The Partners—Airflow Obstruction, Emphysema, and Lung Cancer

Lung cancer risk prediction to select smokers for screening CT--a model based on the Italian COSMOS trial

Screening with low-dose helical computed tomography (CT) has been shown to significantly reduce lung cancer mortality but the optimal target population and time interval to subsequent screening are yet to be defined. We developed two models to stratify individual smokers according to risk of developing lung cancer. We first used the number of lung cancers detected at baseline screening CT in the 5,203 asymptomatic participants of the COSMOS trial to recalibrate the Bach model, which we propose using to select smokers for screening. Next, we incorporated lung nodule characteristics and presence of emphysema identified at baseline CT into the Bach model and proposed the resulting multivariable model to predict lung cancer risk in screened smokers after baseline CT. Age and smoking exposure were the main determinants of lung cancer risk. The recalibrated Bach model accurately predicted lung cancers detected during the first year of screening. Presence of nonsolid nodules (RR = 10.1, 95% CI = 5.57-18.5), nodule size more than 8 mm (RR = 9.89, 95% CI = 5.84-16.8), and emphysema (RR = 2.36, 95% CI = 1.59-3.49) at baseline CT were all significant predictors of subsequent lung cancers. Incorporation of these variables into the Bach model increased the predictive value of the multivariable model (c-index = 0.759, internal validation). The recalibrated Bach model seems suitable for selecting the higher risk population for recruitment for large-scale CT screening. The Bach model incorporating CT findings at baseline screening could help defining the time interval to subsequent screening in individual participants. Further studies are necessary to validate these models.

Are airflow obstruction and radiographic evidence of emphysema risk factors for lung cancer? A nested case-control study using quantitative emphysema analysis

OBJECTIVES

Several studies have identified airflow obstruction as a risk factor for lung cancer independent of smoking history, but the risk associated with the presence of radiographic evidence of emphysema has not been extensively studied. We proposed to assess this risk using a quantitative volumetric CT scan analysis.

METHODS

Sixty-four cases of lung cancer were identified from a prospective cohort of 1,520 participants enrolled in a spiral CT scan lung cancer screening trial. Each case was matched to six control subjects for age, sex, and smoking history. Quantitative CT scan analysis of emphysema was performed. Spirometric measures were also conducted. Data were analyzed using conditional logistic regression making use of the 1:6 set groups of 64 cases and 377 matched control subjects.

RESULTS

Decreased FEV(1) and FEV(1)/FVC were significantly associated with a diagnosis of lung cancer with ORs of 1.15 (95% CI, 1.00-1.32; P = .046) and 1.29 (95% CI, 1.02-1.62; P = .031), respectively. The quantity of radiographic evidence of emphysema was not found to be a significant risk for lung cancer with OR of 1.042 (95% CI, 0.816-1.329; P = .743). Additionally, there was no significant association between severe emphysema and lung cancer with OR of 1.57 (95% CI, 0.73-3.37).

CONCLUSIONS

We confirm previous observations that airflow obstruction is an independent risk factor for lung cancer. The absence of a clear relationship between radiographic evidence of emphysema and lung cancer using an automated quantitative volumetric analysis may result from different population characteristics than those of prior studies, radiographic evidence of emphysema quantitation methodology, or absence of any relationship between emphysema and lung cancer risk.