Lung cancer mortality among construction workers: implications for early detection.

Journal Article (Journal Article)

OBJECTIVES: This study examined predictors of lung cancer mortality, beyond age and smoking, among construction workers employed at US Department of Energy (DOE) sites to better define eligibility for low-dose CT (LDCT) lung cancer screening. METHODS: Predictive models were based on 17 069 workers and 352 lung cancer deaths. Risk factors included age, gender, race/ethnicity, cigarette smoking, years of trade or DOE work, body mass index (BMI), chest X-ray results, spirometry results, respiratory symptoms, beryllium sensitisation and personal history of cancer. Competing risk Cox models were used to obtain HRs and to predict 5-year risks. RESULTS: Factors beyond age and smoking included in the final predictive model were chest X-ray changes, abnormal lung function, chronic obstructive pulmonary disease (COPD), respiratory symptoms, BMI, personal history of cancer and having worked 5 or more years at a DOE site or in construction. Risk-based LDCT eligibility demonstrated improved sensitivity, specificity and positive predictive value compared with current US Preventive Services Task Force guidelines. The risk of lung cancer death from 5 years of work in the construction industry or at a DOE site was comparable with the risk from a personal cancer history, a family history of cancer or a diagnosis of COPD. LDCT eligibility criteria used for DOE construction workers, which includes factors beyond age and smoking, identified 86% of participants who eventually would die from lung cancer compared with 51% based on age and smoking alone. CONCLUSIONS: Results support inclusion of risk from occupational exposures and non-malignant respiratory clinical findings in LDCT clinical guidelines.

Full Text

Duke Authors

Cited Authors

  • Dement, JM; Ringen, K; Hines, S; Cranford, K; Quinn, P

Published Date

  • April 2020

Published In

Volume / Issue

  • 77 / 4

Start / End Page

  • 207 - 213

PubMed ID

  • 31996473

Electronic International Standard Serial Number (EISSN)

  • 1470-7926

Digital Object Identifier (DOI)

  • 10.1136/oemed-2019-106196


  • eng

Conference Location

  • England