In a recent article, Maisonneuve and colleagues described risk models identifying smokers at greatest risk of lung cancer for computed tomographic (CT) screening (1). We agree that such an approach will help increase lung cancer detection rates, improve cost-effectiveness, and reduce harm from unnecessary follow-up to screening. However, we propose below an alternative approach based on the current literature.
Among the risk models for lung cancer that they described (1), some were developed in populations including lifelong nonsmokers. As such, the relevance of these models in the context of CT screening, where exclusively current or former smokers are targeted, is not clear. Moreover, the model developed by Maisonneuve and colleagues (1) is based on age and smoking exposure (Bach model) and little comment is made of the sensitivity of such an approach. Using a representative sample of 446 lung cancer cases (2), we estimate that the eligibility criteria of the National Lung Screening Trial (NLST) and COSMOS trial would identify only 47% and 57% of cases, respectively. This means that approximately 40% to 50% of all lung cancer cases will occur outside these current screening programs.
We strongly agree with the study of Maisonneuve and colleagues (1) that additional clinical variables such as chronic obstructive pulmonary disease (COPD; airflow limitation and/or emphysema) will contribute significantly to the risk-based approach to optimizing CT screening. The epidemiologic data linking reduced FEV1 (airflow limitation) to an elevated risk of lung cancer is strongly supported by both cross-sectional and prospective data (1–3). Using data from the Pittsburgh and NELSON CT trials (3, 4), simple spirometry identified COPD 89% and 84% of the time, respectively, compared with using CT-based emphysema which identified 49% and 67%, respectively (3, 4). More importantly, based on the Pittsburgh trial (3), 85% of lung cancer cases were identified among smokers with either airflow limitation and/or CT-based emphysema (see Fig. 1). In these trials, this constitutes 46% to 48% of all CT screening participants. Conversely, only 15% of lung cancers were detected in those who had normal lungs (normal spirometry and no emphysema). Consistent with the recently published National Comprehensive Cancer Network (NCCN) recommendations for lung cancer screening (www.NCCN.org), we have developed a risk model for lung cancer that includes age, COPD, and genetic risk variables (family history and genetic markers) that has use in all smokers, including those with normal lung function (5). This is currently undergoing further validation in the NLST. We conclude that the optimal target population for CT screening of lung cancer can be identified by risk models that include clinical variables indicative of COPD (1, 3, 5).
See the Response, p. 699
Disclosure of Potential Conflicts of Interest
R.P. Young has commercial research grant (financial support) from Synergenz BioScience Ltd.; ownership interest (including patents) and patents related to genetic risk prediction and lung cancer held by Synergenz BioScience Ltd.; and is an unpaid consultant to Synergenz BioScience Ltd. R.J. Hopkins is employed with Synergenz BioScience Ltd.
Conception and design of the study: R.P. Young, R.J. Hopkins.
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): R.P. Young.
Writing, review, and/or revision of the manuscript: R.P. Young, R.J. Hopkins.
R.P. Young, and the funding of his research, has been supported by grants from the University of Auckland (Auckland, New Zealand), Health Research Council of New Zealand, and Synergenz BioSciences Ltd.