Quantitative Imaging Markers of Lung Function in a Smoking Population Distinguish COPD Subgroups with Differential Lung Cancer Risk.

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 subgroups differ with respect to sociodemographic characteristics, COPD-related comorbidities, 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 subgroups based on hierarchical clustering. Seven variables were used to define clusters: pack years, quit years, FEV1/FVC, % predicted FEV1, and from quantitative CT (qCT) 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 (qCT) measures of COPD defines a spectrum of lung disease that predicts lung cancer risk differentially among patient clusters.

Risk of Lung Cancer Associated with COPD Phenotype Based on Quantitative Image Analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a risk factor for lung cancer. This study evaluates alternative measures of COPD based on spirometry and quantitative image analysis to better define a phenotype that predicts lung cancer risk. METHODS: A total of 341 lung cancer cases and 752 volunteer controls, ages 21 to 89 years, participated in a structured interview, standardized CT scan, and spirometry. Logistic regression, adjusted for age, race, gender, pack-years, and inspiratory and expiratory total lung volume, was used to estimate the odds of lung cancer associated with FEV1/FVC, percent voxels less than -950 Hounsfield units on the inspiratory scan (HUI) and percent voxels less than -856 HU on expiratory scan (HUE). RESULTS: The odds of lung cancer were increased 1.4- to 3.1-fold among those with COPD compared with those without, regardless of assessment method; however, in multivariable modeling, only percent voxels <-856 HUE as a continuous measure of air trapping [OR = 1.04; 95% confidence interval (CI), 1.03-1.06] and FEV1/FVC < 0.70 (OR = 1.71; 95% CI, 1.21-2.41) were independent predictors of lung cancer risk. Nearly 10% of lung cancer cases were negative on all objective measures of COPD. CONCLUSION: Measures of air trapping using quantitative imaging, in addition to FEV1/FVC, can identify individuals at high risk of lung cancer and should be considered as supplementary measures at the time of screening for lung cancer. IMPACT: Quantitative measures of air trapping based on imaging provide additional information for the identification of high-risk groups who might benefit the most from lung cancer screening. Cancer Epidemiol Biomarkers Prev; 25(9); 1341-7. ©2016 AACR.