Lung Cancer Screening Research Articles

MA18.03 Participant Eligibility for Lung Cancer Screening in Australia: An Analysis of Proposed Criteria

MA18.03 Participant Eligibility for Lung Cancer Screening in Australia: An Analysis of Proposed Criteria

P2.04B.06 Lung Cancer Screening Program in Serbia: A 3-year- Results and Challenges

P2.04B.06 Lung Cancer Screening Program in Serbia: A 3-year- Results and Challenges

P2.04B.09 A Qualitative Evaluation of the Critical Role of Lung Cancer Screening Program Navigators

P2.04B.09 A Qualitative Evaluation of the Critical Role of Lung Cancer Screening Program Navigators

P2.04B.16 Real-World First Round Results from a Charity Lung Cancer Screening Program in East Asia

P2.04B.16 Real-World First Round Results from a Charity Lung Cancer Screening Program in East Asia

P2.16G.02 "It's Like A Donut!"- Veteran Perspectives of Lung Cancer Screening with Low Dose CT

P2.16G.02 "It's Like A Donut!"- Veteran Perspectives of Lung Cancer Screening with Low Dose CT

P2.04A.05 Providing Tobacco Treatment to Patients Undergoing Lung Cancer Screening at a Large U.S. Health System: A Randomized Trial

P2.04A.05 Providing Tobacco Treatment to Patients Undergoing Lung Cancer Screening at a Large U.S. Health System: A Randomized Trial

The overview of imaging protocols for chest CT

Computed Tomography (CT) is a common method of choice in the diagnosis of thoracic diseases. Since CT operates on the principle of ionizing radiation and frequently involves the use of contrast agents, it is crucial to standardize CT protocols to reduce the need for repeat imaging and, consequently, minimize patient exposure to radiation. The selection of a CT protocol primarily depends on the patient’s clinical indications and needs. The main classification of CT protocols distinguishes between the use of contrast agents (CECT) and non-contrast protocols (NCCT). The LDCT protocol is characterized by a low radiation dose and high sensitivity for detecting pulmonary nodules, making it suitable for lung cancer screening. Ultra-LDCT yields satisfactory results in diagnosing pneumonia and pneumothorax. Cine CT enables the assessment of cardiac function throughout the entire cardiac cycle, though it involves a high radiation dose and low temporal resolution. The use of contrast agents is particularly beneficial for differentiating adjacent non-vascular structures, more accurately identifying vascular anatomy, and improving the detection and characterization of pathological lesions. For diagnosing vascular pathologies, CTA is used, while CTPA is essential for diagnosing pulmonary embolism (PE) with high sensitivity and specificity. TRO CT is useful in cases of acute chest pain to rule out emergencies. Dynamic changes in tissue perfusion are monitored with DCE-CT, which is also valuable in tumor diagnostics. In pediatric applications of CT for the chest, it is essential to emphasize the use of the lowest possible radiation dose and contrast agent to minimize risks.

P2.04B.13 Time to Benefit: A Systematic Review and Meta-Analysis of Lung Cancer Screening Trials

P2.04B.13 Time to Benefit: A Systematic Review and Meta-Analysis of Lung Cancer Screening Trials

Future implications of artificial intelligence in lung cancer screening: a systematic review.

The aim of this study was to systematically review the literature to assess the application of AI-based interventions in lung cancer screening, and its future implications. Relevant published literature was screened using PRISMA guidelines across three databases: PubMed, Scopus, and Web of Science. Search terms for article selection included "artificial intelligence," "radiology," "lung cancer," "screening," and "diagnostic." Included studies evaluated the use of AI in lung cancer screening and diagnosis. Twelve studies met the inclusion criteria. All studies concerned the role of AI in lung cancer screening and diagnosis. The AIs demonstrated promising ability across four domains: (1) detection, (2) characterization and differentiation, (3) augmentation of the work of human radiologists, (4) AI implementation of the LUNG-RADS framework and its ability to augment this framework. All studies reported positive results, demonstrating in some cases AI's ability to perform these tasks to a level close to that of human radiologists. The AI systems included in this review were found to be effective screening tools for lung cancer. These findings hold important implications for the future use of AI in lung cancer screening programmes as they may see use as an adjunctive tool for lung cancer screening that would aid in making early and accurate diagnosis. AI-based systems appear to be powerful tools that can assist radiologists with lung cancer screening and diagnosis.

Disparities in lungcancerscreening utilization attwo health systems in the Southeastern USA.

Low-dose computed tomography lung cancer screening is effective for reducing lung cancer mortality. It is critical to understand the lung cancer screening practices for screen-eligible individuals living in Alabama and Georgia where lung cancer is the leading cause of cancer death. High lung cancer incidence and mortality rates are attributed to high smoking rates among underserved, low income, and rural populations. Therefore, the purpose of this study is to define sociodemographic and clinical characteristicsof patients who were screened for lung cancer at an Academic Medical Center (AMC) in Alabama and a Safety Net Hospital (SNH) in Georgia. A retrospective cohort study of screen-eligible patients was constructed using electronic health records between 2015 and 2020 seen at an Academic Medical Center (AMC) and a Safety Net Hospital (SNH) separately. Chi-square tests and Student t tests were used to compare screening uptake across patient demographic and clinical variables. Bivariate and multivariate logistic regressions determined significant predictors of lung cancer screening uptake. At the AMC, 67,355 were identified as eligible for LCS and 1,129 were screened. In bivariate analyses, there were several differences between those who were screened and those who were not screened. Screening status in the site at Alabama-those with active tobacco use are significantly more likely to be screened than former smokers (OR: 3.208, p < 0.01). For every 10-unit increase in distance, the odds of screening decreased by about 15% (OR: 0.848, p < 0.01). For every 10-year increase in age, the odds of screening decrease by about 30% (OR: 0.704, p < 0.01). Each additional comorbidity increases the odds of screening by about 7.5% (OR: 1.075, p < 0.01). Those with both private and public insurance have much higher odds of screening compared to those with only private insurance (OR: 5.403, p < 0.01). However, those with only public insurance have lower odds of screening compared to those with private insurance (OR: 0.393, p < 0.01). At the SNH-each additional comorbidity increased the odds of screening by about 11.9% (OR: 1.119, p = 0.01). Notably, those with public insurance have significantly higher odds of being screened compared to those with private insurance (OR: 2.566, p < 0.01). The study provides evidence that LCS has not reached all subgroups and that additional targeted efforts are needed to increase lung cancer screening uptake. Furthermore, disparity was noticed between adults living closer to screening institutions and those who lived farther.

Public perspectives on the benefits and harms of lung cancer screening: A systematic review and mixed-method integrative synthesis.

Screening for lung cancer with low dose computed tomography aims to reduce lung cancer mortality, but there is a lack of knowledge about how target populations consider its potential benefits and harms. We conducted a systematic review of primary empirical studies published in any jurisdiction since 2002 using an integrative meta-synthesis technique. We searched six health and social science databases. Two reviewers independently screened titles, abstracts, and potentially eligible full-text studies. Quantitative assessments and open-ended perspectives on benefits and harms were extracted and convergently integrated at analysis using a narrative approach. Study quality was assessed. The review included 26 quantitative, 18 qualitative, and 5 mixed methods studies. Study quality was acceptable. Lung cancer screening was widely perceived to be personally beneficial for early detection and reassurance. Radiation exposure and screening accuracy were recognised as harms, but these were frequently considered to be justified by early detection of lung cancer. Stigma, anxiety, and fear related to screening procedures and results were pervasive among current smokers. People with low incomes reported not participating in screening because of potential out-of-pocket costs and geographic access. Populations targeted for lung cancer screening tended to consider screening as personally beneficial and rationalised physical, but not psychological, harms. Screening programmes should be clear about benefits, use non-stigmatising design, and consider equity as a guiding principle.

Prostate cancer screening: Is it time for a new approach? A review article.

Prostate cancer screening has presented a challenge to clinicians. Although the implementation of screening tests such as prostate-specific antigen (PSA) and digital rectal exam (DRE) has had a significant impact on prostate-cancer-specific mortality, these traditional screening tests have a relatively poor positive predictive value of clinically significant prostate cancer (CSPC), leading to unnecessary biopsies and treatment with a host of potential complications. Fortunately, much research has been done to optimize prostate cancer screening. This includes the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, which underwent a secondary analysis to identify an association between PSA level and CSPC, and the IP1-PROSTAGRAM Tri.

Body composition as a biomarker for assessing future lung cancer risk.

To investigate if body composition is a biomarker for assessing the risk of developing lung cancer. Low-dose computed tomography (LDCT) scans from the Pittsburgh Lung Screening Study (PLuSS) (n=3,635, 22 follow-up years) and NLST-ACRIN (n=16,435, 8 follow-up years) cohorts were used in the study. Artificial intelligence (AI) algorithms were developed to automatically segment and quantify subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), intramuscular adipose tissue (IMAT), skeletal muscle (SM), and bone. Cause-specific Cox proportional hazards models were used to evaluate the hazard ratios (HRs). Standard time-dependent receiver operating characteristic (ROC) analysis was used to evaluate the prognostic ability of different models over time. The final composite models were formed by seven variables: age (HR=1.20), current smoking status (HR=1.59), bone volume (HR=1.79), SM density (HR=0.29), IMAT ratio (HR=0.33), IMAT density (HR=0.56), and SAT volume (HR=0.56). The models trained on the PLuSS cohort achieved a mean AUC of 0.76 (95% CI: 0.74-0.79) over 21 follow-up years and 0.70 (95% CI: 0.66-0.74) over the first 7 follow-up years for predicting lung cancer development within the PLuSS cohort. In contrast, models trained on the PLuSS cohort alone, as well as in combination with the NLST cohorts, achieved an AUC ranging from 0.61 to 0.68 in the NLST cohort over a 7-year follow-up period. Body composition assessed on LDCT is a significant predictor of lung cancer risk and could improve the effectiveness of LDCT lung cancer screening by optimizing the screening eligibility and frequency. Body composition assessed on LDCT is a significant predictor of lung cancer risk and could improve the effectiveness of LDCT lung cancer screening by optimizing the screening eligibility and frequency. This study unveils the significant associations between body tissues and lung cancer risk.The prediction models based on body composition alone, as well as the combination of demographics and body composition features can effectively identify patients at higher risk of developing lung cancer.

Ultra-processed food consumption and renal cell carcinoma incidence and mortality: results from a large prospective cohort

BackgroundGrowing evidence shows that ultra-processed food consumption is associated with the risk of cancer. However, prospective evidence is limited on renal cell carcinoma (RCC) incidence and mortality. In this study, we aimed to examine the association of ultra-processed food consumption and RCC incidence and mortality in a large cohort of US adults.MethodsA population-based cohort of 101,688 participants were included from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Ultra-processed food items were confirmed by using the NOVA food classification system. The consumption of ultra-processed food was expressed as a percentage of total food intake (g/day). Prospective associations were calculated using Cox regression. Restricted cubic spline regression was used to assess nonlinearity. Subgroup analyses were performed to investigate the potential effect modifiers on the incidence and mortality of RCC.ResultsA total of 410 participants developed RCC during a total of 899,731 person-years of follow-up (median 9.41 years) and 230 RCC deaths during 1,533,930 person-years of follow-up (median 16.85 years). In the fully adjusted model, participants in the highest compared with the lowest quintiles of ultra-processed food consumption had a higher risk of RCC (HR quartile 4 vs 1:1.42; 95% CI: 1.06–1.91; Ptrend = 0.004) and mortality (HR quartile 4 vs. quartile 1: 1.64; 95% CI: 1.10–2.43; Ptrend = 0.027). Linear dose–response associations with RCC incidence and mortality were observed for ultra-processed food consumption (all Pnonlinearity > 0.05). The reliability of these results was supported by sensitivity and subgroup analyses.ConclusionIn conclusion, higher consumption of ultra-processed food is associated with an increased risk of RCC incidence and mortality. Limiting ultra-processed food consumption might be a primary prevention method of RCC.

Evolutionary Conserved and Divergent Responses to Copper Zinc Superoxide Dismutase Inhibition in Plants.

After an initial evolution in a reducing environment, life got successively challenged by reactive oxygen species (ROS), especially during the great oxidation event (GOE) that followed the development of photosynthesis. Therefore, ROS are deeply intertwined into the physiological, morphological and transcriptional responses of most present-day organisms. Copper-zinc superoxide dismutases (CuZnSODs) evolved during the GOE and are present in charophytes and extant land plants, but nearly absent from chlorophytes. The chemical inhibitor of CuZnSOD, lung cancer screen 1 (LCS-1), could greatly facilitate the study of SODs in diverse plants. Here, we determined the impact of chemical inhibition of plant CuZnSOD activity, on plant growth, transcription and metabolism. We followed a comparative approach by using different plant species, including Marchantia Polymorpha and Physcomitrium patens, representing bryophytes, the sister lineage to vascular plants, and Arabidopsis thaliana. We show that LCS-1 causes oxidative stress in plants and that the inhibition of CuZnSODs provoked a similar core response that mainly impacted glutathione homoeostasis in all plant species analysed. That said, Physcomitrium and Arabidopsis, which contain multiple CuZnSOD isoforms showed a more complex and exacerbated response. In addition, an untargeted metabolomics approach revealed a specific metabolic signature for each plant species. Our comparative analysis exposes a conserved core response at the physiological and transcriptional level towards LCS-1, while the metabolic response largely varies. These differences correlate with the number and localization of the CuZnSOD isoforms present in each species.

Potential of Chest Radiography in Primary Diagnosis of Lung Cancer

Objective: to evaluate the effectiveness of diagnostics for non-small cell lung cancer (LC) based on chest radiography/fluorography data for LC screening diagnostics during preventive medical examination and check-ups.Material and methods. The work was organized as a retrospective cohort study. The starting point of the study was chest radiography, the final point was the diagnosis of LC based on the results of low-dose computed tomography (LDCT) and tumor morphological examination. The patient sample was composed using inclusion and exclusion criteria and initially included 800 patients, then narrowed down to 788. Patients were divided into groups according to LC stage and depending on whether radiography during preventive measures made it possible to suspect LC verified within 3 months via LDCT for any reasons not related to the suspicion of a tumor process. The diagnostic coefficient and informative value of radiography were calculated for each stage of the established LC diagnosis.Results. The study showed that chest radiography does not allow establishing stage I LC diagnosis (J=0.00; p&lt;0.05), it is low informative for stage II LC (J=0.25; p&lt;0.05), and medium informative for stage III LC (J=0.80; p&lt;0.05). Chest radiography does not reliably detect LC signs at early stages in 84.3% of cases.Conclusion. The obtained results indicate an insufficient sensitivity of radiography as a screening method, primarily for early LC diagnosis. The introduction of chest LDCT instead of radiography into the procedure for preventive medical examination and check-ups of the adult population approved by the Ministry of Health of the Russian Federation will increase LC detection at early stages by 5.37 times (95% confidence interval 3,77–7,64).

Development and validation of a lung cancer polygenic risk score incorporating susceptibility variants for risk factors.

Incorporating susceptibility genetic variants of risk factors has been reported to enhance the risk prediction of polygenic risk score (PRS). However, it remains unclear whether this approach is effective for lung cancer. Hence, we aimed to construct a meta polygenic risk score (metaPRS) of lung cancer and assess its prediction of lung cancer risk and implication for risk stratification. Here, a total of 2180 genetic variants were used to develop nine PRSs for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer-related risk factors, respectively. These PRSs were then integrated into a metaPRS for lung cancer using the elastic-net Cox regression model in the UK Biobank (N = 442,508). Furthermore, the predictive effects of the metaPRS were assessed in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial (N = 108,665). The metaPRS was associated with lung cancer risk with a hazard ratio of 1.33 (95% confidence interval: 1.27-1.39) per standard deviation increased. The metaPRS showed the highest C-index (0.580) compared with the previous nine PRSs (C-index: 0.513-0.564) in PLCO. Besides, smokers in the intermediate risk group predicted by the clinical risk model (1.34%-1.51%) with the intermediate-high genetic risk had a 6-year average absolute lung cancer risk that exceeded the clinical risk model threshold (≥1.51%). The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI = 6.50%) in PLCO. These findings suggest the metaPRS can improve the predictive efficiency of lung cancer compared with the previous PRSs and refine risk stratification for lung cancer.

Leveraging External Aggregated Information for the Marginal Accelerated Failure Time Model.

It is becoming increasingly common for researchers to consider leveraging information from external sources to enhance the analysis of small-scale studies. While much attention has focused on univariate survival data, correlated survival data are prevalent in epidemiological investigations. In this article, we propose a unified framework to improve the estimation of the marginal accelerated failure time model with correlated survival data by integrating additional information given in the form of covariate effects evaluated in a reduced accelerated failure time model. Such auxiliary information can be summarized by using valid estimating equations and hence can then be combined with the internal linear rank-estimating equations via the generalized method of moments. We investigate the asymptotic properties of the proposed estimator and show that it is more efficient than the conventional estimator using internal data only. When population heterogeneity exists, we revise the proposed estimation procedure and present a shrinkage estimator to protect against bias and loss of efficiency. Moreover, the proposed estimation procedure can be further refined to accommodate the non-negligible uncertainty in the auxiliary information, leading to more trustable inference conclusions. Simulation results demonstrate the finite sample performance of the proposed methods, and empirical application on the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial substantiates its practical relevance.

"We don't get that information right back to us unless it's a full-blown cancer": Challenges coordinating lung cancer screening across healthcare systems.

To examine how lung cancer screening (LCS) is coordinated across healthcare systems, specifically Veterans Affairs (VA) and non-VA settings. We conducted primary qualitative data collection in six VA medical centers with established LCS programs from November 2020 to November 2021. Semi-structured interviews were conducted with 48 primary care providers, LCS program coordinators and directors, and pulmonologists. Thematic analysis examined spontaneously raised narratives related to initiating and coordinating LCS for Veterans screened in non-VA settings. We mapped coordination challenges to each step of the LCS care continuum. While non-VA options increased access to LCS for Veterans, VA medical centers lacked clear processes for initiating LCS referrals and tracking Veterans across the LCS continuum when screening occurred in non-VA settings. The responsibility of coordinating LCS with community providers often fell to VA primary care providers rather than LCS programs. Gaps in communication and data transfer contributed to delayed evaluation of potentially cancerous nodules post-screening, raising concerns about compromised care quality when LCS was shared with non-VA settings. While policies expanding LCS for Veterans in non-VA settings increase access, lack of consistent processes to initiate referrals, obtain results, and promote timely downstream evaluation fragmented care and delayed evaluation of concerning nodules. These unintended consequences highlight a need to address cross-system coordination challenges. Strategies to better coordinate LCS between VA and non-VA settings are essential to achieve high quality LCS and prevent Veterans from falling through the cracks.

Patients’ effective doses assessment during low-dose computed tomography

Computed tomography has become increasingly common for diagnosing socially significant diseases in recent years. In foreign practice, screening schemes for lung cancer in people belonging to risk categories have been developed and implemented. These schemes have been successfully used over the past 10 years. In this case, “low-dose” scanning protocols are used, which make it possible to perform examination with patient effective dose several times lower compared to standard protocols. Lung cancer screening methods using low-dose computed tomography are beginning to be introduced in the Russian Federation. To ensure the radiation safety of those individuals eligible for inclusion in screening programs or participating in biomedical research testing lung cancer screening, it is necessary to evaluate effective doses from low-dose computed tomography and compare these doses to established radiation dose limits. This study assessed the patients’ effective doses who underwent different types of low-dose computed tomography of chest at two medical organizations. The results of the study show that it is possible to achieve non-exceedance of the current annual effective dose limit of 1 mSv only for patients weighing less than 90 kg. For patients with higher body weight, the minimum effective dose will be in the range of 1.2 – 1.4 mSv. The results of the study indicate the need to make changes to the current regulatory and methodological documents of Rospotrebnadzor to ensure the possibility of using low-dose computed tomography as part of screening for all categories of people.