Early detection of lung cancer in a population at high risk due to occupation and smoking.

Published

Journal Article

OBJECTIVE: The US National Comprehensive Cancer Network (NCCN) recommends two pathways for eligibility for Early Lung Cancer Detection (ELCD) programmes. Option 2 includes individuals with occupational exposures to lung carcinogens, in combination with a lesser requirement on smoking. Our objective was to determine if this algorithm resulted in a similar prevalence of lung cancer as has been found using smoking risk alone, and if so to present an approach for lung cancer screening in high-risk worker populations. METHODS: We enrolled 1260 former workers meeting NCCN criteria, with modifications to account for occupational exposures in an ELCD programme. RESULTS: At baseline, 1.6% had a lung cancer diagnosed, a rate similar to the National Lung Cancer Screening Trial (NLST). Among NLST participants, 59% were current smokers at the time of baseline scan or had quit smoking fewer than 15 years prior to baseline; all had a minimum of 30 pack-years of smoking. Among our population, only 24.5% were current smokers and 40.1% of our participants had smoked fewer than 30 pack-years; only 43.5% would meet entry criteria for the NLST. The most likely explanation for the high prevalence of screen-detected lung cancers in the face of a reduced risk from smoking is the addition of occupational risk factors for lung cancer. CONCLUSION: Occupational exposures to lung carcinogens should be incorporated into criteria used for ELCD programmes, using the algorithm developed by NCCN or with an individualised risk assessment; current risk assessment tools can be modified to incorporate occupational risk.

Full Text

Duke Authors

Cited Authors

  • Welch, LS; Dement, JM; Cranford, K; Shorter, J; Quinn, PS; Madtes, DK; Ringen, K

Published Date

  • March 2019

Published In

Volume / Issue

  • 76 / 3

Start / End Page

  • 137 - 142

PubMed ID

  • 30415231

Pubmed Central ID

  • 30415231

Electronic International Standard Serial Number (EISSN)

  • 1470-7926

Digital Object Identifier (DOI)

  • 10.1136/oemed-2018-105431

Language

  • eng

Conference Location

  • England