多
查看译文
关键词
Biological monitoring,antineoplastic drugs,health risk
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要