Cumulative asbestos exposure as a key predictor of long-term pleuropulmonary outcomes: insights from decades of follow-up

累积石棉暴露是长期胸膜肺部疾病结局的关键预测因素:来自数十年随访的启示

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Abstract

PURPOSE: Occupational asbestos exposure was widespread before regulatory bans, and it remains a risk during renovations or demolitions of older buildings. While asbestos-related diseases are well-documented, less is known about minor radiological changes in exposed individuals. This longitudinal study aimed to identify predictors of pleural and parenchymal lung disorders in individuals with previous occupational asbestos exposure, focusing on both established asbestos-related diseases and minor radiological abnormalities. METHODS: The study tracked 445 former employees (334 men, 111 women) of two Czech asbestos-processing plants, who underwent regular examinations from the 1980s to December 2022. Cox proportional hazards regression models were employed to analyse predictors of asbestos-related diseases, as well as minor radiological findings alone. RESULTS: Over a median latency of 37 years, 127 participants (28.5%) developed asbestos-related diseases, mainly pleural mesothelioma (59 cases). An additional 168 participants (37.8%) exhibited minor radiological findings, predominantly pleural plaques (129 cases), while 150 (33.7%) had no abnormalities. Substantial cumulative exposure was a strong predictor for minor radiological findings (odds ratio [OR] 1.98, 95% confidence interval [CI] 1.18-3.35, p = 0.010) and any endpoint, including diseases (OR 1.89, 95% CI 1.18-3.02, p = 0.008). Respiratory symptoms and impaired spirometry results significantly increased the likelihood of endpoint occurrence. No significant differences emerged between settings with predominantly chrysotile exposure and those with a chrysotile-crocidolite mixture. CONCLUSION: This study highlights the predictive value of cumulative exposure and the need for ongoing surveillance of occupationally exposed individuals to better understand radiological changes, their significance, and to refine risk assessment models.

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