Interstitial lung abnormalities in a large clinical lung cancer screening cohort: association with mortality and ILD diagnosis.

BACKGROUND: Interstitial lung abnormalities (ILA) are CT findings suggestive of interstitial lung disease in individuals without a prior diagnosis or suspicion of ILD. Previous studies have demonstrated that ILA are associated with clinically significant outcomes including mortality. The aim of this study was to determine the prevalence of ILA in a large CT lung cancer screening program and the association with clinically significant outcomes including mortality, hospitalizations, cancer and ILD diagnosis. METHODS: This was a retrospective study of individuals enrolled in a CT lung cancer screening program from 2012 to 2014. Baseline and longitudinal CT scans were scored for ILA per Fleischner Society guidelines. The primary analyses examined the association between baseline ILA and mortality, all-cause hospitalization, and incidence of lung cancer. Kaplan-Meier plots were generated to visualize the associations between ILA and lung cancer and all-cause mortality. Cox regression proportional hazards models were used to test for this association in both univariate and multivariable models. RESULTS: 1699 subjects met inclusion criteria. 41 (2.4%) had ILA and 101 (5.9%) had indeterminate ILA on baseline CTs. ILD was diagnosed in 10 (24.4%) of 41 with ILA on baseline CT with a mean time from baseline CT to diagnosis of 4.47 ± 2.72 years. On multivariable modeling, the presence of ILA remained a significant predictor of death, HR 3.87 (2.07, 7.21; p < 0.001) when adjusted for age, sex, BMI, pack years and active smoking, but not of lung cancer and all-cause hospital admission. Approximately 50% with baseline ILA had progression on the longitudinal scan. CONCLUSIONS: ILA identified on baseline lung cancer screening exams are associated with all-cause mortality. In addition, a significant proportion of patients with ILA are subsequently diagnosed with ILD and have CT progression on longitudinal scans. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov; No.: NCT04503044.

Improved motivation and readiness to quit shortly after lung cancer screening: Evidence for a teachable moment.

BACKGROUND: For patients at high risk for lung cancer, screening using low-dose computed tomography (lung cancer screening [LCS]) is recommended. The purpose of this study was to examine whether screening may serve as a teachable moment for smoking-related outcomes. METHODS: In a smoking-cessation trial, participants (N = 843) completed 2 phone interviews before randomization: before LCS (T0) and after LCS (T1). By using logistic and linear regression, the authors examined teachable moment variables (perceived risk, lung cancer worry) and outcomes (readiness, motivation, and cigarettes per day [CPD]). RESULTS: Participants were a mean ± SD age of 63.7 ± 5.9 years, had 47.8 ± 7.1 pack-years of smoking, 35.2% had a high school diploma or General Educational Development (high school equivalency) degree or less, and 42.3% were undergoing their first scan. Between T0 and T1, 25.7% of participants increased readiness to quit, 9.6% decreased readiness, and 64.7% reported no change (P < .001). Motivation to quit increased (P < .05) and CPD decreased between assessments (P < .001), but only 1.3% self-reported quitting. Compared with individuals who reported no lung cancer worry/little worry, extreme worry was associated with readiness to quit in the next 30 days (odds ratio, 1.8; 95% CI, 1.1-3.0) and with higher motivation (b = 0.83; P < .001) at T1. Individuals undergoing a baseline (vs annual) scan were more ready to quit in the next 30 days (odds ratio, 1.8; 95% CI, 1.3-2.5). CONCLUSIONS: During the brief window between registering for LCS and receiving the results, the authors observed that very few participants quit smoking, but a significant proportion improved on readiness and motivation to quit, particularly among individuals who were undergoing their first scan and those who were extremely worried about lung cancer. These results indicate that providing evidence-based tobacco treatment can build upon this teachable moment.

Quantitative Pectoralis Muscle Area is Associated with the Development of Lung Cancer in a Large Lung Cancer Screening Cohort.

BACKGROUND: Studies have demonstrated an inverse relationship between body mass index (BMI) and the risk of developing lung cancer. We conducted a retrospective cohort study evaluating baseline quantitative computed tomography (CT) measurements of body composition, specifically muscle and fat area in a large CT lung screening cohort (CTLS). We hypothesized that quantitative measurements of baseline body composition may aid in risk stratification for lung cancer. METHODS: Patients who underwent baseline CTLS between January 1st, 2012 and September 30th, 2014 and who had an in-network primary care physician were included. All patients met NCCN Guidelines eligibility criteria for CTLS. Quantitative measurements of pectoralis muscle area (PMA) and subcutaneous fat area (SFA) were performed on a single axial slice of the CT above the aortic arch with the Chest Imaging Platform Workstation software. Cox multivariable proportional hazards model for cancer was adjusted for variables with a univariate p < 0.2. Data were dichotomized by sex and then combined to account for baseline differences between sexes. RESULTS: One thousand six hundred and ninety six patients were included in this study. A total of 79 (4.7%) patients developed lung cancer. There was an association between the 25th percentile of PMA and the development of lung cancer [HR 1.71 (1.07, 2.75), p < 0.025] after adjusting for age, BMI, qualitative emphysema, qualitative coronary artery calcification, and baseline Lung-RADS® score. CONCLUSIONS: Quantitative assessment of PMA on baseline CTLS was associated with the development of lung cancer. Quantitative PMA has the potential to be incorporated as a variable in future lung cancer risk models.

Automated Tracking of Follow-Up Imaging Recommendations.

OBJECTIVE. Radiology reports often contain follow-up imaging recommendations. Failure to comply with these recommendations in a timely manner can lead to poor patient outcomes, complications, and legal liability. As such, the primary objective of this research was to determine adherence rates to follow-up recommendations. MATERIALS AND METHODS. Radiology-related examination data, including report text, for examinations performed between June 1, 2015, and July 31, 2017, were extracted from the radiology departments at the University of Washington (UW) and Lahey Hospital and Medical Center (LHMC). The UW dataset contained 923,885 examinations, and the LHMC dataset contained 763,059 examinations. A 1-year period was used for detection of imaging recommendations and up to 14-months for the follow-up examination to be performed. RESULTS. On the basis of an algorithm with 97.9% detection accuracy, the follow-up imaging recommendation rate was 11.4% at UW and 20.9% at LHMC. Excluding mammography examinations, the overall follow-up imaging adherence rate was 51.9% at UW (range, 44.4% for nuclear medicine to 63.0% for MRI) and 52.0% at LHMC (range, 30.1% for fluoroscopy to 63.2% for ultrasound) using a matcher algorithm with 76.5% accuracy. CONCLUSION. This study suggests that follow-up imaging adherence rates vary by modality and between sites. Adherence rates can be influenced by various legitimate factors. Having the capability to identify patients who can benefit from patient engagement initiatives is important to improve overall adherence rates. Monitoring of follow-up adherence rates over time and critical evaluation of variation in recommendation patterns across the practice can inform measures to standardize and help mitigate risk.

NCCN Guidelines as a Model of Extended Criteria for Lung Cancer Screening.

Background: This review assessed the performance of patients in NCCN high-risk group 2 in a clinical CT lung screening (CTLS) program. Methods: We retrospectively reviewed screening results for all patients from our institution undergoing clinical CTLS from January 2012 through December 2016, with follow-up through June 2017. To qualify for screening, patients had to meet the NCCN Guidelines high-risk criteria for CTLS, have a physician order for screening, be asymptomatic, be lung cancer-free for 5 years, and have no known metastatic disease. We compared demographics and screening performance of NCCN high-risk groups 1 and 2 across >4 rounds of screening. Screening metrics assessed included rates of positive and suspicious examinations, significant incidental and infectious/inflammatory findings, false negatives, and cancer detection. We also compared cancer stage and histology detected in each NCCN high-risk group. Results: A total of 2,927 individuals underwent baseline screening, of which 698 (24%) were in NCCN group 2. On average, group 2 patients were younger (60.6 vs 63.1 years), smoked less (38.8 vs 50.8 pack-years), had quit longer (18.1 vs 6.3 years), and were more often former smokers (61.4% vs 44.2%). Positive and suspicious examination rates, false negatives, and rates of infectious/inflammatory findings were equivalent in groups 1 and 2 across all rounds of screening. An increased rate of cancer detection was observed in group 2 during the second annual (T2) screening round (2.7% vs 0.5%; P=.005), with no difference in the other screening rounds: baseline (T0; 2% vs 2.3%; P=.61), first annual (T1; 1.2% vs 1.7%; P=.41), and third annual and beyond (≥T3; 1.2% vs 1.1%; P=1.00). Conclusions: CTLS appears to be equally effective in both NCCN high-risk groups.

Outcomes of Positive and Suspicious Findings in Clinical Computed Tomography Lung Cancer Screening and the Road Ahead.

Rationale: Future optimization of computed tomography (CT) lung cancer screening (CTLS) algorithms will depend on clinical outcomes data. Objectives: To report the outcomes of positive and suspicious findings in a clinical CTLS program. Methods: We retrospectively reviewed results for patients from our institution undergoing lung cancer screening from January 2012 through December 2018, with follow-up through December 2019. All exams were retrospectively rescored using Lung-RADS v1.1 (LR). Metrics assessed included positive, probably benign, and suspicious exam rates, frequency/nature of care escalation, and lung cancer detection rates after a positive, probably benign, and suspicious exam result and overall. We calculated time required to resolve suspicious exams as malignant or benign. Results were broken down by subcategories, reason for positive/suspicious designation, and screening round. Results: During the study period 4,301 individuals underwent a total of 10,897 exams. The number of positive (13.9%), suspicious (5.5%), and significant incidental (6.4%) findings was significantly higher at baseline screening. Cancer detection and false-positive rates were 2.0% and 12.3% at baseline versus 1.3% and 5.1% across subsequent screening rounds, respectively. Baseline solid nodule(s) 6 to <8 mm were the only probably benign findings resulting in lung cancer detection within 12 months. New solid nodules 6 to <8 mm were the only LR category 4A (LR4A) findings falling within the LR predicted cancer detection range of 5-15% (12.8%). 38.5% of LR4A cancers were detected within 3 months. Conclusions: Modification of the definition and suggested workup of positive and suspicious lung cancer screening findings appears warranted.

Surgery and invasive diagnostic procedures for benign disease are rare in a large low-dose computed tomography lung cancer screening program.

OBJECTIVE: Lung cancer screening with low-dose chest computed tomography improves survival. However, concerns about overdiagnosis and unnecessary interventions persist. We reviewed our lung cancer screening program to determine the rate of surgery and invasive procedures for nonmalignant disease. METHODS: We reviewed all patients undergoing lung cancer screening from January 2012 to June 2017 with follow-up through January 2019. Patients with suspicious findings (Lung CT Screening Reporting and Data System 4) were referred for further evaluation. RESULTS: Of 3280 patients screened, 345 (10.5%) had Lung CT Screening Reporting and Data System 4 findings. A total of 311 patients had complete follow-up, of whom 93 (29.9%) were diagnosed with lung cancer. Eighty-three patients underwent lung surgery (2.5% of screened patients). Forty patients underwent lobectomy (48.2%), 3 patients (3.6%) underwent bilobectomy, and 40 patients (48.2%) underwent sublobar resection. Fourteen patients underwent surgery for benign disease (0.43% of screened patients). Fifty-four patients, 5 with benign disease, had at least 1 invasive diagnostic procedure but never underwent surgery. The incidence of any invasive intervention for nonmalignant disease was 0.95% (31/3280 patients). There were no postprocedural deaths within 60 days. Twenty-five patients (0.76%) underwent stereotactic body radiation therapy; 19 patients (76%) had presumed lung cancer without pretreatment pathologic confirmation. CONCLUSIONS: Surgical resection for benign disease occurred in 0.43% of patients undergoing lung cancer screening. The combined incidence of any invasive diagnostic or therapeutic intervention, including surgical resection, for benign disease was only 0.95%. Periprocedural complications were rare. These results indicate that concern over unnecessary interventions is overstated and should not hinder adoption of lung cancer screening. A multidisciplinary team approach, including thoracic surgeons, is critical to maintain an appropriate rate of interventions in lung cancer screening.

Towards radiologist-level cancer risk assessment in CT lung screening using deep learning.

PURPOSE: Lung cancer is the leading cause of cancer mortality in the US, responsible for more deaths than breast, prostate, colon and pancreas cancer combined and large population studies have indicated that low-dose computed tomography (CT) screening of the chest can significantly reduce this death rate. Recently, the usefulness of Deep Learning (DL) models for lung cancer risk assessment has been demonstrated. However, in many cases model performances are evaluated on small/medium size test sets, thus not providing strong model generalization and stability guarantees which are necessary for clinical adoption. In this work, our goal is to contribute towards clinical adoption by investigating a deep learning framework on larger and heterogeneous datasets while also comparing to state-of-the-art models. METHODS: Three low-dose CT lung cancer screening datasets were used: National Lung Screening Trial (NLST, n = 3410), Lahey Hospital and Medical Center (LHMC, n = 3154) data, Kaggle competition data (from both stages, n = 1397 + 505) and the University of Chicago data (UCM, a subset of NLST, annotated by radiologists, n = 132). At the first stage, our framework employs a nodule detector; while in the second stage, we use both the image context around the nodules and nodule features as inputs to a neural network that estimates the malignancy risk for the entire CT scan. We trained our algorithm on a part of the NLST dataset, and validated it on the other datasets. Special care was taken to ensure there was no patient overlap between the train and validation sets. RESULTS AND CONCLUSIONS: The proposed deep learning model is shown to: (a) generalize well across all three data sets, achieving AUC between 86% to 94%, with our external test-set (LHMC) being at least twice as large compared to other works; (b) have better performance than the widely accepted PanCan Risk Model, achieving 6 and 9% better AUC score in our two test sets; (c) have improved performance compared to the state-of-the-art represented by the winners of the Kaggle Data Science Bowl 2017 competition on lung cancer screening; (d) have comparable performance to radiologists in estimating cancer risk at a patient level.

Lung Screening Benefits and Challenges: A Review of The Data and Outline for Implementation.

Lung cancer is the leading cause of cancer-related deaths worldwide, accounting for almost a fifth of all cancer-related deaths. Annual computed tomographic lung cancer screening (CTLS) detects lung cancer at earlier stages and reduces lung cancer-related mortality among high-risk individuals. Many medical organizations, including the U.S. Preventive Services Task Force, recommend annual CTLS in high-risk populations. However, fewer than 5% of individuals worldwide at high risk for lung cancer have undergone screening. In large part, this is owing to delayed implementation of CTLS in many countries throughout the world. Factors contributing to low uptake in countries with longstanding CTLS endorsement, such as the United States, include lack of patient and clinician awareness of current recommendations in favor of CTLS and clinician concerns about CTLS-related radiation exposure, false-positive results, overdiagnosis, and cost. This review of the literature serves to address these concerns by evaluating the potential risks and benefits of CTLS. Review of key components of a lung screening program, along with an updated shared decision aid, provides guidance for program development and optimization. Review of studies evaluating the population considered "high-risk" is included as this may affect future guidelines within the United States and other countries considering lung screening implementation.

A qualitative study exploring older smokers' attitudes and motivation toward quitting during the COVID-19 pandemic.

Older individuals who smoke are at increased risk of having severe outcomes from COVID-19, due to their long-term smoking and underlying health conditions. In this qualitative study, we explored the impact of COVID-19 on attitudes toward smoking and motivation to quit. Participants (N = 30) were enrolled in a larger ongoing randomized controlled smoking cessation trial conducted in the lung cancer screening setting. From March to May 2020, we assessed quantitative and qualitative responses to participants' overall concern about COVID-19, changes in amount smoked, and motivation to reduce/quit smoking. Responses to the quantitative questions indicated that 64.3% of participants were extremely concerned with COVID-19, 20.7% reported reductions in amount smoked, and 37.9% reported increased motivation to quit. The qualitative responses, which were transcribed and coded using Consensual Qualitative Research guidelines, expanded upon these findings by providing the content of participants' concerns, which included perceived risk of contracting COVID-19, the added stressors caused by COVID-19, and a variable impact on the amount smoked and motivation to quit. Although half of participants expressed extreme concern regarding COVID-19, fewer indicated increased motivation or reduced smoking. Qualitative themes suggested that the initial two months of the pandemic prompted some smokers to reduce or quit, but it exacerbated smoking triggers for others. Understanding how the pandemic continues to affect this vulnerable group will aid in adapting methods to support their efforts to stop smoking and remain abstinent.

Predictors of attrition in a smoking cessation trial conducted in the lung cancer screening setting.

SIGNIFICANCE: Although it is a requirement that tobacco treatment is offered to cigarette smokers undergoing low-dose computed tomographic lung cancer screening (LCS), not all smokers engage in treatment. To understand the barriers to tobacco treatment in this setting, we evaluated predictors of attrition in a smoking cessation trial among individuals undergoing LCS. METHODS: Prior to LCS, 926 participants, 50-80 years old, completed the baseline (T0) phone assessment, including demographic, clinical, tobacco, and psychological characteristics. Following LCS and receipt of the results, participants completed the pre-randomization (T1) assessment. RESULTS: At the T1 assessment, 735 (79%) participants were retained and 191 (21%) dropped out. In multivariable analyses, attrition was higher among those who: smoked >1 pack per day (OR = 1.44, CI 1.01, 2.06) or had undergone their first (vs. annual) LCS scan (OR = 1.70, CI 1.20, 2.42). Attrition was lower among those with: more education (associates (OR = 0.67, CI = 0.46, 0.98) or bachelor's degree (OR = 0.56, CI 0.35, 0.91) vs. high school/GED), some (vs. none/a little) worry about lung cancer (OR = 0.60, CI 0.39, 0.92), or a screening result that was benign (OR = 0.57, CI 0.39, 0.82) or probably benign (OR = 0.38, CI 0.16, 0.90) vs. negative. CONCLUSIONS: This study illuminated several LCS-related factors that contributed to trial attrition. Increasing tobacco treatment in this setting will require targeted strategies for those who report little lung cancer worry, are undergoing their first LCS exam, and/or who have a negative LCS result. Addressing attrition and reducing barriers to tobacco treatment will increase the likelihood of cessation, thereby reducing the risk of developing lung cancer.

Pathologic and gene expression comparison of CT- screen detected and routinely detected stage I/0 lung adenocarcinoma in NCCN risk-matched cohorts.

INTRODUCTION: Although three randomized control trials have proven mortality benefit of CT lung cancer screening (CTLS), <5% of eligible US smokers are screened. Some attribute this to fear of harm conveyed at shared decision visits, including the harm of overdiagnosis/overtreatment of indolent BAC-like adenocarcinoma. METHODS: Since the frequency of indolent cancers has not been compared between CTLS and routinely detected cohorts, we compare pathology and RNA expression of 86 NCCN high-risk CTLS subjects to 83 high-risk (HR-R) and 51 low-risk (LR-R) routinely detected patients. Indolent adenocarcinoma was defined as previously described for low malignant potential (LMP) adenocarcinoma along with AIS/MIA. Exome RNA sequencing was performed on a subset of high-risk (CTLS and HR-R) FFPE tumor samples. RESULTS: Indolent adenocarcinoma (AIS, MIA, and LMP) showed 100% disease-specific survival (DSS) with similar frequency in CTLS (18%) and HR-R (20%) which were comparatively lower than LR-R (33%). Despite this observation, CTLS exhibited intermediate DSS between HR-R and LR-R (5-year DSS: 88% CTLS, 82% HR-R, & 95% LR-R, p = 0.047), possibly reflecting a 0.4 cm smaller median tumor size and lower frequency of tumor necrosis compared to HR-R. WGCNA gene modules derived from TCGA lung adenocarcinoma correlated with aggressive histologic patterns, mitotic activity, and tumor invasive features, but no significant differential expression between CTLS and HR-R was observed. CONCLUSION: CTLS subjects are at no greater risk of overdiagnosis from indolent adenocarcinoma (AIS, MIA, and LMP) than risk-matched patients whose cancers are discovered in routine clinical practice. Improved outcomes likely reflect detection and treatment at smaller size.

Change in amount smoked and readiness to quit among patients undergoing lung cancer screening.

BACKGROUND: There is mixed evidence regarding whether undergoing computed tomography lung cancer screening (LCS) can serve as a "teachable moment" that impacts smoking behavior and attitudes. The study aim was to assess whether the standard procedures of undergoing LCS and receiving free and low-cost evidence-based cessation resources impacted short-term smoking-related outcomes. METHODS: Participants were smokers (N=87) who were registered to undergo lung screening and were enrolled in a cessation intervention trial. We conducted two phone interviews, both preceding trial randomization: the first interview was conducted prior to lung screening, and the second interview followed lung screening (median =12.5 days post-screening) and participants' receipt of their screening results. The interviews assessed demographic characteristics, interest in evidence-based cessation intervention methods, and tobacco-related characteristics, including cigarettes per day and readiness to quit. Participants received minimal evidence-based cessation resources following the pre-lung screening interview. RESULTS: Participants were 60.3 years old, 56.3% female, and reported a median of 40 pack-years. Participants were interested in using several evidence-based strategies, including counseling from a healthcare provider (76.7%) and receiving nicotine replacement therapy (69.8%). Pre-lung screening, 25.3% smoked ≤10 cigarettes per day, and 29.9% were ready to quit in the next 30 days. We conducted two McNemar binomial distribution tests to assess change from pre- to post-screening. At the post-lung screening assessment, approximately three-quarters reported no change on these variables. However, 23.3% reported smoking fewer cigarettes per day, whereas 4.7% reported smoking more cigarettes per day (McNemar P=0.002), and 17.2% reported increased readiness to quit, whereas 6.9% reported decreased readiness to quit (McNemar P=0.078). CONCLUSIONS: Following receipt of cessation resources and completion of lung screening, most participants reported no change in smoking outcomes. However, there was a significant reduction in cigarettes per day, and there was a trend for increased readiness to quit. This setting may provide a potential "teachable moment" and an opportunity to assist smokers with quitting. However, more proactive and intensive interventions will be necessary to capitalize on these changes and to support abstinence in the long-term.

Qualitative coronary artery calcification scores and risk of all cause, COPD and pneumonia hospital admission in a large CT lung cancer screening cohort.

BACKGROUND: Patients at high-risk for lung cancer and qualified for CT lung cancer screening (CTLS) are at risk for numerous cardio-pulmonary comorbidities. We sought to examine if qualitatively assessed coronary artery calcifications (CAC) on CTLS exams could identify patients at increased risk for non-cardiovascular events such as all cause, COPD and pneumonia related hospitalization and to verify previously reported associations between CAC and mortality and cardiovascular events. STUDY DESIGN AND METHODS: Patients (n = 4673) from Lahey Hospital and Medical Center who underwent CTLS from January 12, 2012 through September 30, 2017 were included with clinical follow-up through September 30, 2019. CTLS exams were qualitatively scored for the presence and severity of CAC at the time of exam interpretation using a four point scale: none, mild, moderate, and marked. Multivariable Cox regression models were used to evaluate the association between CT qualitative CAC and all-cause, COPD-related, and pneumonia-related hospital admissions. RESULTS: 3631 (78%) of individuals undergoing CTLS had some degree of CAC on their baseline exam: 1308 (28.0%), 1128 (24.1%), and 1195 (25.6%) had mild, moderate and marked coronary calcification, respectively. Marked CAC was associated with all-cause hospital admission and pneumonia related admissions HR 1.48; 95% CI 1.23-1.78 and HR 2.19; 95% 1.30-3.71, respectively. Mild, moderate and marked CAC were associated with COPD-related admission HR 2.30; 95% CI 1.31-4.03, HR 2.17; 95% CI 1.20-3.91 and HR 2.27; 95% CI 1.24-4.15. CONCLUSION: Qualitative CAC on CTLS exams identifies individuals at elevated risk for all cause, pneumonia and COPD-related hospital admissions.

Qualitative emphysema and risk of COPD hospitalization in a multicenter CT lung cancer screening cohort study.

BACKGROUND: In the United States, 9 to 10 million Americans are estimated to be eligible for computed tomographic lung cancer screening (CTLS). Those meeting criteria for CTLS are at high-risk for numerous cardio-pulmonary co-morbidities. The objective of this study was to determine the association between qualitative emphysema identified on screening CTs and risk for hospital admission. STUDY DESIGN AND METHODS: We conducted a retrospective multicenter study from two CTLS cohorts: Lahey Hospital and Medical Center (LHMC) CTLS program, Burlington, MA and Mount Auburn Hospital (MAH) CTLS program, Cambridge, MA. CTLS exams were qualitatively scored by radiologists at time of screening for presence of emphysema. Multivariable Cox regression models were used to evaluate the association between CT qualitative emphysema and all-cause, COPD-related, and pneumonia-related hospital admission. RESULTS: We included 4673 participants from the LHMC cohort and 915 from the MAH cohort. 57% and 51.9% of the LHMC and MAH cohorts had presence of CT emphysema, respectively. In the LHMC cohort, the presence of emphysema was associated with all-cause hospital admission (HR 1.15, CI 1.07-1.23; p < 0.001) and COPD-related admission (HR 1.64; 95% CI 1.14-2.36; p = 0.007), but not with pneumonia-related admission (HR 1.52; 95% CI 1.27-1.83; p < 0.001). In the MAH cohort, the presence of emphysema was only associated with COPD-related admission (HR 2.05; 95% CI 1.07-3.95; p = 0.031). CONCLUSION: Qualitative CT assessment of emphysema is associated with COPD-related hospital admission in a CTLS population. Identification of emphysema on CLTS exams may provide an opportunity for prevention and early intervention to reduce admission risk.

Study protocol for a telephone-based smoking cessation randomized controlled trial in the lung cancer screening setting: The lung screening, tobacco, and health trial.

Lung cancer mortality can be reduced by 20% via low dose CT lung cancer screening (LCS) and treatment of early-stage disease. Providing tobacco use treatment to high risk cigarette smokers in the LCS setting may result in health benefits beyond the impact of LCS. As one of the nine trials in the National Cancer Institute's Smoking Cessation at Lung Examination (SCALE) collaboration, the goal of the Lung Screening, Tobacco, and Health (LSTH) trial is to develop a scalable and cost-effective cessation intervention for subsequent implementation by LCS programs. Guided by the RE-AIM Framework, the LSTH trial is a two-arm RCT (N = 1330) enrolling English- and Spanish-speaking smokers registered for LCS at one of seven collaborating sites. Participants are randomly assigned to Usual Care (UC; three proactive telephone counseling sessions/two weeks of nicotine patches) vs. Intensive Telephone Counseling (ITC; eight proactive sessions/eight weeks of nicotine patches, plus discussion of the LCS results to increase motivation to quit). Telephone counseling is provided by tobacco treatment specialists. To increase continuity of care, referring physicians are notified of participant enrollment and smoking status following the intervention. Outcomes include: 1) self-reported 7-day, 30-day, and sustained abstinence, and biochemically-verified at 3-, 6-, and 12-months post-randomization, 2) reach and engagement of the interventions, and 3) cost-effectiveness of the interventions. The Cancer Intervention and Surveillance Modeling Network (CISNET) will model long-term impacts of six SCALE trials on the cost per life year saved, quality-adjusted life years saved, lung cancer mortality reduction, and population mortality. CLINICAL TRIALS REGISTRATION: The trial is registered at clinical trials.gov: NCT03200236.

Qualitative coronary artery calcium assessment on CT lung screening exam helps predict first cardiac events.

RESULTS: A total of 1,513 individuals underwent CTLS. Downstream data, pre-test cardiac risk factors and CAC scores were available for 88.3% (1,336/1,513). The average length of follow-up was 2.64 (SD ±0.72) years. There were a total of 43 events, occurring in 1.55% (6/386) of patients with mild CAC, 3.24% (11/339) of patients with moderate CAC, and 8.90% (26/292) of patients with marked CAC. There were no events among patients with no reported CAC (0/319). Using multivariable logistic modeling, the increased odds of an initial cardiac event was 2.56 (95% CI, 1.76-3.92, P<0.001) for mild CAC, 6.57 (95% CI, 3.10-15.4, P<0.001) for moderate CAC, and 16.8 (95% CI, 5.46-60.3, P<0.001) for marked CAC, as compared to individuals with no CAC. Time to event analysis showed distinct differences among the four CAC categories (P<0.001). CONCLUSIONS: Qualitative coronary artery calcification scoring of CTLS exams may provide a novel method to help select individuals at elevated risk for an initial cardiac event.

Adherence to Radiology Recommendations in a Clinical CT Lung Screening Program.

BACKGROUND: Assess patient adherence to radiologist recommendations in a clinical CT lung cancer screening program. METHODS: Patients undergoing CT lung cancer screening between January 12, 2012, and June 12, 2013, were included in this institutional review board-approved retrospective review. Patients referred from outside our institution were excluded. All patients met National Comprehensive Cancer Network Guidelines Lung Cancer Screening high-risk criteria. Full-time program navigators used a CT lung screening program management system to schedule patient appointments, generate patient result notification letters detailing the radiologist follow-up recommendation, and track patient and referring physician notification of missed appointments at 30, 60, and 90 days. To be considered adherent, patients could be no more than 90 days past due for their next recommended examination as of September 12, 2014. Patients who died, were diagnosed with cancer, or otherwise became ineligible for screening were considered adherent. Adherence rates were assessed across multiple variables. RESULTS: During the study interval, 1,162 high-risk patients were screened, and 261 of 1,162 (22.5%) outside referrals were excluded. Of the remaining 901 patients, 503 (55.8%) were male, 414 (45.9%) were active smokers, 377 (41.8%) were aged 65 to 73, and >95% were white. Of the 901 patients, 772 (85.7%) were adherent. Most common reasons for nonadherence were patient refusal of follow-up exam (66.7%), inability to successfully contact the patient (20.9%), and inability to obtain the follow-up order from the referring provider (7.8%); 23 of 901 (2.6%) were discharged for other reasons. CONCLUSIONS: High rates of adherence to radiologist recommendations are achievable for in-network patients enrolled in a clinical CT lung screening program.

Automatic Lung-RADS™ classification with a natural language processing system.

BACKGROUND: Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. METHODS: Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines®. All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. RESULTS: The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. CONCLUSIONS: An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used.

Preliminary evaluation of a telephone-based smoking cessation intervention in the lung cancer screening setting: A randomized clinical trial.

Incorporating effective smoking cessation interventions into lung cancer screening (LCS) programs will be essential to realizing the full benefit of screening. We conducted a pilot randomized trial to determine the feasibility and efficacy of a telephone-counseling (TC) smoking cessation intervention vs. usual care (UC) in the LCS setting. In collaboration with 3 geographically diverse LCS programs, we enrolled current smokers (61.5% participation rate) who were: registered to undergo LCS, 50-77 years old, and had a 20+ pack-year smoking history. Eligibility was not based on readiness to quit. Participants completed pre-LCS (T0) and post-LCS (T1) telephone assessments, were randomized to TC (N=46) vs. UC (N=46), and completed a final 3-month telephone assessment (T2). Both study arms received a list of evidence-based cessation resources. TC participants also received up to 6 brief counseling calls with a trained cessation counselor. Counseling calls incorporated motivational interviewing and utilized the screening result as a motivator for quitting. The outcome was biochemically verified 7-day point prevalence cessation at 3-months post-randomization. Participants (56.5% female) were 60.2 (SD=5.4) years old and reported 47.1 (SD=22.2) pack years; 30% were ready to stop smoking in the next 30 days. TC participants completed an average of 4.4 (SD=2.3) sessions. Using intent-to-treat analyses, biochemically verified quit rates were 17.4% (TC) vs. 4.3% (UC), p<.05. This study provides preliminary evidence that telephone-based cessation counseling is feasible and efficacious in the LCS setting. As millions of current smokers are now eligible for lung cancer screening, this setting represents an important opportunity to exert a large public health impact on cessation among smokers who are at very high risk for multiple tobacco-related diseases. If this evidence-based, brief, and scalable intervention is replicated, TC could help to improve the overall cost-effectiveness of LCS. TRIAL REGISTRATION: NCT02267096, https://clinicaltrials.gov.