Rationale: To study the relationship between emphysema and/or airflow obstruction and lung cancer in a high-risk population. Objective: We studied lung cancer related to radiographic emphysema and spirometric airflow obstruction in tobacco-exposed persons who were screened for lung cancer using chest computed tomography (CT). Methods: Subjects completed questionnaires, spirometry, and low-dose helical chest CT. CT scans were scored for emphysema based on National Emphysema Treatment Trial criteria. Multiple logistic regressions estimated the independent associations between various factors, including radiographic emphysema and airflow obstruction, and subsequent lung cancer diagnosis. Measurements and Main Results: Among 3,638 subjects, 57.5, 18.8, 14.6, and 9.1% had no, trace, mild, and moderate–severe emphysema, and 57.3, 13.6, 22.8, and 6.4% had no, mild (Global Initiative for Chronic Obstructive Lung Disease [GOLD] I), moderate (GOLD II), and severe (GOLD III–IV) airflow obstruction. Of 3,638 subjects, 99 (2.7%) received a lung cancer diagnosis. Adjusting for sex, age, years of cigarette smoking, and number of cigarettes smoked daily, logistic regression showed the expected lung cancer association with the presence of airflow obstruction (GOLD I–IV, odds ratio [OR], 2.09; 95% confidence interval [CI], 1.33–3.27). A second logistic regression showed lung cancer related to emphysema (OR, 3.56; 95% CI, 2.21–5.73). After additional adjustments for GOLD class, emphysema remained a strong and statistically significant factor related to lung cancer (OR, 3.14; 95% CI, 1.91–5.15). Conclusions: Emphysema on CT scan and airflow obstruction on spirometry are related to lung cancer in a high-risk population. Emphysema is independently related to lung cancer. Both radiographic emphysema and airflow obstruction should be considered when assessing lung cancer risk.

Rationale: The role of computed tomography (CT) screening for lung cancer is controversial, currently under study, and not yet fully elucidated. Objectives: To report findings from initial and 1-year repeat screening low-radiation-dose CT of the chest and 3-year outcomes for 50- to 79-year-old current and ex-smokers in the Pittsburgh Lung Screening Study (PLuSS). Methods: Notified of findings on screening CT, subjects received diagnostic advice from both study and personal physicians. Tracking subjects for up to three years since initial screening, we obtained medical records to document diagnostic procedures, lung cancer diagnoses, and deaths. Measurements and Main Results: 3,642 and 3,423 subjects had initial and repeat screening. A total of 1,477 (40.6% of 3,624) were told about noncalcified lung nodules on the initial screening and, before repeat screening, 821 (55.6% of 1,477, 22.5% of 3,642) obtained one or more subsequent diagnostic imaging studies (CT, positron emission tomography [PET], or PET-CT). Tracking identified 80 subjects with lung cancer, including 53 subjects with tumor seen at initial screening. In all, 36 subjects (1.0% of the 3,642 screened), referred for abnormalities on either the initial or repeat screening, had a major thoracic surgical procedure (thoracotomy, video-assisted thoracoscopic surgery [VATS], median sternotomy, or mediastinoscopy) leading to a noncancer final diagnosis. Out of 82 subjects with thoracotomy or VATS to exclude malignancy in a lung nodule, 28 (34.1%) received a noncancer final diagnosis. Forty of 69 (58%) subjects with non–small cell lung cancer had stage I disease at diagnosis. Conclusions: Though leading to the discovery of early stage lung cancer, CT screening also led to many diagnostic follow-up procedures, including major thoracic surgical procedures with noncancer outcomes.

Background Low-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate nodules. We aimed to develop and assess prediction models based on radiological features to discriminate between benign and malignant pulmonary lesions detected on a baseline screen. Methods Using four international lung cancer screening studies, we extracted 2060 radiomic features for each of 16 797 nodules (513 malignant) among 6865 participants. After filtering out low-quality radiomic features, 642 radiomic and 9 epidemiological features remained for model development. We used cross-validation and grid search to assess three machine learning (ML) models (eXtreme Gradient Boosted Trees, random forest, least absolute shrinkage and selection operator (LASSO)) for their ability to accurately predict risk of malignancy for pulmonary nodules. We report model performance based on the area under the curve (AUC) and calibration metrics in the held-out test set. Results The LASSO model yielded the best predictive performance in cross-validation and was fit in the full training set based on optimised hyperparameters. Our radiomics model had a test-set AUC of 0.93 (95% CI 0.90 to 0.96) and outperformed the established Pan-Canadian Early Detection of Lung Cancer model (AUC 0.87, 95% CI 0.85 to 0.89) for nodule assessment. Our model performed well among both solid (AUC 0.93, 95% CI 0.89 to 0.97) and subsolid nodules (AUC 0.91, 95% CI 0.85 to 0.95). Conclusions We developed highly accurate ML models based on radiomic and epidemiological features from four international lung cancer screening studies that may be suitable for assessing indeterminate screen-detected pulmonary nodules for risk of malignancy.

Rationale: As computed tomography (CT) screening for lung cancer becomes more widespread, volumetric analyses, including doubling times, of CT-screen detected lung nodules and lung cancers may provide useful information in the follow-up and management of CT-detected lung nodules and cancers. Objectives: To analyze doubling times in CT screen detected lung cancers and compare prevalent and nonprevalent cancers and different cell types on non small cell lung cancer. Methods: We performed volumetric and doubling time analysis on 63 non–small cell lung cancers detected as part of the Pittsburgh Lung Screening Study using a commercially available VITREA 2 workstation and VITREA VITAL nodule segmentation software. Measurements and Main Results: Doubling times (DT) were divided into three groups: rapid (DT < 183 d), typical (DT 183–365 d), and slow (DT > 365 d). Adenocarcinoma/bronchioloalveolar carcinoma comprised 86.7% of the slow DT group compared with 20% of the rapid DT group. Conversely, squamous cell cancer comprised 60% of the rapid DT group compared with 3.3% of the slow DT group. Twenty-eight of 42 (67%) prevalent and 2 of 21 (10%) nonprevalent cancers were in the slow DT group (P < 0.0001; Fisher's exact test). Twenty-four of 32 (75%) prevalent and 1 of 11 (9%) nonprevalent adenocarcinomas were in the slow DT group (P < 0.0002; Fisher's exact test). Conclusions: Volumetric analysis of CT-detected lung cancers is particularly useful in AC/BAC. Prevalent cancers have a significantly slower DT than nonprevalent cancers and a higher percentage of adenocarcinoma/bronchioloalveolar carcinoma. These results should affect the management of indeterminant lung nodules detected on screening CT scans.

CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.

Lung Cancer is occasionally observed in patients with Idiopathic Pulmonary Fibrosis (IPF). We sought to describe the epidemiologic and clinical characteristics of lung cancer for patients with IPF and other interstitial lung disease (ILD) using institutional and statewide data registries. We conducted a retrospective analysis of IPF and non-IPF ILD patients from the ILD center registry, to compare with lung cancer registries at the University of Pittsburgh as well as with population data of lung cancer obtained from Pennsylvania Department of Health between 2000 and 2015. Among 1108 IPF patients, 31 patients were identified with IPF and lung cancer. The age-adjusted standard incidence ratio of lung cancer was 3.34 (with IPF) and 2.3 (with non-IPF ILD) (between-group Hazard ratio = 1.4, p = 0.3). Lung cancer worsened the mortality of IPF (p < 0.001). Lung cancer with IPF had higher mortality compared to lung cancer in non-IPF ILD (Hazard ratio = 6.2, p = 0.001). Lung cancer among IPF was characterized by a predilection for lower lobes (63% vs. 26% in non-IPF lung cancer, p < 0.001) and by squamous cell histology (41% vs. 29%, p = 0.07). Increased incidence of lung cancer was observed among single lung transplant (SLT) recipients for IPF (13 out of 97, 13.4%), with increased mortality compared to SLT for IPF without lung cancer (p = 0.028) during observational period. Lung cancer is approximately 3.34 times more frequently diagnosed in IPF patients compared to general population, and associated with worse prognosis compared with IPF without lung cancer, with squamous cell carcinoma and lower lobe predilection. The causality between non-smoking IPF patients and lung cancer is to be determined.