Increasing frequency of non-smoking lung cancer: Presentation of patients with early disease to a tertiary institution in the UK
- PMID: 28783541
- DOI: 10.1016/j.ejca.2017.06.031
Increasing frequency of non-smoking lung cancer: Presentation of patients with early disease to a tertiary institution in the UK
Abstract
Background: Never-smokers with lung cancer often present late as there are no established aetiological risk factors. The aim of the study is to define the frequency over time and characterise clinical features of never-smokers presenting sufficiently early to determine if it is possible to identify patients at risk.
Methods: We retrospectively analysed data from a prospectively collected database of patients who underwent surgery. The frequency was defined as number of never-smokers versus current and ex-smokers by year. Clinical features at presentation were collated as frequency.
Results: A total of 2170 patients underwent resection for lung cancer from March 2008 to November 2014. The annual frequency of developing lung cancer in never-smokers increased from 13% to 28%, attributable to an absolute increase in numbers and not simply a change in the ratio of never-smokers to current and ex-smokers. A total of 436 (20%) patients were never-smokers. The mean age was 60 (16 SD) years and 67% were female. Presenting features were non-specific consisting of cough in 34%, chest infections in 18% and haemoptysis in 11%. A total of 14% were detected on incidental chest film, 30% on computed tomography, 7% on positron-emission tomography/computed tomography and 1% on MRI.
Conclusions: We observed more than a double of the annual frequency of never-smokers in the last 7 years. Patients present with non-specific symptoms and majority were detected on incidental imaging, a modality that is likely to play an increasingly important role for early detection in this cohort that does not have any observable clinical risk factors.
Keywords: Mediastinum abnormalities; Mediastinum diagnostic imaging; PET-CT; Smoking.
Copyright © 2017 Elsevier Ltd. All rights reserved.
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