OBJECTIVE: The main goal was to investigate the potential of a probabilistic approach for exposure assessment and use this information to evaluate the impact of a complex of policy actions/interventions on dermal exposure to antineoplastic agents among oncology nurses. The central theme of this study was to make optimal use of existing data, supplemented only with limited additional information from a questionnaire survey. METHODS: A task based exposure model was used to estimate dermal exposure of the hands among oncology nurses in non-academic hospitals in the Netherlands. Monte Carlo simulation was used to integrate information from available (exposure) studies and generate exposure distributions for the total population of oncology nurses in both pre- and post-intervention situation. Graphs and descriptive statistics of the simulated exposure distributions were used to evaluate trends in population exposure. RESULTS: The inventory showed that important intervention occurred in the preparation and administering of antineoplastic agents and in the handling of urine. Hardly any changes were identified in de nursing tasks. The use of gloves seemed to have decreased for a number of tasks. The results of the analysis show that the interventions did not affect the median exposure. However frequencies of occurrence of individuals with very high and very low total dermal exposures decreased substantially in the post-intervention situation. Analysis of the effect of pregnancy showed that pregnancy is very unlikely to influence exposure or any of the key input variables. CONCLUSIONS: The present study shows that the probabilistic approach adds valuable information to deterministic exposure assessment, especially when extrapolating data on a subpopulation to populations of individuals at large. The results show that the identified changes in the past decade in Dutch non-academic hospitals resulted in changes in the exposure distribution of antineoplastic agents among oncology nurses.
OBJECTIVE: The main goal was to investigate the potential of a probabilistic approach for exposure assessment and use this information to evaluate the impact of a complex of policy actions/interventions on dermal exposure to antineoplastic agents among oncology nurses. The central theme of this study was to make optimal use of existing data, supplemented only with limited additional information from a questionnaire survey. METHODS: A task based exposure model was used to estimate dermal exposure of the hands among oncology nurses in non-academic hospitals in the Netherlands. Monte Carlo simulation was used to integrate information from available (exposure) studies and generate exposure distributions for the total population of oncology nurses in both pre- and post-intervention situation. Graphs and descriptive statistics of the simulated exposure distributions were used to evaluate trends in population exposure. RESULTS: The inventory showed that important intervention occurred in the preparation and administering of antineoplastic agents and in the handling of urine. Hardly any changes were identified in de nursing tasks. The use of gloves seemed to have decreased for a number of tasks. The results of the analysis show that the interventions did not affect the median exposure. However frequencies of occurrence of individuals with very high and very low total dermal exposures decreased substantially in the post-intervention situation. Analysis of the effect of pregnancy showed that pregnancy is very unlikely to influence exposure or any of the key input variables. CONCLUSIONS: The present study shows that the probabilistic approach adds valuable information to deterministic exposure assessment, especially when extrapolating data on a subpopulation to populations of individuals at large. The results show that the identified changes in the past decade in Dutch non-academic hospitals resulted in changes in the exposure distribution of antineoplastic agents among oncology nurses.
Authors: Mohmmad Ali Eghbal; Elham Yusefi; Maria Tavakoli-Ardakani; Maral Ramazani; Mohammad Hadi Zarei; Ahmad Salimi; Jalal Pourahmad Journal: Iran J Pharm Res Date: 2018 Impact factor: 1.696