Abstract：
:This study aims to develop a prognostic risk prediction model for the development of silicosis among workers exposed to silica dust in China. The prediction model was performed by using retrospective cohort of 3,492 workers exposed to silica in an iron ore, with 33 years of follow-up. We developed a risk score system using a linear combination of the predictors weighted by the LASSO penalized Cox regression coefficients. The model's predictive accuracy was evaluated using time-dependent ROC curves. Six predictors were selected into the final prediction model (age at entry of the cohort, mean concentration of respirable silica, net years of dust exposure, smoking, illiteracy, and no. of jobs). We classified workers into three risk groups according to the quartile (Q1, Q3) of risk score; 203 (23.28%) incident silicosis cases were derived from the high risk group (risk score ≥ 5.91), whilst only 4 (0.46%) cases were from the low risk group (risk score < 3.97). The score system was regarded as accurate given the range of AUCs (83-96%). This study developed a unique score system with a good internal validity, which provides scientific guidance to the clinicians to identify high-risk workers, thus has important cost efficient implications.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Tse LA,Dai J,Chen M,Liu Y,Zhang H,Wong TW,Leung CC,Kromhout H,Meijer E,Liu S,Wang F,Yu IT,Shen H,Chen Wdoi
10.1038/srep11059subject
Has Abstractpub_date
2015-06-19 00:00:00pages
11059issn
2045-2322pii
srep11059journal_volume
5pub_type
临床试验,杂志文章abstract：:Drug-resistant tuberculosis (TB) is a serious global problem, and pathogen factors involved in the transmission of isoniazid (INH)-resistant TB have not been fully investigated. We performed whole genome sequencing of 332 clinical Mycobacterium tuberculosis (Mtb) isolates collected from patients newly diagnosed with s...
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更新日期：2015-10-09 00:00:00
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pub_type： 临床试验,杂志文章
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