Low-dose Computed Tomography Screening Research Articles

Early candidate nasal swab classifiers developed using machine learning and whole transcriptome sequencing may improve early lung cancer detection.

8551 Background: The goal of lung nodule management is to make an early diagnosis in patients with lung cancer while avoiding unnecessary, costly and potentially harmful procedures in patients with benign lesions. Increased implementation of low dose CT screening will lead to increased numbers of both benign and malignant nodules that will require effective management. We have previously described the feasibility of detecting gene expression changes associated with lung cancer (“field of injury”) in nasal epithelium utilizing whole transcriptome RNA sequencing from non-invasive nasal brush samples. Using this approach, we now report the performance of candidate nasal classifiers that combine both genomic and clinical features to risk stratify lung nodules from ever-smokers to aid in the diagnosis of lung cancer. Methods: Patients from several clinical cohorts who were ever-smokers with a lung nodule < 30 mm and without a history of prior cancer underwent nasal epithelium sampling. All patients had at least one year of follow up or until a final diagnosis of benign or malignant nodule was made. Candidate classifiers were developed using whole-transcriptome RNA sequencing and machine learning. Training of these classifiers included genomic and clinical information (age, sex, pack-years, years-since-quit, nodule size and nodule spiculation). Two decision boundaries were chosen to maximize sensitivity and specificity for low and high-risk nodules, respectively. The performance of these classifiers was evaluated using cross-validation (CV). Results: All candidate nasal classifiers underwent CV assessment on over 700 patients with lung nodules. All candidate classifiers achieved CV performance of > 40% specificity at 95% sensitivity in low- risk nodules and all candidate classifiers achieved CV performance of > 60% sensitivity at 90% specificity in high-risk nodules. The classifiers stratified benign nodules as low- risk with > 95% negative predictive value (NPV), intermediate risk nodules were stratified as 5-65% risk and malignant nodules were stratified as high- risk with > 65% positive predictive value (PPV) in a population with estimated 25% prevalence. This performance was robust across subgroups of age ( < 65 year vs. >65 year), sex, and current versus former smokers. Conclusions: The nasal genomic-clinical candidate classifiers have a high NPV effectively identifying benign nodules when calling them low- risk, thereby, informing decisions to more safely avoid a diagnostic workup. Additionally, the high PPV of these classifiers identifies malignant nodules when calling them high- risk and informs decisions regarding the urgency of a further diagnostic work-up. A nasal genomic-clinical classifier has the potential to serve as a non-invasive tool for lung cancer risk-stratification to help inform decision making in patients with lung nodules.

Early detection of lung cancer with an incidental lung nodule program (ILNP).

8553 Background: Lung cancer early detection improves survival, but risk-based low-dose CT screening (LDCT) only identifies a minority of patients. We implemented an ILNP in a community healthcare system, and evaluated its risks and benefits. Methods: Patients with lung lesions on routinely-performed radiologic studies were flagged by radiologists and triaged using evidence-based guidelines. We tracked demographics, clinical characteristics, procedures, complications, and health outcomes. We analyzed ILNP subjects’ eligibility for LDCT by National Lung Screening Trial (NLST), Center for Medicaid Services (CMS), NEderlands Leuvens Screening ONderzoek (NELSON), National Comprehensive Cancer Network (NCCN) Risk Groups 1 and 2 (screening recommended), NCCN Risk Group 3 (screening not currently recommended), and US Preventive Services Task Force (USPSTF) criteria from 2013 and 2020. Statistical analysis used the chi-square test and Kaplan Meier method. Results: From 2015-2020, 13,710 patients were evaluated in the ILNP program: median age, 64 years; 42% male; 65% White, 29% Black; 667 (4.9%) were diagnosed with lung cancer. Lung cancers diagnosed from ILNP were 39% adenocarcinoma / 20% Squamous Cell with clinical stage distribution 49% I, 8% II, 17% III, and 16% IV. 832 (6.1%) had invasive diagnostic testing- CT-guided biopsy (50%), bronchoscopy (30%), and/or EBUS (26%); 11% of the 832 had >1 invasive diagnostic test. The most common complications from invasive testing were pneumothorax and chest tube placement. Only 11%-20% of all ILNP patients would have been eligible for LDCT. In ILNP patients diagnosed with lung cancer, only 33% were eligible for screening by NLST criteria; the proportion increased substantially when USPSTF 2020 or NCCN Group 2 criteria were applied (Table). Compared to NLST, NCCN Group 2 criteria increased screening eligibility among cancer patients by 22% (from 33% to 55%), while only increasing screening eligibility by 6% (from 8% to 14%) in non-cancer patients. Aggregate 1-year and 3-year survival rates for lung cancer patient diagnosed through ILNP were 76% (95% CI: 73, 80) and 64% (95% CI: 59, 69). Conclusions: The ILNP identified early-stage lung cancer more frequently than most LDCT programs, with promising survival rates. The majority of subjects with lung cancer were not eligible for LDCT, we still need to optimize risk-based screening criteria. Even with new, expanded criteria for LDCT, structured ILNP is necessary to expand early detection of lung cancer.[Table: see text]

Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT

Background Accurate estimation of the malignancy risk of pulmonary nodules at chest CT is crucial for optimizing management in lung cancer screening. Purpose To develop and validate a deep learning (DL) algorithm for malignancy risk estimation of pulmonary nodules detected at screening CT. Materials and Methods In this retrospective study, the DL algorithm was developed with 16 077 nodules (1249 malignant) collected -between 2002 and 2004 from the National Lung Screening Trial. External validation was performed in the following three -cohorts -collected between 2004 and 2010 from the Danish Lung Cancer Screening Trial: a full cohort containing all 883 nodules (65 -malignant) and two cancer-enriched cohorts with size matching (175 nodules, 59 malignant) and without size matching (177 -nodules, 59 malignant) of benign nodules selected at random. Algorithm performance was measured by using the area under the receiver operating characteristic curve (AUC) and compared with that of the Pan-Canadian Early Detection of Lung Cancer (PanCan) model in the full cohort and a group of 11 clinicians composed of four thoracic radiologists, five radiology residents, and two pulmonologists in the cancer-enriched cohorts. Results The DL algorithm significantly outperformed the PanCan model in the full cohort (AUC, 0.93 [95% CI: 0.89, 0.96] vs 0.90 [95% CI: 0.86, 0.93]; P = .046). The algorithm performed comparably to thoracic radiologists in cancer-enriched cohorts with both random benign nodules (AUC, 0.96 [95% CI: 0.93, 0.99] vs 0.90 [95% CI: 0.81, 0.98]; P = .11) and size-matched benign nodules (AUC, 0.86 [95% CI: 0.80, 0.91] vs 0.82 [95% CI: 0.74, 0.89]; P = .26). Conclusion The deep learning algorithm showed excellent performance, comparable to thoracic radiologists, for malignancy risk estimation of pulmonary nodules detected at screening CT. This algorithm has the potential to provide reliable and reproducible malignancy risk scores for clinicians, which may help optimize management in lung cancer screening. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Tammemägi in this issue.

Analysis of low-dose computed tomography compliance and related factors among high-risk population of lung cancer in three provinces participating in the cancer screening program in urban China

Objective: To analyze the compliance and related factors of low-dose computed tomography (LDCT) screening among the high-risk population of lung cancer in three provinces participating in the cancer early diagnosis and early treatment program in urban areas of China. Methods: From October 2017 to October 2018, 17 983 people aged between 40 and 74 years old at high risk of lung cancer were recruited from Zhejiang, Anhui and Liaoning provinces. The basic demographic characteristics, living habits, history of the disease and family history of cancer were collected by using a cancer risk assessment questionnaire, and the data of participants examined by LDCT were obtained from the hospitals participating in the program. The screening compliance was quantified by the screening participation rate, and it was calculated as the proportion of participants completing LDCT scan among high-risk population. The related factors of LDCT screening compliance were analyzed by using a multivariate logistic regression model. Results: The age of 17 983 participants was (56.52±8.22) years old. Males accounted for 51.9% (N=9 332), and 69.5% (N=12 495) had ever smoked, including former smokers and current smokers. A total of 6 269 participants were screened by LDCT, and the screening participation rate was 34.86%. The results of multivariate logistic regression analysis showed that the age group of 50 to 69 years old, female, passive smokers, alcohol consumption, family history of lung cancer and history of chronic respiratory diseases were more likely to be screened by LDCT, while the compliance of LDCT screening in current smokers was low. Conclusions: The LDCT screening compliance of the high-risk population of lung cancer in urban areas of China still needs to be improved. Age, sex, smoking, drinking, family history of lung cancer and history of chronic respiratory disease are associated with screening compliance.

Advancing health equity in cancer care: The lived experiences of poverty and access to lung cancer screening.

Individuals living with low income are more likely to smoke, have a higher risk of lung cancer, and are less likely to participate in preventative healthcare (i.e., low-dose computed tomography (LDCT) for lung cancer screening), leading to equity concerns. To inform the delivery of an organized pilot lung cancer screening program in Ontario, we sought to contextualize the lived experiences of poverty and the choice to participate in lung cancer screening. At three Toronto academic primary-care clinics, high-risk screen-eligible patients who chose or declined LDCT screening were consented; sociodemographic data was collected. Qualitative interviews were conducted. Theoretical thematic analysis was used to organize, describe and interpret the data using the morphogenetic approach as a guiding theoretical lens. Eight participants chose to undergo screening; ten did not. From interviews, we identified three themes: Pathways of disadvantage (social trajectories of events that influence lung-cancer risk and health-seeking behaviour), lung-cancer risk and early detection (upstream factors that shape smoking behaviour and lung-cancer screening choices), and safe spaces of care (care that is free of bias, conflict, criticism, or potentially threatening actions, ideas or conversations). We illuminate how 'choice' is contextual to the availability of material resources such as income and housing, and how 'choice' is influenced by having access to spaces of care that are free of judgement and personal bias. Underserved populations will require multiprong interventions that work at the individual, system and structural level to reduce inequities in lung-cancer risk and access to healthcare services such as cancer screening.

Lung cancer screening: who pays? who receives?-the Chinese perspective.

The National Lung Screening Trial (NLST) revealed that low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20.0%. In China, LDCT is very cheap and easy to access. As a result, LDCT screening is not limited to “high-risk” population defined by the NLST trial. The results of LDCT screening in China are also quite different from that in Western countries. LDCT detected lung cancer in a significant proportion of young, female and non-smokers in China. There is also a higher proportion of adenocarcinoma (ADC), a lower proportion of squamous cell carcinoma, and a higher proportion of early-stage 0/I disease among LDCT-detected lung cancer in China. The issue of overdiagnosis and overtreatment is discussed. Finally, we call the global attention to clarify the etiology of lung cancer in young female non-smokers.

The person behind the nodule: a narrative review of the psychological impact of lung cancer screening.

Lung cancer is the leading cause of cancer mortality globally, responsible for an estimated 1.76 million deaths worldwide in 2018 alone. Screening adults at high risk of lung cancer using low-dose computed tomography (LDCT) significantly reduces lung cancer mortality by finding the disease at an early, treatable stage. Many countries are actively considering whether to implement screening for their high-risk populations in light of the recently published Dutch-Belgian trial ‘NELSON’. In deciding whether to implement a national screening programme, policymakers must weigh up the evidence for the relative risks posed to the entire screened population, including the potential psychological burden. This narrative review aimed to critically summarise the evidence for both negative and positive psychological responses experienced throughout the LDCT screening pathway, to describe their magnitude, duration and clinical relevance, and to draw out different aspects of measurement design crucial to their interpretation. A further aim was to discuss the available evidence for individual differences in psychological response, as well as interventions designed to promote psychological well-being. In summary, there was no evidence that the LDCT screening process caused adverse psychological outcomes overall, although those receiving indeterminate and suspicious LDCT results did report clinically raised anxiety and lung cancer-specific distress in the short-term. There was early evidence that demographic factors, smoking status and screening-ineligibility could be associated with individual differences in propensity to experience distress. Qualitative data suggested health beliefs could be modifiable mediators of these individual differences, but their aetiology requires quantitative and prospective research. There was also some evidence of positive psychological responses that could be capitalised on, and of the potential for person-centred communication interventions to achieve this. Further research needs to be embedded in real-world LDCT lung cancer screening services and use condition-specific measures to monitor outcomes and test evidence-based communication interventions in promoting psychological well-being.

Q&A: Ned Sharpless on COVID-19 and Cancer Prevention.

Q&A: Ned Sharpless on COVID-19 and Cancer Prevention.

Deep Learning-Quantified Calcium Scores for Automatic Cardiovascular Mortality Prediction at Lung Screening Low-Dose CT.

To examine the prognostic value of location-specific arterial calcification quantities at lung screening low-dose CT for the prediction of cardiovascular disease (CVD) mortality. This retrospective study included 5564 participants who underwent low-dose CT from the National Lung Screening Trial between August 2002 and April 2004, who were followed until December 2009. A deep learning network was trained to quantify six types of vascular calcification: thoracic aorta calcification (TAC); aortic and mitral valve calcification; and coronary artery calcification (CAC) of the left main, the left anterior descending, and the right coronary artery. TAC and CAC were determined in six evenly distributed slabs spatially aligned among chest CT images. CVD mortality prediction was performed with multivariable logistic regression using least absolute shrinkage and selection operator. The methods were compared with semiautomatic baseline prediction using self-reported participant characteristics, such as age, history of smoking, and history of illness. Statistical significance between the prediction models was tested using the nonparametric DeLong test. The prediction model was trained with data from 4451 participants (median age, 61 years; 37.9% women) and then tested on data from 1113 participants (median age, 61 years; 37.9% women). The prediction model using calcium scores achieved a C statistic of 0.74 (95% CI: 0.69, 0.79), and it outperformed the baseline model using only participant characteristics (C statistic, 0.69; P = .049). Best results were obtained when combining all variables (C statistic, 0.76; P < .001). Five-year CVD mortality prediction using automatically extracted image-based features is feasible at lung screening low-dose CT.© RSNA, 2021.

Patient Adherence in an Academic Medical Center's Low-dose Computed Tomography Screening Program.

Low-dose computed tomography (LDCT) screening is an important tool for reducing lung cancer mortality. This study describes a single center's experience with LDCT and attempts to identify any barriers to compliance with standard guidelines. This is a retrospective review of a single university-based hospital system from 2015 to 2019. All individuals who met eligibility for lung cancer screening were entered into a database. The definition of adherence with the screening program was determined by the recommended timeline for the follow-up LDCT. Cohorts were split by adherence and demographics were compared. A total of 203 LDCTs were performed in 121 patients who met eligibility for LDCT and had appropriate surveillance from 2015 to 2019. The average age was 64 years old. The overall adherence rate for prescribed LDCTs was 59.1%. Patients with Lung-RADS score 2 had 2.43 times higher odds of adherence relative to patients with Lung-RADS score 1 (odds ratio [OR]=2.43; 95% confidence interval [CI]: 1.23-4.83; P=0.011). African American patients had 42% lower odds of adherence relative to white patients (OR=0.58; 95% CI: 0.32-1.06; P=0.076). Patients with non-District of Columbia zip codes had 57% higher odds of adherence relative to those with District of Columbia zip codes, although this did not reach statistical significance (OR=1.57; 95% CI: 0.87-2.82; P=0.136). Despite the implementation of a multidisciplinary, academic LDCT screening program, overall adherence rate to prescribed follow-up scans was suboptimal. Socioeconomic disparities and African American race may negatively affect adherence to lung cancer screening LDCT guidelines. Patients with concerning findings on initial LDCT had a higher association of adherence to guidelines.

Low positive predictive value of computed tomography screening for lung cancer irrespective of commonly employed definitions of target population.

Screening for lung cancer (LC) by low-dose computed tomography (LDCT) has been demonstrated to reduce LC mortality in randomized clinical trials (RCTs), and its implementation is in preparation in many countries. However, definition of the target population, which was based on various combinations of age ranges and definitions of heavy smoking in the RCTs, is subject to ongoing debate. Using epidemiological data from Germany, we aimed to estimate prevalence of preclinical LC and positive predictive value (PPV) of LDCT in potential target populations defined by age and smoking history. Populations aged 50 to 69, 55 to 69, 50 to 74 and 55 to 79 years were considered in this analysis. Sex-specific prevalence of preclinical LC was estimated using LC incidence data within those age ranges and annual transition rates from preclinical to clinical LC obtained by meta-analysis. Prevalence of preclinical LC among heavy smokers (defined by various pack-year thresholds) within those age ranges was estimated by combining LC prevalence in the general population with proportions of heavy smokers and relative risks for LC among them derived from epidemiological studies. PPVs were calculated by combining these prevalences with sensitivity and specificity estimates of LDCT. Estimated prevalence of LC was 0.3% to 0.5% (men) and 0.2% to 0.3% (women) in the general population and 0.8% to 1.7% in target populations of heavy smokers. Estimates of PPV of LDCT were <20% for all definitions of target populations of heavy smokers. Refined preselection of target populations would be highly desirable to increase PPV and efficiency of LDCT screening and to reduce numbers of false-positive LDCT findings.

The importance of low-dose CT screening to identify emphysema in asymptomatic participants with and without a prior diagnosis of COPD

PurposeChronic Obstructive Pulmonary Disease (COPD) includes chronic bronchitis, small airways disease, and emphysema. Diagnosis of COPD requires spirometric evidence and may be normal even when small airways disease or emphysema is present. Emphysema increases the risk of exacerbations, and is associated with all-cause mortality and increased risk of lung cancer. We evaluated the prevalence of emphysema in participants with and without a prior history of COPD. MethodsWe reviewed a prospective cohort of 52,726 subjects who underwent baseline low dose CT screening for lung cancer from 2003 to 2016 in the International Early Lung Cancer Action Program. ResultsOf 52,726 participants, 23.8%(12,542) had CT evidence of emphysema. Of these 12,542 participants with emphysema, 76.5%(9595/12,542) had no prior COPD diagnosis even though 23.6% (2258/9595) had moderate or severe emphysema. Among 12,542 participants, significant predictors of no prior COPD diagnosis were: male (OR = 1.47, p < 0.0001), younger age (ORage10 = 0.72, p < 0.0001), lower pack-years of smoking (OR10pack-years = 0.90, p < 0.0001), completed college or higher (OR = 1.54, p < 0.0001), no family history of lung cancer (OR = 1.12, p = 0.04), no self-reported cardiac disease (OR = 0.76, p = 0.0003) or hypertension (OR = 0.74, p < 0.0001). The severity of emphysema was significantly lower among the 9595 participants with no prior COPD diagnosis, the OR for moderate emphysema was ORmoderate = 0.58(p = 0.0007) and for severe emphysema, it was ORsevere = 0.23(p < 0.0001). ConclusionEmphysema was identified in 23.8% participants undergoing LDCT and was unsuspected in 76.5%. LDCT provides an opportunity to identify emphysema, and recommend smoking cessation.

Low‐dose CT lung cancer screening uptake: A rural–urban comparison

The US Preventive Services Task Force recommends lung cancer screening with Low-Dose Computed Tomography (LDCT) in high-risk individuals. Our objective was to identify demographic, health, and financial factors associated with screening uptake, with a focus on urban-rural differences. We analyzed data from the 2018 and 2019 Behavioral Risk Factor Surveillance System and its optional Lung Cancer Screening Module to examine factors associated with screening uptake among 20 states that administered the optional module. We compared differences in factors associated with uptake overall and by geographical regions and conducted multivariable logistic mixed-effects regression, accounting for participant clustering by state to assess the impact of these factors on uptake. Overall 1,268 participants underwent LDCT screening with no significant differences observed between rural (16.3%) and urban residents (17.7%, p = 0.67). In multivariable models, rural residents did not differ significantly in their LDCT screening uptake (OR = 0.85; 95% CI: 0.67-1.09, p = 0.20), but uptake was significantly higher for participants with underlying chronic respiratory conditions, veterans, those with higher pack-year history, and those with poor/fair general health and prior history of cancer. Uptake declined with age, higher education level, concerns about paying for medical care, and lack of primary care. Modifiable targets can be leveraged to increase LDCT screening. Based on significant predictors of screening uptake, clinicians should prioritize interventions that effectively consider smoking history as well as those identified as effective in veterans' health settings. Additionally, reducing structural barriers to care related to insurance and income will be key to reducing disparities.

Optimum diameter threshold for lung nodules at baseline lung cancer screening with low-dose chest CT: exploration of results from the Korean Lung Cancer Screening Project.

To explore the optimum diameter threshold for solid nodules to define positive results at baseline screening low-dose CT (LDCT) and to compare two-dimensional and volumetric measurement of lung nodules for the diagnosis of lung cancers. We included consecutive participants from the Korean Lung Cancer Screening project between 2017 and 2018. The average transverse diameter and effective diameter (diameter of a sphere with the same volume) of lung nodules were measured by semi-automated segmentation. Diagnostic performances for lung cancers diagnosed within 1 year after LDCT were evaluated using area under receiver-operating characteristic curves (AUCs), sensitivities, and specificities, with diameter thresholds for solid nodules ranging from 6 to 10 mm. The reduction of unnecessary follow-up LDCTs and the diagnostic delay of lung cancers were estimated for each threshold. Fifty-two lung cancers were diagnosed among 10,424 (10,141 men; median age 62 years) participants within 1 year after LDCT. Average transverse (0.980) and effective diameters (0.981) showed similar AUCs (p = .739). Elevating the average transverse diameter threshold from 6 to 9 mm resulted in a significantly increased specificity (91.7 to 96.7%, p < .001), a modest reduction in sensitivity (96.2 to 94.2%, p = .317), a 60.2% estimated reduction of unnecessary follow-up LDCTs, and a diagnostic delay in 1.9% of lung cancers. Elevating the threshold to 10 mm led to a significant reduction in sensitivity (86.5%, p = .025). Elevating the diameter threshold for solid nodules from 6 to 9 mm may lead to a substantial reduction in unnecessary follow-up LDCTs with a small proportion of diagnostic delay of lung cancers. • Elevation of the diameter threshold for solid nodules from 6 to 9 mm can substantially reduce unnecessary follow-up LDCTs with a small proportion of diagnostic delay of lung cancers. • The average transverse and effective diameters of lung nodules showed similar performances for the prediction of a lung cancer diagnosis.

Interobserver variability in Lung CT Screening Reporting and Data System categorisation in subsolid nodule-enriched lung cancer screening CTs.

To assess interobserver agreement in Lung CT Screening Reporting and Data System (Lung-RADS) categorisation in subsolid nodule-enriched low-dose screening CTs. A retrospective review of low-dose screening CT reports from 2013 to 2017 using keyword searches for subsolid nodules identified 54 baseline CT scans. With an additional 108 negative screening CT scans, a total of 162 CT scans were categorised according to the Lung-RADS by two fellowship-trained thoracic radiologists in consensus. We randomly selected 20, 20, 10, and 10 scans from categories 1/2, 3, 4A, and 4B CT scans, respectively, to ensure balanced category representation. Five radiologists classified the 60 CT scans into Lung-RADS categories. The frequencies of concordance and minor and major discordance were calculated, with major discordance defined as at least 6 months of management discrepancy. We used Cohen's κ statistics to analyse reader agreement. An average of 60.3% (181 of 300) of all cases and 45.0% (90 of 200) of positive screens were correctly categorised. The minor and major discordance rates were 12.3% and 27.3% overall and 18.5% and 36.5% in positive screens, respectively. The concordance rate was significantly higher among experienced thoracic radiologists. Overall, the interobserver agreement was moderate (mean κ, 0.45; 95% confidence interval: 0.40-0.51). The proportion of part-solid risk-dominant nodules was significantly higher in cases with low rates of accurate categorisation. This retrospective study observed variable accuracy and moderate interobserver agreement in radiologist categorisation of subsolid nodules in screening CTs. This inconsistency may affect management recommendations for lung cancer screening. • Diagnostic performance for Lung-RADS categorisation is variable among radiologists with fair to moderate interobserver agreement in subsolid nodule-enriched CT scans. • Experienced thoracic radiologists showed more accurate and consistent Lung-RADS categorisation than radiology residents. • The relative abundance of part-solid nodules was a potential factor related to increased disagreement in Lung-RADS categorisation.

Assessment and Efficacy of Low-Dose CT Screening and Primary Care Providers Perspective on Lung Cancer Screening: An Institutional Review.

Lung cancer is the most common cause of death in both men and women. The United States Preventive Services Task Force (USPSTF) recommends annual lung screening with low-dose computed tomography (LDCT) chest for individuals aged 55-80 who have a 30 pack-year smoking history and currently smoke or have quit within the past 15 years. We reviewed the electronic medical records of patients visiting our outpatient clinic over a period of one year. We included all eligible individuals according to USPSTF guidelines for LDCT to identify screening rates at our institution. All primary care physicians, including residents and attendings, were given a prepared questionnaire to understand their beliefs and concerns with the implementation of this program. A total of 13,500 patients visited the outpatient clinic and 1178 were eligible for LDCT. Forty-five percent (45%) of patients received LDCT screening, which was higher than the national average of 2%-5%. A total of 50 primary care providers were included in the survey. The majority of the providers were aware of the USPSTF guidelines and believed that patients with multiple comorbidities and insurance issues were barriers in initiating LDCT screening. Lung cancer screening is an important component in cancer preventive strategies. Widespread awareness among the primary care providers and the public is extremely necessary for improving the use of LDCT.

Molecular approaches to lung cancer prevention.

Lung cancer is generally diagnosed at advanced stages when surgical resection is not possible. Late diagnosis, along with development of chemoresistance, results in high mortality. Preventive approaches, including smoking cessation, chemoprevention and early detection are needed to improve survival. Smoking cessation combined with low-dose computed tomography screening has modestly improved survival. Chemoprevention has also shown some promise. Despite these successes, mostlung cancer cases remain undetected untiladvanced stages. Additional early detection strategies may further improve survival and treatment outcome. Molecular alterations taking place during lung carcinogenesis have the potential to be used in early detection via noninvasive methods and may also serve as biomarkers for success of chemopreventive approaches. This review focuses on theutilization of molecular biomarkers to increase the efficacy of various preventive approaches.

Risk Perception Among a Lung Cancer Screening Population

A successful lung cancer screening program requires a patient cohort at sufficient risk of developing cancer who are willing to participate. Among other factors, a patient's lung cancer risk perception may inform their attitudes toward screening and smoking cessation programs. This study analyzed data from the Pan-Canadian Early Detection of Lung Cancer (PanCan) Study to address the following questions: Which factors are associated with the perception of lung cancer risk? Is there an association between risk perception for lung cancer and actual calculated risk? Is there an association between risk perception for lung cancer and the intent to quit smoking? Are there potential targets for lung cancer screening awareness? The PanCan study recruited current or former smokers aged 50 to 75 years who had at least a 2%risk of developing lung cancer over 6 years to undergo low-dose screening CT. Risk perception and worry about lung cancer were captured on a baseline questionnaire. Cumulative logistic regression analysis was used to assess the relationship between baseline risk variables and both lung cancer risk perception and worry. Among the 2,514 individuals analyzed, a higher perceived risk of lung cancer was positively associated with calculated risk (P= .032). Younger age, being a former smoker, respiratory symptoms, lower FEV1, COPD, and a family history of lung cancer were associated with higher perceived risk. Conversely, a consistent relationship between calculated risk and worry was not identified. There was a positive association between risk perception and lung cancer worry and reported intent to quit smoking. Individuals' lung cancer risk perception correlated positively with calculated risk in a screening population. Promotion of screening programs may benefit from focusing on factors associated with higher risk perception; conversely, harnessing worry seemingly holds less value.

PS01.02 National Lung Cancer Screening Program in Taiwan: The TALENT Study

Lung cancer in never-smoker is a global rising threat especially in East Asia. Our recent proteogenomics study has revealed the demographically distinct signatures of oncogenesis and progression of this dreadful disease and provide new insights into the precision management of early lung cancer. Currently, early detection is the most effective way to improve lung cancer survival. Low-dose computed tomography (LDCT) has been proven effective for lung cancer screening. However, most of the lung cancer screenings focused on heavy smoker which may not be suitable for East Asian population. In Taiwan, lung cancer is the leading cause of cancer mortality and 53% were never-smoker. We therefore conducted a nationwide lung cancer LDCT screening focused on never-smoker (TALENT: Taiwan Lung Cancer Screening for Never Smoker Trial) aiming to develop an effective strategy for screening of lung cancer in never-smoker and establish a risk prediction model to identify high-risk population that may benefit from LDCT screening. Here we report on behalf of the TALENT study group the first round (T0) results. This is a prospective, multicenter study sponsored by The Ministry of Health and Welfare, Taiwan. The inclusion criteria were age between 55-75 years, never-smoker and having one of the following risks: family history of lung cancer within third-degree, passive smoking exposure, TB/COPD, cooking index ≥ 110, and not using ventilator during cooking. The LDCT was conducted according to the guideline suggested by ACR. A solid or part-solid (PS) nodule larger than 6 mm or pure ground glass nodule (GGN) larger than 5 mm in diameter was designated as positive on LDCT. The PBMC DNA was obtained for SNP typing analysis. Institutional Review Board approved the study and informed consent was obtained from each participating subject. From Feb. 2015 to July 2019, a total of 12,011 subjects (Table 1) were enrolled. Among them, 6,012 (50.1%) had lung cancer family history, 5,999 (49.9%) did not. In 12,011 scans, 2,094 (17.4%) were considered positive, there were 392 subjects (3.3%) underwent lung biopsies or surgeries at T0, lung cancer (2.6%) were diagnosed in 311 subjects, 254 (2.1%) were invasive lung cancer. All but one was adenocarcinoma and 96.5% were stage 0 or I, 81 had benign lung disease or malignancy other than primary lung cancer. The prevalence of lung cancer was 3.2% and 2.0% in subjects with and without lung cancer family history, respectively. The prevalence of invasive lung cancer was 2.6% and 1.6%, respectively. For subjects with lung cancer family history, the prevalence of lung cancer was 3.3%, 1.6% and 1.7% in those with 1st degree, 2nd degree and 3rd degree families had lung cancer, respectively. The TALENT study confirmed the effectiveness of LDCT screening in a pre-defined, never-smoker high-risk population. The T0 lung cancer detection rate was 2.6%, which was even higher than NLST study (1.1%) and NELSON study (0.9%). Most importantly, 96.5% patients were stage 0 or 1, that were potentially curable by surgery. Our study also revealed the high risk of family history, especially those subjects with 1st degree families had lung cancer.

MA05.08 Impact of Low-Dose CT Screening for Primary Lung Cancer on Subsequent Risk of Brain Metastasis: Secondary Analysis of NLST

Brain metastasis (BrM) is one of the most common metastases from primary lung cancer (LC). Prior studies have shown that 40% of LC patients develop BrM during the course of their diseases. Recently, the National Lung Screening Trial (NLST) demonstrated that low-dose computed tomography (LDCT) screening (vs chest X-Ray) reduces LC mortality by 20%. This has resulted in USPSTF recommendation of annual LDCT screening for individuals at high risk for LC. Despite the recent adoption of LDCT screening, it remains unknown if early detection of LC through LDCT screening may be potentially beneficial in reducing the risk of developing metastases from primary LC.