Quantitative imaging markers of lung function in a smoking population distinguish COPD sub-groups with differential lung cancer risk.
Cancer epidemiology, biomarkers & prevention
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition with respect to onset, progression and response to therapy. Incorporating clinical- and imaging-based features to refine COPD phenotypes provides valuable information beyond that obtained from traditional clinical evaluations. We characterized the spectrum of COPD-related phenotypes in a sample of former and current smokers and evaluated how these sub-groups differ with respect to sociodemographic characteristics, COPD-related co-morbidities, and subsequent risk of lung cancer.
METHODS: White (N=659) and African American (N=520) male and female participants without lung cancer (controls) in the INHALE study who completed a chest CT scan, interview and spirometry test were used to define distinct COPD-related sub-groups based on hierarchical clustering. Seven variables were used to define clusters: pack years, quit years, FEV1/FVC, % predicted FEV1 and from quantitative CT imaging, % emphysema, % air trapping and mean lung density ratio. Cluster definitions were then applied to INHALE lung cancer cases (N=576) to evaluate lung cancer risk.
RESULTS: Five clusters were identified that differed significantly with respect to sociodemographic (e.g., race, age) and clinical (e.g., BMI, limitations due to breathing difficulties) characteristics. Increased risk of lung cancer was associated with increasingly detrimental lung function clusters (when ordered from most detrimental to least detrimental).
CONCLUSIONS: Measures of lung function vary considerably among smokers, and are not fully explained by smoking intensity.
IMPACT: Combining clinical (spirometry) and radiologic (quantitative CT) measures of COPD define a spectrum of lung disease that predicts lung cancer risk differentially among patient clusters.
ePub ahead of print