Reduce Lung Cancer Mortality Research Articles

Bio-inspired swarm-intelligent with machine learning framework for prediction and classification of lung cancer

Early detection of lung cancer nodules, which is often dependent on a tomography scan filmic examination, greatly increases the probability of survival. Earlier tumor detection reduces lung cancer mortality by increasing the likelihood of successful therapy. Traditionally, radiologists have analyzed medical pictures for signs of lung cancer using a laborious and inaccurate systematic approach. The confidentiality and integrity of medical data have become a serious challenge for healthcare applications as a result of the tremendous improvement in the transmission of medical data in the healthcare sector. This research makes use of computational intelligence methods. In this research, a brand-new Enhanced vortex search algorithm optimized Support Vector Machine (EVSAO-SVM) is developed for detection and classification. Preprocessing using the Gaussian Filter, segmentation with Otsu thresholding, feature extraction with local binary patterns (LPB), and classification and prediction with the EVSAO-SVM are the processes that are simulated. Regarding performance criteria including accuracy, sensitivity, specificity, and F1-measure, this study indicates the suggested framework's superiority over the traditional approaches. The results of the tests conducted demonstrate that the suggested model can reach up to 95.42 percent sensitivity, 96.24 percent accuracy, 98.92 percent specificity, and 94.26 percent F1 measure.

Systematic Review of Lung Cancer Screening: Advancements and Strategies for Implementation.

Lung cancer is the leading cause of cancer-related deaths in Europe, with low survival rates primarily due to late-stage diagnosis. Early detection can significantly improve survival rates, but lung cancer screening is not currently implemented in Italy. Many countries have implemented lung cancer screening programs for high-risk populations, with studies showing a reduction in mortality. This review aimed to identify key areas for establishing a lung cancer screening program in Italy. A literature search was conducted in October 2022, using the PubMed and Scopus databases. Items of interest included updated evidence, approaches used in other countries, enrollment and eligibility criteria, models, cost-effectiveness studies, and smoking cessation programs. A literature search yielded 61 scientific papers, highlighting the effectiveness of low-dose computed tomography (LDCT) screening in reducing mortality among high-risk populations. The National Lung Screening Trial (NLST) in the United States demonstrated a 20% reduction in lung cancer mortality with LDCT, and other trials confirmed its potential to reduce mortality by up to 39% and detect early-stage cancers. However, false-positive results and associated harm were concerns. Economic evaluations generally supported the cost-effectiveness of LDCT screening, especially when combined with smoking cessation interventions for individuals aged 55 to 75 with a significant smoking history. Implementing a screening program in Italy requires the careful consideration of optimal strategies, population selection, result management, and the integration of smoking cessation. Resource limitations and tailored interventions for subpopulations with low-risk perception and non-adherence rates should be addressed with multidisciplinary expertise.

A diagnostic classification of lung nodules using multiple-scale residual network

Computed tomography (CT) scans have been shown to be an effective way of improving diagnostic efficacy and reducing lung cancer mortality. However, distinguishing benign from malignant nodules in CT imaging remains challenging. This study aims to develop a multiple-scale residual network (MResNet) to automatically and precisely extract the general feature of lung nodules, and classify lung nodules based on deep learning. The MResNet aggregates the advantages of residual units and pyramid pooling module (PPM) to learn key features and extract the general feature for lung nodule classification. Specially, the MResNet uses the ResNet as a backbone network to learn contextual information and discriminate feature representation. Meanwhile, the PPM is used to fuse features under four different scales, including the coarse scale and the fine-grained scale to obtain more general lung features of the CT image. MResNet had an accuracy of 99.12%, a sensitivity of 98.64%, a specificity of 97.87%, a positive predictive value (PPV) of 99.92%, and a negative predictive value (NPV) of 97.87% in the training set. Additionally, its area under the receiver operating characteristic curve (AUC) was 0.9998 (0.99976–0.99991). MResNet's accuracy, sensitivity, specificity, PPV, NPV, and AUC in the testing set were 85.23%, 92.79%, 72.89%, 84.56%, 86.34%, and 0.9275 (0.91662–0.93833), respectively. The developed MResNet performed exceptionally well in estimating the malignancy risk of pulmonary nodules found on CT. The model has the potential to provide reliable and reproducible malignancy risk scores for clinicians and radiologists, thereby optimizing lung cancer screening management.

Integrating Smoking Cessation Into Low-Dose Computed Tomography Lung Cancer Screening: Results of the Ontario, Canada Pilot

IntroductionLow-dose computed tomography screening in high-risk individuals reduces lung cancer mortality. To inform the implementation of a provincial lung cancer screening program, Ontario Health undertook a Pilot study, which integrated smoking cessation (SC). MethodsThe impact of integrating SC into the Pilot was assessed by the following: rate of acceptance of a SC referral; proportion of individuals who were currently smoking cigarettes and attended a SC session; the quit rate at 1 year; change in the number of quit attempts; change in Heaviness of Smoking Index; and relapse rate in those who previously smoked. ResultsA total of 7768 individuals were recruited predominantly through primary care physician referral. Of these, 4463 were currently smoking and were risk assessed and referred to SC services, irrespective of screening eligibility: 3114 (69.8%) accepted referral to an in-hospital SC program, 431 (9.7%) to telephone quit lines, and 50 (1.1%) to other programs. In addition, 4.4% reported no intention to quit and 8.5% were not interested in participating in a SC program. Of the 3063 screen-eligible individuals who were smoking at baseline low-dose computed tomography scan, 2736 (89.3%) attended in-hospital SC counseling. The quit rate at 1 year was 15.5% (95% confidence interval: 13.4%–17.7%; range: 10.5%–20.0%). Improvements were also observed in Heaviness of Smoking Index (p < 0.0001), number of cigarettes smoked per day (p < 0.0001), time to first cigarette (p < 0.0001), and number of quit attempts (p < 0.001). Of those who reported having quit within the previous 6 months, 6.3% had resumed smoking at 1 year. Furthermore, 92.7% of the respondents reported satisfaction with the hospital-based SC program. ConclusionsOn the basis of these observations, the Ontario Lung Screening Program continues to recruit through primary care providers, to assess risk for eligibility using trained navigators, and to use an opt-out approach to referral for cessation services. In addition, initial in-hospital SC support and intensive follow-on cessation interventions will be provided to the extent possible.

Lung Cancer Screening With Low-Dose Computed Tomography.

Approximately 21 900 women and 35 300 men developed lung cancer in Germany in 2018, and 16 514 women and 28 365 men died of it. The outcome mainly depends on the tumor stage. In early stages (stage I or II), treatment can be curative; unfortunately, because early-stage lung cancers are generally asymptomatic, 74% of women and 77% of men already have advanced-stage disease (stage III or IV) at the time of diagnosis. Screening with low-dose computed tomography is an option enabling early diagnosis and curative treatment. This review is based on pertinent articles retrieved by a selective search of the literature on screening for lung cancer. In the studies of lung cancer screening that have been published to date, sensitivity ranged from 68.5% to 93.8%, and specificity from 73.4% to 99.2%. A meta-analysis by the German Federal Office for Radiation Protection revealed a 15% reduction in lung cancer mortality when low-dose computed tomography was used in persons who were judged to be at high risk for lung cancer (risk ratio [RR] 0.85, 95% confidence interval [0.77; 0.95]). 1.9% of subjects died in the screening arm of the metaanalysis, and 2.2% in the control group. The observation periods ranged from 6.6 to 10 years; false-positive rates ranged from 84.9% to 96.4%. Malignant findings were confirmed in 45% to 70% of the biopsies or resective procedures that were performed. Systematic lung cancer screening with low-dose CT lowers mortality from lung cancer in (current or former) heavy smokers. This benefit must be weighed against the high rate of false-positive findings and overdiagnoses.

Assessing disparities in lung cancer screening eligibility among high-risk individuals.

10563 Background: Low-dose computerized tomography (LDCT) scanning confers a 20% reduction in lung cancer mortality by diagnosing the disease at earlier, more treatable stages. Racial/ethnic minorities have historically been less likely to be eligible for lung cancer screening. In 2021, the U.S. Preventive Services Task Force (USPSTF) updated its 2013 guideline for lung cancer screening eligibility by reducing the minimum age (55 to 50) and decreasing the cumulative number of cigarette pack-years smoked (30 to 20). The purpose of this study was to assess if the updated guideline will mitigate disparities in lung cancer screening eligibility among high-risk individuals. Methods: Data were obtained from the Behavioral Risk Factor Surveillance System (2017-2019), a population-based survey administered annually by the Centers for Disease Control and Prevention. Only subjects with complete information on the variables used to determine eligibility (age, smoking status, age at first start smoking, age at last smoked, average number of cigarettes smoked each day) (n = 793,537) were included in the final analysis. Logistic regression was used to model the association between predictors and 2021 vs. 2013 lung cancer screening eligibility. Results: Based on the 2013 guideline, Non-Hispanic Blacks (OR: 0.34; 95%CI: 0.31 - 0.38), Hispanics (OR: 0.12; 95%CI: 0.10 – 0.14), and other racial/ethnic minorities (OR: 0.59; 95%CI: 0.54 – 0.64) were less likely to be eligible for lung cancer screening than Non-Hispanic Whites. Using the 2021 guideline, Non-Hispanic Blacks (OR: 0.45; 95%CI: 0.42 - 0.49), Hispanics (OR: 0.15; 95%CI: 0.13 – 0.16), and other racial/ethnic minorities (OR: 0.63; 95%CI: 0.58 – 0.67) remain less likely to be eligible for lung cancer screening than Non-Hispanic Whites. Conclusions: The 2021 guideline slightly reduces racial/ethnic disparities in lung cancer screening eligibility. Further efforts should be made to develop a guideline that better addresses disparities in lung cancer screening eligibility to reduce lung cancer deaths in racial minorities.

The probability of lung cancer in patients with incidentally detected pulmonary nodules detected via low-dose computed tomography screening in China.

10569 Background: Low dose computed tomography (LDCT) screening has been proven to be effective in reducing lung cancer mortality, but the ensuing high false-positive and overdiagnosis rates shackle the effectiveness of lung cancer screening (LCS) in China. Nodule malignancy prediction models may be an applicable solution. Methods: We developed and internally validated the model using data from the ongoing Henan province Cancer Screening Program in Urban China (CanSPUC). From 2013 to 2021, 23031 heavy smokers underwent baseline screening with LDCT; 2553 participants were diagnosed with pulmonary nodules. Detailed questionnaire, physical assessment and follow-up were completed for all participants. We then externally validated the model using the National Lung Screening Trial (NLST) dataset consisting of 10485 lung nodules in 4660 participants. Multivariable Cox proportional risk regression models were used. Data analysis was performed from July 1, 2022, through December 31, 2022. Results: A total of 111 and 1089 lung cancer cases with a median follow-up duration of 3.7 years occurred in the Henan CanSPUC and NLST study, respectively. Age, gender, physical activity, consumption of pickled food, history of silicosis or pneumoconiosis, nodule type, size, calcification, and pleural retraction sign were included into the model. The AUC (95% CI) of the model for 5-year lung cancer risk was 0.857 (0.801, 0.914) and 0.847 (0.829, 0.881) in the training set and validation set, respectively. Compared with Mayo model, VA model, PKU model, and Brock model, the Henan CanSPUC model yield statistically better discriminatory performance (all P values &lt; 0.05). The model calibrated well across the deciles of predicted risk in both the overall population and all subgroups. Conclusions: The model developed and validated in this study may be used to estimate the probability of lung cancer in nodules detected at baseline LDCT, allowing more efficient risk-adapted follow-up in population-based LCS programs.

Early detection of lung cancer using small RNAs.

3035 Background: Low-dose computed tomography (LDCT) screening can significantly reduce lung cancer mortality. However, annual screening is limited by low adherence in the USA and still not broadly implemented in Europe. As a result, &lt;10% of lung cancers are detected through existing programs. Thus, there is great need for additional diagnostic modalities, such as a blood test that could be deployed in the primary care setting. Methods: We prospectively recruited 1,189 patients meeting the 2013 USPSTF screening criteria for lung cancer and collected stabilized whole blood. Ultra-deep small RNA sequencing was performed with a method to remove highly abundant erythroid RNAs, opening bandwidth for the detection of less abundant species originating from plasma or the immune cellular compartment. We utilized 100 random data splits to train and evaluate logistic regression classifiers using small RNA expression, discovered an 18-small RNA feature consensus signature (miLung), and validated this in an independent cohort (246 patients). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin. Results: We generated diagnostic models and report a median ROC AUC of 0.86 (95% CI 0.84-0.86) in the discovery cohort, and generalized performance of 0.84 in the validation cohort. Diagnostic performance increased stage-dependently from 0.73 (95% CI 0.71-0.76) for Stage I to 0.90 (95% CI 0.89-0.90) for Stage IV. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased following surgery with curative intent. In additional experiments, dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted via home-sampling. Conclusions: These data suggest the potential of a small RNA-based blood test as a viable alternative to LDCT screening for early detection of smoking-associated lung cancer. Clinical trial information: NCT03452514 . [Table: see text]

Leveraging social media to increase lung cancer screening awareness, knowledge and uptake among high-risk populations (The INSPIRE-Lung Study): study protocol of design and methods of a community-based randomized controlled trial

BackgroundLung cancer is the leading cause of cancer death for both men and women in the United States. The National Lung Screening Trial (NLST) demonstrated that low-dose computed tomography (LDCT) screening can reduce lung cancer mortality among high-risk individuals, but uptake of lung screening remains low. Social media platforms have the potential to reach a large number of people, including those who are at high risk for lung cancer but who may not be aware of or have access to lung screening.MethodsThis paper discusses the protocol for a randomized controlled trial (RCT) that leverages FBTA to reach screening-eligible individuals in the community at large and intervene with a public-facing, tailored health communication intervention (LungTalk) to increase awareness of, and knowledge about, lung screening.DiscussionThis study will provide important information to inform the ability to refine implementation processes for national population efforts to scale a public-facing health communication focused intervention using social media to increase screening uptake of appropriate, high-risk individuals.Trial registrationThe trial is registered at clinicaltrials.gov (#NCT05824273).

Characteristics of Pulmonary Nodules in Current Smoker

Lung cancer is the leading cause of death from cancer and the most effective way to reduce lung cancer mortality is early detection and treatment. The low-dose computed tomography (CT) can reduce the chances of lung cancer death, and used as screening test in several countries. Pulmonary nodules are a common finding in smokers, and differential diagnosis from cancer is a particularly important in lung cancer screening in smokers. We tried to find out the characteristics of lung nodules in patients who underwent smoker cancer screening. Data on low-dose lung CT findings and smoking counseling were collected for lung cancer screening patients for smokers conducted from January 2012 to June 2022. Out of a total of 1,320 patients, 1,101 had lung nodules. Lung nodules located in the right upper lobe were the most common at 30.5%, and lung nodules located in the right middle lobe were the least at 11.5%. Solid nodules were 97.3%, and ground-lass shadowing lesion was 2.4%. The average nodule size was 3.33 mm, and the largest was 43 mm. Compared to the previous test, 8.8% of the nodules were changed, and 1.8% of the total were suspected of cancer. The number of cessation patients interviewed was 138 (10.5%), and 98 were referred to smoking cessation clinics. This study shows that the lung nodule reporting rate is higher than overseas lung nodule reporting rate.

Significant Incidental Findings in the National Lung Screening Trial

Low-dose computed tomography (LDCT) lung screening has been shown to reduce lung cancer mortality. Significant incidental findings (SIFs) have been widely reported in patients undergoing LDCT lung screening. However, the exact nature of these SIF findings has not been described. To describe SIFs reported in the LDCT arm of the National Lung Screening Trial and classify SIFs as reportable or not reportable to the referring clinician (RC) using the American College of Radiology's white papers on incidental findings. This was a retrospective case series study of 26 455 participants in the National Lung Screening Trial who underwent at least 1 screening examination with LDCT. The trial was conducted from 2002 to 2009, and data were collected at 33 US academic medical centers. Significant incident findings were defined as a final diagnosis of a negative screen result with significant abnormalities that were not suspicious for lung cancer or a positive screen result with emphysema, significant cardiovascular abnormality, or significant abnormality above or below the diaphragm. Of 26 455 participants, 10 833 (41.0%) were women, the mean (SD) age was 61.4 (5.0) years, and there were 1179 (4.5%) Black, 470 (1.8%) Hispanic/Latino, and 24 123 (91.2%) White individuals. Participants were scheduled to undergo 3 screenings during the course of the trial; the present study included 75 126 LDCT screening examinations performed for 26 455 participants. A SIF was reported for 8954 (33.8%) of 26 455 participants who were screened with LDCT. Of screening tests with a SIF detected, 12 228 (89.1%) had a SIF considered reportable to the RC, with a higher proportion of reportable SIFs among those with a positive screen result for lung cancer (7632 [94.1%]) compared with those with a negative screen result (4596 [81.8%]). The most common SIFs reported included emphysema (8677 [43.0%] of 20 156 SIFs reported), coronary artery calcium (2432 [12.1%]), and masses or suspicious lesions (1493 [7.4%]). Masses included kidney (647 [3.2%]), liver (420 [2.1%]), adrenal (265 [1.3%]), and breast (161 [0.8%]) abnormalities. Classification was based on free-text comments; 2205 of 13 299 comments (16.6%) could not be classified. The hierarchical reporting of final diagnosis in NLST may have been associated with an overestimate of severe emphysema in participants with a positive screen result for lung cancer. This case series study found that SIFs were commonly reported in the LDCT arm of the National Lung Screening Trial, and most of these SIFs were considered reportable to the RC and likely to require follow-up. Future screening trials should standardize SIF reporting.

Implementation of Lung Cancer Screening in Primary Care and Pulmonary Clinics: Pragmatic Clinical Trial of Electronic Health Record-Integrated Everyday Shared Decision-Making Tool and Clinician-Facing Prompts

Although low-dose CT (LDCT) scan imaging lung cancer screening (LCS) can reduce lung cancer mortality, it remains underused. Shared decision-making (SDM) is recommended to assess the balance of benefits and harms for each patient. Do clinician-facing electronic health record (EHR) prompts and an EHR-integrated everyday SDM tool designed to support routine incorporation of SDM into primary care improve LDCT scan imaging ordering and completion? A preintervention and postintervention analysis was conducted in 30 primary care and four pulmonary clinics for visits with patients who met United States Preventive Services Task Force criteria for LCS. Propensity scores were used to adjust for covariates. Subgroup analyses were conducted based on the expected benefit from screening (high benefit vsintermediate benefit), pulmonologist involvement (ie, whether the patient was seen in a pulmonary clinic in addition to a primary care clinic), sex, and race and ethnicity. In the 12-month preintervention phase among 1,090 eligible patients, 77 patients (7.1%) had LDCT scan imaging orders and 48 patients (4.4%) completed screenings. In the 9-month intervention phase among 1,026 eligible patients, 280 patients (27.3%) had LDCT scan imaging orders and 182 patients (17.7%) completed screenings. Adjusted ORs were 4.9 (95%CI, 3.4-6.9; P< .001) and 4.7 (95%CI, 3.1-7.1; P< .001) for LDCT imaging ordering and completion, respectively. Subgroup analyses showed increases in ordering and completion for all patient subgroups. In the intervention phase, the SDM tool was used by 23 of 102 ordering providers (22.5%) and for 69 of 274 patients (25.2%) for whom LDCT scan imaging was ordered and who needed SDM at the time of ordering. Clinician-facing EHR prompts and an EHR-integrated everyday SDM tool are promising approaches to improving LCS in the primary care setting. However, room for improvement remains. As such, further research is warranted. ClinicalTrials.gov; No.: NCT04498052; URL: www. gov.

Development and validation of a simple general population lung cancer risk model including AHRR-methylation

IntroductionScreening reduces lung cancer mortality of high-risk populations. Currently proposed screening eligibility criteria only identify half of those individuals, who later develop lung cancer. This study aimed to develop and validate a sensitive and simple model for predicting 10-year lung cancer risk. MethodsUsing the 1991–94 examination of The Copenhagen City Heart Study in Denmark, 6,820 former or current smokers from the general population were followed for lung cancer within 10 years after examination. Logistic regression of baseline variables (age, sex, education, chronic obstructive pulmonary disease, family history of lung cancer, smoking status and cumulative smoking, secondhand smoking, occupational exposures to dust and fume, body mass index, lung function, plasma C-reactive protein, and AHRR(cg05575921) methylation) identified the best predictive model. The model was validated among 3,740 former or current smokers from the 2001-03 examination, also followed for 10 years. A simple risk chart was developed with Poisson regression. ResultsAge, sex, education, smoking status, cumulative smoking, and AHRR(cg05575921) methylation identified 65 of 88 individuals who developed lung cancer in the validation cohort. The highest risk group, consisting of less educated men aged >65 with current smoking status and cumulative smoking >20 pack-years, had absolute 10-year risks varying from 4% to 16% by AHRR(cg05575921) methylation. ConclusionA simple risk chart including age, sex, education, smoking status, cumulative smoking, and AHRR(cg05575921) methylation, identifies individuals with 10-year lung cancer risk from below 1% to 16%. Including AHRR(cg05575921) methylation in the eligibility criteria for screening identifies smokers who would benefit the most from screening.

Metabolic biomarkers in lung cancer screening and early diagnosis (Review).

Late diagnosis is one of the major contributing factors to the high mortality rate of lung cancer, which is now the leading cause of cancer-associated mortality worldwide. At present, low-dose CT (LDCT) screening in the high-risk population, in which lung cancer incidence is higher than that of the low-risk population is the predominant diagnostic strategy. Although this has efficiently reduced lung cancer mortality in large randomized trials, LDCT screening has high false-positive rates, resulting in excessive subsequent follow-up procedures and radiation exposure. Complementation of LDCT examination with biofluid-based biomarkers has been documented to increase efficacy, and this type of preliminary screening can potentially reduce potential radioactive damage to low-risk populations and the burden of hospital resources. Several molecular signatures based on components of the biofluid metabolome that can possibly discriminate patients with lung cancer from healthy individuals have been proposed over the past two decades. In the present review, advancements in currently available technologies in metabolomics were reviewed, with particular focus on their possible application in lung cancer screening and early detection.

Screening for Lung Cancer: An Expert Review

The NCCN Guidelines for Lung Cancer Screening have evolved over time to reflect the latest evidence and expert consensus. These NCCN Guidelines have played a significant role in shaping clinical practice and policy, leading to increased payer coverage for lung cancer screening and decreasing lung cancer mortality. Continued research and advancements in early detection methods, along with the implementation of effective screening programs, will be crucial in the ongoing effort to reduce lung cancer mortality and improve the overall quality of life for patients affected by this disease.

Probability of lung cancer in a population excluded from screening due to low PLCOM2012 risk

BackgroundSeveral randomized trials demonstrated have reduced lung cancer mortality with screening using computed tomography. However, there remains debate about the optimal approach for determining screening eligibility, and no evidence yet exists reporting lung cancer rates in those excluded from screening due to too low of a personalized risk. MethodsThis study was based on the Alberta Lung Cancer Screening Study, which received 1737 applicants and enrolled 850 based on the NLST criteria or a PLCOM2012 risk ≥ 1.5%. We excluded 887 applicants who were interested in screening but deemed ineligible. We report lung cancer rates in the screened and unscreened cohorts. ResultsWe observed 30 and 8 lung cancers in the screened and unscreened groups, respectively. Only 1 of 8 lung cancers were among those considered too low risk (0.14%), while the remaining 7 were among those excluded for other reasons, including symptoms requiring more immediate workup. No NLST eligible but PLCO risk < 1.5% screened individual had a lung cancer detected as part of the study, so that of all applicants contacting the program with risk estimates less than 1.5%, only 1/857 (0.12%) developed lung cancer. ConclusionOur findings indicate that a risk-based approach for screening eligibility is unlikely to miss many lung cancers.

Indonesian Society of Respirology (ISR) Consensus Statement on Lung Cancer Screening and Early Detection in Indonesia

Lung cancer is the leading cause of mortality for all cancer globally and in Indonesia. In Indonesia, lung cancer contributes to 12.6% of death of all cancer, making it the number one cause of cancer death, and 8.6% of all cancer incidence in 2018, behind breast, cervical, and colorectal cancer. The total cases per year are expected to almost double from 30,023 in 2018 to 54,983 cases in 2040. Smoking is among the risk factors for lung cancer, after occupational/environmental risk factors, history of lung fibrosis, and family history of cancer. There was a tendency of younger smokers in Indonesia and increased lung cancer incidence and prevalence in the younger population. The median age of lung cancer in Indonesia was younger than in any country, probably due to the younger age of smoking, early onset of carcinogens, asbestos use, and environmental. Lung cancer screening is a voluntary measure to detect lung cancer in the earliest stage, to find cancer at curable disease before symptoms appear in high-risk individuals. Lung cancer early detection is strategies to find cancer earlier after symptoms appear (cough, hemoptysis, dyspnea, chest pain). Low-dose computerized tomography of the thorax (LDCT) screening has been known to reduce lung cancer mortality compared to a chest x-ray (CXR). This Indonesian Society of Respirology consensus statement was aimed to give recommendations on lung cancer screening and early diagnosis in Indonesia.

"What do I think about implementing lung cancer screening? It all depends on how." Acceptability and feasibility of lung cancer screening in Australia: The view of key stakeholders about health system factors.

Lung cancer is the number one cause of cancer death worldwide. Although international trials demonstrate that targeted screening using low dose computed tomography (LDCT) significantly reduces lung cancer mortality, implementation of screening in the high-risk population presents complex health system challenges that need to be thoroughly understood to support policy change. To elicit health care providers' and policymakers' views about the acceptability and feasibility of lung cancer screening (LCS) and barriers and enablers to implementation in the Australian setting. We conducted 24 focus groups and three interviews (22 focus groups and all interviews online) in 2021 with 84 health professionals, researchers, and current cancer screening program managers and policy makers across all Australian states and territories. Focus groups included a structured presentation about lung cancer and screening and lasted approximately one hour each. A qualitative approach to analysis was used to map topics to the Consolidated Framework for Implementation Research. Nearly all participants considered LCS to be acceptable and feasible but identified a wide range of implementation challenges. Topics (five specific to health systems and five cross-cutting with participant factors) identified were mapped to CFIR constructs, of which 'readiness for implementation', 'planning' and 'executing' were most salient. Health system factor topics included delivery of the LCS program, cost, workforce considerations, quality assurance and complexity of health systems. Participants strongly advocated for streamlined referral processes. Practical strategies to address equity and access, such as using mobile screening vans, were emphasised. Key stakeholders readily identified the complex challenges associated with the acceptability and feasibility of LCS in Australia. The barriers and facilitators across health system and cross-cutting topics were clearly elicited. These findings are highly relevant to the scoping of a national LCS program by the Australian Government and a subsequent recommendation for implementation.

Abstract 787: Lung cancer screening use before &amp; during the COVID-19 pandemic in the US: Population-based evidence from 2019-2021

Abstract Introduction: Lung cancer is the leading cause of cancer-related death in the US with an estimated 236,740 new cases and 130,180 deaths expected in 2022. While early detection with low-dose computed tomography reduces lung cancer mortality by at least 20%, there has been a low uptake of lung cancer screening (LCS) use in the US. The COVID-19 pandemic caused significant disruption in cancer screening. Yet, little is known about how COVID-19 impacted already low use of LCS. This study aims to estimate LCS use before (2019) and during (2020 and 2021) the COVID-19 pandemic among LCS-eligible population in the US. Methods: We used population-based, nationally representative, cross-section data from the 2019 (n=4,484), 2020 (n=1,239) and 2021 (n=1,673) Behavioral Risk Factor Surveillance System, Lung Cancer Screening module. The outcome was self-reported LCS use among eligible adults in the past 12 months. For 2019 and 2020, the eligibility was defined based on US Preventive Services Task Force (USPSTF) initial criteria—adults aged 55 to 80 years old, who were current and former smokers (had quit within the past 15 years) with at least 30 pack years of smoking history. For 2021, we used the USPSTF updated criteria— adults aged 50 to 80 years, current and former smokers (who had quit within the past 15 years) with at least 20 pack years of smoking history. We applied sampling weights to account for the complex survey design to generate population estimates and conducted weighted descriptive statistics and logistic regression models. Results: Overall, there were an estimated 1,559,137 LCS-eligible respondents from 16 US states in 2019 (AZ, ID, KY, ME, MN, MS, MT, NC, ND, PA, RI, SC, UT, VT, WV, WI), 200,301 LCS-eligible respondents from five states in 2020 (DE, ME, NJ, ND, SD), and 668,359 LCS-eligible respondents from four states in 2021 (ME, MI, NJ, RI). Among 2,427,797 LCS-eligible adults, 254,890; 38,875; and 122,240 individuals reported receiving LCS in 2019, 2020 and 2021, respectively. Overall, 16.4% (95% CI 14.4-18.5), 19.4% (95% CI 15.3-24.3), and 18.3% (95% CI 15.6-21.3) received LCS during 2019, 2020, and 2021, respectively. In all years, the proportion of LCS use was higher among adults aged 65-74, insured, those with fair and poor health, lung disease and history of cancer (other than lung cancer). In 2020, a higher proportion of adults living in urban areas reported receiving LCS compared to those living in rural areas (20.36% vs. 12.7%, p=0.01). Compared to non-Hispanic White adults, the odds of receiving LCS was lower among Hispanic adults and higher among Non-Hispanic American Indian/Alaskan Native adults in 2020 and 2021, respectively. Conclusion: LCS uptake remains low in the US. An estimated 2,011,792 adults at high-risk for developing lung cancer did not receive LCS during 2019, 2020 and 2021. Efforts should be focused to increase LCS awareness and uptake across the US to reduce lung cancer burden. Citation Format: Hermine Poghosyan, Sayantani Sarkar, Ilana Richman. Lung cancer screening use before &amp; during the COVID-19 pandemic in the US: Population-based evidence from 2019-2021 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 787.

Abstract 68: Dissecting cellular and molecular alterations in pre-invasive to invasive lung cancer progression at single-cell resolution

Abstract Non-small cell lung cancer (NSCLC) accounts for most cancer-related deaths worldwide, largely due to diagnosis at advanced metastatic stages. Increased implementation of low-dose computed tomography (CT)-guided screening has led to the identification of non-solid lesions or ground-glass opacities (GGOs) that are not visible on plain chest radiography and can harbor very early-stage tumors. Growth of the lesions and/or development of a solid component can indicate more aggressive behavior. Using the low-dose CT reduced lung cancer mortality by &amp;gt;20%, underscoring the need for early detection and intervention. However, the cellular and molecular determinants that contribute to the malignant progression of those early preinvasive lesions remain poorly understood. To assess intratumoral heterogeneity and associated dynamic changes in the immune contexture during early lung carcinogenesis, we performed single-cell RNA-seq and Hyperion imaging on surgically resected freshly harvested tissues from 21 patients (matched solid and non-solid components of lesions and adjacent non-involved lungs), representing a spectrum from preneoplasia to invasive disease. Analysis of &amp;gt;300K cells identified cellular, transcriptomic, and metabolic alterations as well as tumor-stroma cross-talk pathways. Specifically, preinvasive to invasive disease progression was associated with significant changes in the immune landscape determined by an increase in exhausted CD4/CD8 T-cells, suppressive T-regs, polymorphonuclear myeloid-derived suppressor cells, and M2-like macrophages; and a decrease in cytotoxic CD8 T-cells, NK cells, and inflammatory cDC2 cells, suggesting that activation of immunosuppressive/anti-inflammatory microenvironment and suppression of immune activation microenvironment may enable tumor progression. Citation Format: Liron Yoffe, Alain Borczuk, Timothy E. McGraw, Olivier Elemento, Nasser K. Altorki, Vivek Mittal. Dissecting cellular and molecular alterations in pre-invasive to invasive lung cancer progression at single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 68.