Prolonged lung cancer screening reduced 10-year mortality in the MILD trial: new confirmation of lung cancer screening efficacy

Effects of low dose computed tomography (LDCT) on lung cancer screening on incidence and mortality in regions with high tuberculosis prevalence: A systematic review

BACKGROUND

Lung cancer screening (LCS) using low-dose computed tomography (LDCT) is a strategy for early-stage diagnosis. The implementation of LDCT screening in countries with a high prevalence/incidence of tuberculosis (TB) is controversial. This systematic review and meta-analysis aim to identify whether LCS using LDCT increases early-stage diagnosis and decreases mortality, as well as the false-positive rate, in regions with a high prevalence of TB.

METHODS/DESIGN

Studies were identified by searching BVS, PUBMED, EMBASE, and SCOPUS. RCT and cohort studies (CS) that show the effects of LDCT in LC screening on mortality and secondary outcomes were eligible. Two independent reviewers evaluated eligibility and a third judged disagreements. We used the Systematic Review Data Repository (SRDR+) to extract the metadata and record decisions. The analyses were stratified by study design and incidence of TB. We used the Cochrane "Risk of bias" assessment tool.

RESULTS

The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) were used. Thirty-seven papers were included, referring to 22 studies (10 RCTs and 12 cohorts). Few studies were from regions with a high incidence of TB (One RCT and four cohorts). Nonetheless, the evidence is compatible with European and USA studies. RCTs and CS also had consistent results. There is an increase in early-stage (I-II) diagnoses and reduced LC mortality in the LCDT arm compared to the control. Although false-positive rates varied, they stayed within the 20 to 30% range.

DISCUSSION

This is the first meta-analysis of LDCT for LCS focused on its benefits in regions with an increased incidence/prevalence of TB. Although the specificity of Lung-RADS was higher in participants without TB sequelae than in those with TB sequelae, our findings point out that the difference does not invalidate implementing LDCT LCS in these regions.

TRIAL REGISTRATION

Systematic review registration Systematic review registration PROSPERO CRD42022309581.

Asbestos Surveillance Program Aachen (ASPA): Cancer mortality among asbestos exposed power industry workers

BACKGROUND

The time between initial asbestos exposure and asbestos-related disease can span several decades. The Asbestos Surveillance Program aims to detect early asbestos-related diseases in a cohort of 8,565 power industry workers formerly exposed to asbestos.

RESEARCH QUESTION

How does asbestos exposure patterns affect cancer mortality and the duration of latency until death?

METHODS

A mortality follow-up was conducted with available vital status for 8,476 participants (99 %) and available death certificates for 89.9 % of deceased participants. Standardised mortality ratios (SMR) were calculated for asbestos-related cancers. The SMR of mesothelioma and lung cancer were stratified by exposure duration, cumulative asbestos exposure and smoking. The effect of age at first exposure, cumulative asbestos exposure and smoking on the duration of latency until death was examined using multiple linear regression analysis.

RESULTS

The mortality risk of mesothelioma (n = 104) increased with cumulative asbestos exposure but not with exposure duration; the highest mortality (SMR: 23.20; 95 % CI: 17.62-29.99) was observed in participants who performed activities with short extremely high exposures (steam turbine revisions). Lung cancer mortality (n = 215) was not increased (SMR: 1.03; 95 % CI: 0.89-1.17). Median latency until death was 46 (15-63) years for mesothelioma and 44 (15-70) years for lung cancer and deaths occurred between age 64 and 82 years. Latency until death was not influenced by age at first exposure, cumulative exposure, or smoking.

CONCLUSION

Cumulative dose seems to be more appropriate than exposure duration for estimating the risk of mesothelioma death. Additionally, exposure with high cumulative doses in short time should be considered. Since only lung cancer mortality, not incidence, was recorded in this study, lung cancer risk associated with asbestos exposure could not be assessed and the lung cancer mortality was lower than expected probably due to screening effects and improved treatments. The critical time window of death from asbestos-related cancer is between the seventh and ninth decade of life. Future studies should further explore the concept of latency, especially since large ranges are reported throughout the literature.

LungPath: artificial intelligence-driven histologic pattern recognition for improved diagnosis of early-stage invasive lung adenocarcinoma

Background

Early-stage invasive lung adenocarcinoma (ADC) characterized by a predominant micropapillary or solid pattern exhibit an elevated risk of recurrence following sub-lobar resection, thus determining histological subtype of early-stage invasive ADC prior surgery is important for formulating lobectomy or sub-lobar resection. This study aims to develop a deep learning algorithm and assess its clinical capability in distinguishing high-risk or low-risk histologic patterns in early-stage invasive ADC based on preoperative computed tomography (CT) scans.

Methods

Two retrospective cohorts were included: development cohort 1 and external test cohort 2, comprising patients diagnosed with T1 stage invasive ADC. Electronic medical records and CT scans of all patients were documented. Patients were stratified into two risk groups. High-risk group: comprising cases with a micropapillary component ≥5% or a predominant solid pattern. Low-risk group: encompassing cases with a micropapillary component <5% and an absence of a predominant solid pattern. The overall segmentation model was modified based on Mask Region-based Convolutional Neural Network (Mask-RCNN), and Residual Network 50 (ResNet50)_3D was employed for image classification.

Results

A total of 432 patients participated in this study, with 385 cases in cohort 1 and 47 cases in cohort 2. The fine-outline results produced by the auto-segmentation model exhibited a high level of agreement with manual segmentation by human experts, yielding a mean dice coefficient of 0.86 [95% confidence interval (CI): 0.85-0.87] in cohort 1 and 0.84 (95% CI: 0.82-0.85) in cohort 2. Furthermore, the deep learning model effectively differentiated the high-risk group from the low-risk group, achieving an area under the curve (AUC) of 0.89 (95% CI: 0.88-0.90) in cohort 1. In the external validation conducted in cohort 2, the deep learning model displayed an AUC of 0.87 (95% CI: 0.84-0.88) in distinguishing the high-risk group from the low-risk group. The average diagnostic time was 16.00±3.2 seconds, with an accuracy of 0.82 (95% CI: 0.81-0.83).

Conclusions

We have developed a deep learning algorithm, LungPath, for the automated segmentation of pulmonary nodules and prediction of high-risk histological patterns in early-stage lung ADC based on CT scans.

Innovations in Early Lung Cancer Detection: Tracing the Evolution and Advancements in Screening

Lung cancer mortality rates, particularly non-small cell lung cancer (NSCLC), continue to present a significant global health challenge, and the adoption of lung cancer screening remains limited, often influenced by inequities in access to healthcare. Despite clinical evidence demonstrating the efficacy of annual screening with low-dose computed tomography (LDCT) and recommendations from medical organizations including the U.S. Preventive Services Task Force (USPSTF), the national lung cancer screening uptake remains around 5% among eligible individuals. Advancements in the clinical management of NSCLC have recently become more personalized with the implementation of blood-based biomarker testing. Extensive research into tumor-derived cell-free DNA (cfDNA) through fragmentation offers a novel method for improving early lung cancer detection. This review assesses the screening landscape, explores obstacles to lung cancer screening, and discusses how a plasma whole genome fragmentome test (pWGFrag-Lung) can improve lung cancer screening participation and adherence.

Urinary Metabolite Diagnostic and Prognostic Liquid Biopsy Biomarkers of Lung Cancer in Nonsmokers and Tobacco Smokers

PURPOSE

Nonsmokers account for 10% to 13% of all lung cancer cases in the United States. Etiology is attributed to multiple risk factors including exposure to secondhand smoking, asbestos, environmental pollution, and radon, but these exposures are not within the current eligibility criteria for early lung cancer screening by low-dose CT (LDCT).

EXPERIMENTAL DESIGN

Urine samples were collected from two independent cohorts comprising 846 participants (exploratory cohort) and 505 participants (validation cohort). The cancer urinary biomarkers, creatine riboside (CR) and N-acetylneuraminic acid (NANA), were analyzed and quantified using liquid chromatography-mass spectrometry to determine if nonsmoker cases can be distinguished from sex and age-matched controls in comparison with tobacco smoker cases and controls, potentially leading to more precise eligibility criteria for LDCT screening.

RESULTS

Urinary levels of CR and NANA were significantly higher and comparable in nonsmokers and tobacco smoker cases than population controls in both cohorts. Receiver operating characteristic analysis for combined CR and NANA levels in nonsmokers of the exploratory cohort resulted in better predictive performance with the AUC of 0.94, whereas the validation cohort nonsmokers had an AUC of 0.80. Kaplan-Meier survival curves showed that high levels of CR and NANA were associated with increased cancer-specific death in nonsmokers as well as tobacco smoker cases in both cohorts.

CONCLUSIONS

Measuring CR and NANA in urine liquid biopsies could identify nonsmokers at high risk for lung cancer as candidates for LDCT screening and warrant prospective studies of these biomarkers.

Early Detection and Interception of Lung Cancer

Recent advances in lung cancer treatment have led to dramatic improvements in 5-year survival rates. And yet, lung cancer remains the leading cause of cancer-related mortality, in large part, because it is often diagnosed at an advanced stage, when cure is no longer possible. Lung cancer screening (LCS) is essential for intercepting the disease at an earlier stage. Unfortunately, LCS has been poorly adopted in the United States, with less than 5% of eligible patients being screened nationally. This article will describe the data supporting LCS, the obstacles to LCS implementation, and the promising opportunities that lie ahead.

Patient Navigation for Lung Cancer Screening at a Health Care for the Homeless Program: A Randomized Clinical Trial

Importance

People experiencing homelessness die of lung cancer at rates more than double those in the general population. Lung cancer screening (LCS) with low-dose computed tomography (LDCT) reduces lung cancer mortality, but the circumstances of homelessness create barriers to LCS participation.

Objective

To determine whether patient navigation, added to usual care, improved LCS LDCT receipt at a large Health Care for the Homeless (HCH) program.

Design, Setting, and Participants

This parallel group, pragmatic, mixed-methods randomized clinical trial was conducted at Boston Health Care for the Homeless Program (BHCHP), a federally qualified HCH program that provides tailored, multidisciplinary care to nearly 10 000 homeless-experienced patients annually. Eligible individuals had a lifetime history of homelessness, had a BHCHP primary care practitioner (PCP), were proficient in English, and met the pre-2022 Medicare coverage criteria for LCS (aged 55-77 years, ≥30 pack-year history of smoking, and smoking within the past 15 years). The study was conducted between November 20, 2020, and March 29, 2023.

Intervention

Participants were randomized 2:1 to usual BHCHP care either with or without patient navigation. Following a theory-based, patient-centered protocol, the navigator provided lung cancer education, facilitated LCS shared decision-making visits with PCPs, assisted participants in making and attending LCS LDCT appointments, arranged follow-up when needed, and offered tobacco cessation support for current smokers.

Main Outcomes and Measures

The primary outcome was receipt of a 1-time LCS LDCT within 6 months after randomization, with between-group differences assessed by χ2 analysis. Qualitative interviews assessed the perceptions of participants and PCPs about the navigation intervention.

Results

In all, 260 participants (mean [SD] age, 60.5 [4.7] years; 184 males [70.8%]; 96 non-Hispanic Black participants [36.9%] and 96 non-Hispanic White participants [36.9%]) were randomly assigned to usual care with (n = 173) or without (n = 87) patient navigation. At 6 months after randomization, 75 participants in the patient navigation arm (43.4%) and 8 of those in the usual care-only arm (9.2%) had completed LCS LDCT (P < .001), representing a 4.7-fold difference. Interviews with participants in the patient navigation arm and PCPs identified key elements of the intervention: multidimensional social support provision, care coordination activities, and interpersonal skills of the navigator.

Conclusions and Relevance

In this randomized clinical trial, patient navigation support produced a 4.7-fold increase in 1-time LCS LDCT completion among HCH patients in Boston. Future work should focus on longer-term screening participation and outcomes.

Trial Registration

ClinicalTrials.gov Identifier: NCT04308226.

A Virus-Inspired Inhalable Liponanogel Induces Potent Antitumor Immunity and Regression in Metastatic Lung Tumors

Pulmonary delivery of immunostimulatory agents such as poly(I:C) to activate double-stranded RNA sensors MDA5 and RIG-I within lung-resident antigen-presenting cells is a potential strategy to enhance antitumor immunity by promoting type I interferon secretion. Nevertheless, following pulmonary delivery, poly(I:C) suffers from rapid degradation and poor endosomal escape, thus limiting its potency. Inspired by the structure of a virus that utilizes internal viral proteins to tune the loading and cytosolic delivery of viral nucleic acids, we developed a liponanogel (LNG)-based platform to overcome the delivery challenges of poly(I:C). The LNG comprised an anionic polymer hyaluronic acid-based nanogel core coated by a lipid shell, which served as a protective layer to stabilize the nanogel core in the lungs. The nanogel core was protonated within acidic endosomes to enhance the endosomal membrane permeability and cytosolic delivery of poly(I:C). After pulmonary delivery, LNG-poly(I:C) induced 13.7-fold more IFNβ than poly(I:C) alone and two-fold more than poly(I:C) loaded in the state-of-art lipid nanoparticles [LNP-poly(I:C)]. Additionally, LNG-poly(I:C) induced more potent CD8+ T-cell immunity and stronger therapeutic effects than LNP-poly(I:C). The combination of LNG-poly(I:C) and PD-L1 targeting led to regression of established lung metastases. Due to the ease of manufacturing and the high biocompatibility of LNG, pulmonary delivery of LNG may be broadly applicable to the treatment of different lung tumors and may spur the development of innovative strategies for cancer immunotherapy. Significance: Pulmonary delivery of poly(I:C) with a virus-inspired inhalable liponanogel strongly activates cytosolic MDA5 and RIG-I and stimulates antitumor immunity, representing a promising strategy for safe and effective treatment of metastatic lung tumors.

Yorkshire Lung Screening Trial (YLST) pathway navigation study: a protocol for a nested randomised controlled trial to evaluate the effect of a pathway navigation intervention on lung cancer screening uptake

INTRODUCTION

Lung cancer is the most common cause of cancer death globally. In 2022 the UK National Screening Committee recommended the implementation of a national targeted lung cancer screening programme, aiming to improve early diagnosis and survival rates. Research studies and services internationally consistently observe socioeconomic and smoking-related inequalities in screening uptake. Pathway navigation (PN) is a process through which a trained pathway navigator guides people to overcome barriers to accessing healthcare services, including screening. This nested randomised controlled trial aims to determine whether a PN intervention results in more individuals participating in lung cancer screening compared with the usual written invitation within a previous non-responder population as part of the Yorkshire Lung Screening Trial (YLST).

METHODS AND ANALYSIS

A two-arm randomised controlled trial and process evaluation nested within the YLST. Participants aged 55-80 (inclusive) who have not responded to previous postal invitations to screening will be randomised by household to receive PN or usual care (a further postal invitation to contact the screening service for a lung health check) between March 2023 and October 2024. The PN intervention includes a postal appointment notification and prearranged telephone appointment, during which a pathway navigator telephones the participant, following a four-step protocol to introduce the offer and conduct an initial risk assessment. If eligible, participants are invited to book a low-dose CT (LDCT) lung cancer screening scan. All pathway navigators receive training from behavioural psychologists on motivational interviewing and communication techniques to elicit barriers to screening attendance and offer solutions.

COPRIMARY OUTCOMES

The number undergoing initial telephone assessment of lung cancer risk. The number undergoing an LDCT screening scan.Secondary outcomes include demographic, clinical and risk parameters of people undergoing telephone risk assessment; the number of people eligible for screening following telephone risk assessment; the number of screen-detected cancers diagnosed; costs and a mixed-methods process evaluation.Descriptive analyses will be used to present numbers, proportions and quantitative components of the process evaluation. Primary comparisons of differences between groups will be made using logistic regression. Applied thematic analysis will be used to interpret qualitative data within a conceptual framework based on the COM-B framework. A health economic analysis of the PN intervention will also be conducted.

ETHICS AND DISSEMINATION

The study is approved by the Greater Manchester West Research Ethics Committee (18-NW-0012) and the Health Research Authority following the Confidentiality Advisory Group review. Results will be shared through peer-reviewed scientific journals, conference presentations and on the YLST website.

TRIAL REGISTRATION NUMBERS

ISRCTN42704678 and NCT03750110.

Barriers to Completing Low Dose Computed Tomography Scan for Lung Cancer Screening

INTRODUCTION

Annual low-dose computed tomography (LDCT) screening has been shown to reduce lung cancer mortality in high-risk individuals by detecting the disease at an earlier stage. This study aims to assess the barriers to completing LDCT in a cohort of patients who were determined eligible for lung cancer screening (LCS).

METHODS

We performed a single institution, mixed methods, cross-sectional study of patients who had a LDCT ordered from July to December 2022. We then completed phone surveys with patients who did not complete LDCT to assess knowledge, attitude, and perceptions toward LCS.

RESULTS

We identified 380 patients who met inclusion criteria, including 331 (87%) who completed LDCT and 49 (13%) who did not. Patients who completed a LDCT and those who did not were similar regarding age, sex, race, primary language, household income, body mass index, median pack years, and quit time. Positive predictors of LDCT completion were: meeting USPSTF guidelines (97.9% vs 81.6%), being married (58.3% vs 44.9%), former versus current smokers (55% vs 41.7%), personal history of emphysema (60.4% vs 42.9%), and family history of lung cancer (13.9% vs 4.1%) (all P < .05). Of the patients who participated in the phone survey, only 7% of respondents thought they were high risk for developing lung cancer despite attending a shared decision-making visit and only 10% wanted to re-schedule their LDCT.

CONCLUSION

There exist barriers to completing LDCT even after patients are identified as eligible and complete a shared decision-making visit secondary to knowledge barriers, misperceptions, and patient disinterest.

Willingness to participate in combination screening for lung cancer, chronic obstructive pulmonary disease and cardiovascular disease in four European countries

OBJECTIVES

Lung cancer screening (LCS), using low-dose computed tomography (LDCT), can be more efficient by simultaneously screening for chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD), the Big-3 diseases. This study aimed to determine the willingness to participate in (combinations of) Big-3 screening in four European countries and the relative importance of amendable participation barriers.

METHODS

An online cross-sectional survey aimed at (former) smokers aged 50-75 years elicited the willingness of individuals to participate in Big-3 screening and used analytical hierarchy processing (AHP) to determine the importance of participation barriers.

RESULTS

Respondents were from France (n = 391), Germany (n = 338), Italy (n = 399), and the Netherlands (n = 342), and consisted of 51.2% men. The willingness to participate in screening was marginally influenced by the diseases screened for (maximum difference of 3.1%, for Big-3 screening (73.4%) vs. lung cancer and COPD screening (70.3%)) and by country (maximum difference of 3.7%, between France (68.5%) and the Netherlands (72.3%)). The largest effect on willingness to participate was personal perceived risk of lung cancer. The most important barriers were the missed cases during screening (weight 0.19) and frequency of screening (weight 0.14), while diseases screened for (weight 0.11) ranked low.

CONCLUSIONS

The difference in willingness to participate in LCS showed marginal increase with inclusion of more diseases and limited variation between countries. A marginal increase in participation might result in a marginal additional benefit of Big-3 screening. The amendable participation barriers are similar to previous studies, and the new criterion, diseases screened for, is relatively unimportant.

CLINICAL RELEVANCE STATEMENT

Adding diseases to combination screening modestly improves participation, driven by personal perceived risk. These findings guide program design and campaigns for lung cancer and Big-3 screening. Benefits of Big-3 screening lie in long-term health and economic impact, not participation increase.

KEY POINTS

• It is unknown whether or how combination screening might affect participation. • The addition of chronic obstructive pulmonary disease and cardiovascular disease to lung cancer screening resulted in a marginal increase in willingness to participate. • The primary determinant influencing individuals' engagement in such programs is their personal perceived risk of the disease.

Combined Breast and Lung Cancer Screening Among Dual-Eligible Women: A Descriptive Study

INTRODUCTION

Lung cancer is consistently the leading cause of cancer death among women in the United States, yet lung cancer screening (LCS) rates remain low. By contrast, screening mammography rates are reliably high, suggesting that screening mammography can be a "teachable moment" to increase LCS uptake among dual-eligible women.

MATERIALS AND METHODS

This is a prospective survey study conducted at two academic institutions. Patients undergoing screening mammography were evaluated for LCS eligibility and offered enrollment in a pilot dual-cancer screening program. A series of surveys was administered to characterize participants' knowledge, perceptions, and attitudes about LCS before and after undergoing dual screening. Data were descriptively summarized.

RESULTS

Between August 2022 and July 2023, 54 LCS-eligible patients were enrolled. The study cohort was 100% female and predominantly White (81%), with a median age of 57 y and median of 36 pack-y of smoking. Survey results showed that 98% felt they were at risk for lung cancer, with most (80%) motivated by early detection of potential cancer. Regarding screening barriers, 58% of patients lacked knowledge about LCS eligibility and 47% reported concerns about screening cost. Prior to undergoing LCS, 87% of patients expressed interest in combined breast and lung screening. Encouragingly, after LCS, 84% were likely or very likely to undergo dual screening again and 93% found the shared decision-making visit helpful or very helpful.

CONCLUSIONS

Pairing breast and LCS is a feasible, acceptable intervention that, along with increasing patient and provider education about LCS, can increase LCS uptake and reduce lung cancer mortality.

Investigating socioeconomic disparities in lung cancer diagnosis, treatment and mortality: an Italian cohort study

BACKGROUND

Lung cancer is one of the most lethal cancers worldwide and patient clinical outcomes seem influenced by their socioeconomic position (SEP). Since little has been investigated on this topic in the Italian context, our aim was to investigate the role of SEP in the care pathway of lung cancer patients in terms of diagnosis, treatment and mortality.

METHODS

This observational retrospective cohort study included patients discharged in the Lazio Region with a lung cancer diagnosis between 2014 and 2017. In the main analysis, educational level was used as SEP measure. Multivariate models, adjusted for demographic and clinical variables, were applied to evaluate the association between SEP and study outcomes, stratified for metastatic (M) and non-metastatic (NM) cancer. We defined a diagnosis as 'delayed' when patients received their initial cancer diagnosis after an emergency department admission. Access to advanced lung cancer treatments (high-cost, novel and innovative treatments) and mortality were investigated within the 24-month period post-diagnosis. Moreover, two additional indicators of SEP were examined in the sensitivity analysis: one focusing on area deprivation and the other on income-based exemption.

RESULTS

A total of 13,251 patients were identified (37.3% with metastasis). The majority were males (> 60%) and over half were older than 70 years. The distribution of SEP levels among patients was as follow: 31% low, 29% medium-low, 32% medium-high and 7% high. As SEP increased, the risks of receiving a delayed diagnosis ((high vs low: M: OR = 0.29 (0.23-0.38), NM: OR = 0.20 (0.16-0.25)) and of mortality ((high vs low M: OR = 0.77 (0.68-0.88) and NM: 0.61 (0.54-0.69)) decreased. Access to advanced lung cancer treatments increased in accordance with SEP only in the M cohort (high vs low: M: OR = 1.57 (1.18-2.09)). The primary findings were corroborated by sensitivity analysis.

CONCLUSIONS

Our study highlighted the need of public health preventive and educational programs in Italy, a country where the care pathway of lung cancer patients, especially in terms of diagnosis and mortality, appears to be negatively affected by SEP level.

Prediction of the stage shift growth of early-stage lung adenocarcinomas by volume-doubling time

Background

Prediction of subsolid nodule (SSN) interval growth is crucial for clinical management and decision making in lung cancer screening program. To the best of our knowledge, no study has investigated whether volume doubling time (VDT) is an independent factor for predicting SSN interval growth, or whether its predictive power is better than that of traditional semantic methods, such as nodular diameter or type. This study aimed to investigate whether VDT could provide added value in predicting the long-term natural course of SSNs (<3 cm) regarding stage shift.

Methods

This retrospective study enrolled 132 patients with spectrum lesions of lung adenocarcinoma who underwent two consecutive computed tomography (CT) examinations before surgical tissue proofing between 2012 and 2021 in Kaohsiung Veterans General Hospital. The VDTs were manually calculated from the volumetric segmentation using Schwartz's approximation formula. We utilized logistic regression to identify predictors associated with stage shift progression based on the VDT parameter.

Results

The average duration of follow-up period was 3.629 years. A VDT-based nomogram model (model 2) based on CT semantic features, clinical characteristics, and the VDT parameter yielded an area under the curve (AUC) of 0.877 [95% confidence interval (CI): 0.807-0.928]. Compared with model 1 (CT semantic features and clinical characteristics), model 2 exhibited the better predictive performance for stage shift (AUC model 1: 0.833 versus AUC model 2: 0.877, P=0.047). In model 2, significant predictors of stage shift growth included initial nodule size [odds ratio (OR) =4.074, 95% CI: 1.368-12.135; P=0.012], SSN classification (OR =0.042; 95% CI: 0.006-0.288; P=0.001), follow-up period (OR =1.692, 95% CI: 1.337-2.140; P<0.001), and VDT classification (OR =2.327, 95% CI: 1.368-3.958; P=0.002). For the stage shift, the mean progression time for the VDT (>400 d) group was 7.595 years, and median progression time was 7.430 years. Additionally, a VDT ≤400 d is an important prognostic factor associated with aggressive growth behavior with a stage shift.

Conclusions

VDT is crucial for predicting SSN stage shift growth irrespective of clinical and CT semantic features. This highlights its significance in informing follow-up protocols and surgical planning, emphasizing its prognostic value in predicting SSN growth.

Incidental diagnosis of lung cancer on chest CT scan performed for suspected or documented COVID-19 infection

CONTEXT

Recent studies have shown a benefit of chest computed tomography (CT scan) in lung cancer screening. The COVID-19 pandemic has led to many chest CT scan performed on a large population. The objective of this study was to describe the incidence and characteristics of lung cancer detected on chest CT scan, outside the framework of a clinical trial, for a suspected or documented COVID-19 infection.

METHODS

We conducted a multicenter study, carried out from the analysis of data from the prospective COVID-19 database of the Clinical Data Warehouse of the Greater Paris University Hospitals (AP-HP). We identified the patients who had been diagnosed with a lung cancer, due to a chest CT scan done for a suspected or confirmed COVID-19 infection. The study period was limited to the first two epidemic lockdowns: (03/01/20 - 05/31/20) and (10/10/20 - 11/30/20).

RESULTS

Over the study period, 24 390 patients had at least one chest CT scan. Among them, 72 lung cancer diagnoses were made (incidence 0.30 %; median age 67.4 years old, 50.0 % current smokers, 55.6 % adenocarcinoma). Half of the lung cancer patients (n = 36) did not meet the National Lung Screening Trial inclusion criteria. Twenty-six patients (36.1 %) were diagnosed at an early stage, 25 (34.7 %) of whom received radical curative treatment. Twenty-six patients died during the follow-up (36.1 %) but none in early stages. The median overall survival in lung cancer patients was 693 days [532 - NA].

CONCLUSIONS

A large-scale chest CT scan strategy for suspected or documented COVID-19 infection has allowed a significant proportion of early-stage lung cancer diagnosis, all of which have benefited from curative treatment.

Overcoming barriers to lung cancer screening using a systemwide approach with additional focus on the non-screened

BACKGROUND

The lung cancer screening program at St Elizabeth Healthcare (Kentucky, USA) began in 2013. Over 33,000 low-dose computed tomography lung cancer screens have been performed. From 2015 through 2021, 2595 lung cancers were diagnosed systemwide. A Screening Program with Impactful Results from Early Detection, reviews that experience; 342 (13.2%) were diagnosed by screening and 2253 (86.8%) were non-screened. As a secondary objective, the non-screened cohort was queried to determine how many additional individuals could have been screened, identifying barriers and failures to meet eligibility.

METHODS

Our QlikSense database extracted the lung cancer patients from the Cancer Patient Data and Management System, and identified and categorized them separately as screened or non-screened populations. Stage distribution was compared in screened and non-screened groups. Those meeting age criteria, with any smoking history, were further queried for screening eligibility, accessing the electronic medical record smoking history and audit trail, and determining if enough information was available to substantiate screening eligibility. The same methodology was applied to CMS 2015 and USPSTF 2021 criteria.

RESULTS

The screened and non-screened patients were accounted for in a stage migration chart demonstrating clear shift to early stage among screened lung cancer patients. Additionally, analysis of non-screened individuals is presented.

CONCLUSION

Of the St Elizabeth Healthcare eligible patients attributed to primary care providers, 49.6% were screened in 2021. Despite this level of success, this study highlighted a sizeable pool of additional individuals that could have been screened. We are shifting focus to the non-screened pool of patients that meet eligibility, further enhancing the impact on our community.

[Lung cancer screening: new frontiers]

CLINICAL/METHODICAL ISSUE

Lung cancer is the leading cause of cancer-related deaths worldwide. In early, asymptomatic stages, curative treatment is possible, but the disease is often diagnosed too late.

STANDARD RADIOLOGICAL METHODS

Lung cancer screening (LCS) using low-dose computed tomography (LDCT) helps to detect potentially malignant lesions in early stages and to reduce lung cancer mortality.

METHODOLOGICAL INNOVATIONS

The application of artificial intelligence (AI) algorithms enables a more precise analysis of LDCT scans.

PERFORMANCE

A meta-analysis of eight LCS studies revealed a statistically significant 12% relative reduction in lung cancer mortality.

ACHIEVEMENTS

Based on strong scientific evidence, a recommendation for a structured lung cancer screening program using LDCT for the high-risk population in Germany was issued.

PRACTICAL RECOMMENDATIONS

The holistic LCS program requires a clear definition of the high-risk population, individual risk assessment, qualified personnel for conducting and reading examinations, verification of all diagnostic and therapeutic steps, central documentation and quality assurance, as well as the integration of tobacco cessation programs.

Imaging of Solid Pulmonary Nodules

Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung cancer morbidity and mortality. Computed tomography (CT) remains the most widely used imaging examination for pulmonary nodule evaluation; however, other imaging modalities, such as PET/CT and MRI, are increasingly used for nodule characterization. Current advances in solid nodule imaging are largely due to developments in machine learning, including automated nodule segmentation and computer-aided detection. This review explores current multi-modality solid pulmonary nodule detection and characterization with discussion of radiomics and risk prediction models.

Validation of a Blood-Based Protein Biomarker Panel for a Risk Assessment of Lethal Lung Cancer in the Physicians' Health Study

This study aimed to assess a four-marker protein panel (4MP)'s performance, including the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19, for predicting lung cancer in a cohort enriched with never- and ever-smokers. Blinded pre-diagnostic plasma samples collected within 2 years prior to a lung cancer diagnosis from 25 cases and 100 sex-, age-, and smoking-matched controls were obtained from the Physicians' Health Study (PHS). The 4MP yielded AUC performance estimates of 0.76 (95% CI: 0.61-0.92) and 0.69 (95% CI: 0.56-0.82) for predicting lung cancer within one year and within two years of diagnosis, respectively. When stratifying into ever-smokers and never-smokers, the 4MP had respective AUCs of 0.77 (95% CI: 0.63-0.92) and 0.72 (95% CI: 0.17-1.00) for a 1-year risk of lung cancer. The AUCs of the 4MP for predicting metastatic lung cancer within one year and two years of the blood draw were 0.95 (95% CI: 0.87-1.00) and 0.78 (95% CI: 0.62-0.94), respectively. Our findings indicate that a blood-based biomarker panel may be useful in identifying ever- and never-smokers at high risk of a diagnosis of lung cancer within one-to-two years.

Tumor Location Is an Independent Prognostic Factor in Completely Resected Pathological Stage I Non-Small Cell Lung Cancer: A Multicenter Retrospective Study

Previous studies suggested that the location of the primary tumor in non-small cell lung cancer (NSCLC) is associated with clinical features and prognosis, but results are conflicting. The purpose of this study was to explore tumor location as an independent risk factor of survival for patients with completely resected pathological stage I NSCLC. This was a multicenter retrospective study conducted in Taiwan. Included patients were diagnosed with stage I NSCLC and had undergone primary tumor resection. Variables including tumor location, pathological stage, histological differentiation, and International Association for the Study of Lung Cancer (IASLC) grade were evaluated for predictive ability for disease-free survival (DFS) and overall survival (OS). A total of 208 patients were included, with 123 (59.1%) patients having a primary tumor in the upper and middle lobes. The median duration of follow-up for survivors was 60.5 months. Compared to patients with IASLC Grade 3 disease, patients with Grade 1 disease had significantly longer DFS. Tumor location and IASLC grade were independent predictors for OS in multivariate analysis. Specifically, patients with NSCLC in the lower lobe and patients who are histologically classified as IASLC Grade 3 may have poorer prognosis and require greater attention to improve outcomes.

Cell-free DNA assay for malignancy classification of high-risk lung nodules

OBJECTIVE

Although low-dose computed tomography has been proven effective to reduce lung cancer-specific mortality, a considerable proportion of surgically resected high-risk lung nodules were still confirmed pathologically benign. There is an unmet need of a novel method for malignancy classification in lung nodules.

METHODS

We recruited 307 patients with high-risk lung nodules who underwent curative surgery, and 247 and 60 cases were pathologically confirmed malignant and benign lung lesions, respectively. Plasma samples from each patient were collected before surgery and performed low-depth (5×) whole-genome sequencing. We extracted cell-free DNA characteristics and determined radiomic features. We built models to classify the malignancy using our data and further validated models with 2 independent lung nodule cohorts.

RESULTS

Our models using one type of profile were able to distinguish lung cancer and benign lung nodules at an area under the curve metrics of 0.69 to 0.91 in the study cohort. Integrating all the 5 base models using cell-free DNA profiles, the cell-free DNA-based ensemble model achieved an area under the curve of 0.95 (95% CI, 0.92-0.97) in the study cohort and 0.98 (95% CI, 0.96-1.00) in the validation cohort. At a specificity of 95.0%, the sensitivity reached 80.0% in the study cohort. With the same threshold, the specificity and sensitivity had similar performances in both validation cohorts. Furthermore, the performance of area under the curve reached 0.97 in both the study and validation cohorts when considering the radiomic profile.

CONCLUSIONS

The cell-free DNA profiles-based method is an efficient noninvasive tool to distinguish malignancies and high-risk but pathologically benign lung nodules.

XPC Protects against Carcinogen-Induced Histologic Progression to Lung Squamous Cell Carcinoma by Reduced Basal Epithelial Cell Proliferation

Lung squamous cell carcinoma (LUSC) is the second leading cause of lung cancer. Although characterized by high DNA mutational burdens and genomic complexity, the role of DNA repair in LUSC development is poorly understood. We sought to better understand the role of the DNA repair protein Xeroderma Pigmentosum Group C (XPC) in LUSC development. XPC knock-out (KO), heterozygous, and wild-type (WT) mice were exposed topically to N-nitroso-tris-chloroethylurea (NTCU), and lungs were evaluated for histology and pre-malignant progression in a blinded fashion at various time-points from 8-24 weeks. High-grade dysplasia and LUSC were increased in XPC KO compared with XPC WT NTCU mice (56% vs. 34%), associated with a higher mean LUSC lung involvement (p < 0.05). N-acetylcysteine pre-treatment decreased bronchoalveolar inflammation but did not prevent LUSC development. Proliferation, measured as %Ki67+ cells, increased with NTCU treatment, in high-grade dysplasia and LUSC, and in XPC deficiency (p < 0.01, ANOVA). Finally, pre-LUSC dysplasia developed earlier and progressed to higher histologic classification sooner in XPC KO compared with WT mice. Overall, this supports the protective role of XPC in squamous dysplasia progression to LUSC. Mouse models of early LUSC development are limited; this may provide a valuable model to study mechanisms of LUSC development and progression.

Outcomes in Incidentally Versus Screening Detected Stage I Lung Cancer Surgery Patients

INTRODUCTION

Although the importance of lung cancer screening for early diagnosis is established, because of poor enrollment, incidental findings still play a role in diagnosis of patients who qualify. Nevertheless, analysis of this incidental cohort is lacking. We present a retrospective analysis comparing patients with thoracic surgery with incidental versus screening detected stage I lung cancer.

METHODS

Thoracic surgery cases at Mount Sinai Hospital from March, 1, 2012, to June, 30, 2022, were queried for patients eligible for lung cancer screening and a stage I diagnosis. The basis of lung nodule detection (incidental versus screening detected) was identified. We compared demographic variables, comorbidities, tumor staging, procedure details, and postoperative outcomes between the cohorts.

RESULTS

Of the patients eligible for screening with lung cancer resection and stage I diagnosis at Mount Sinai, 153 were identified incidentally and 67 through screening. The patients in the incidental cohort were older (p = 0.005), more likely to have quit smoking (p = 0.04), and had a greater number of comorbidities (p = 0.0002). There was no statistically significant difference between the groups with regard to pack-year smoking history, lung cancer histological type, location or size of tumor, and surgical approach, length of surgery or stay, number of postoperative outcomes, and survival.

CONCLUSIONS

In stage I lung cancers, no significant differences were identified between incidentally and screening detected lung nodules with regard to tumor characteristics, surgical approach, and postoperative outcomes. Imaging conducted for other reasons should be considered as a valid and important diagnostic tool, similar to traditional low-dose computed tomography, in patients who qualify for screening.

Perspective on Management of Low-Dose Computed Tomography Findings on Low-Dose Computed Tomography Examinations for Lung Cancer Screening. From the International Association for the Study of Lung Cancer Early Detection and Screening Committee

Lung cancer screening using low-dose computed tomography (LDCT) carefully implemented has been found to reduce deaths from lung cancer. Optimal management starts with selection of eligibility criteria, counseling of screenees, smoking cessation, selection of the regimen of screening which specifies the imaging protocol, and workup of LDCT findings. Coordination of clinical, radiologic, and interventional teams and ultimately treatment of diagnosed lung cancers under screening determine the benefit of LDCT screening. Ethical considerations of who should be eligible for LDCT screening programs are important to provide the benefit to as many people at risk of lung cancer as possible. Unanticipated diseases identified on LDCT may offer important benefits through early detection of leading global causes of death, such as cardiovascular diseases and chronic obstructive pulmonary disease, as the latter may result from conditions such as emphysema and bronchiectasis, which can be identified early on LDCT. This report identifies the key components of the regimen of LDCT screening for lung cancer which include the need for a management system to provide data for continuous updating of the regimen and provides quality assurance assessment of actual screenings. Multidisciplinary clinical management is needed to maximize the benefit of early detection, diagnosis, and treatment of lung cancer. Different regimens have been evolving throughout the world as the resources and needs may be different, for countries with limited resources. Sharing of results, further knowledge, and incorporation of technologic advances will continue to accelerate worldwide improvements in the diagnostic and treatment approaches.

Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers

BACKGROUND

Heavy smokers are at increased risk for cardiovascular disease and may benefit from individualized risk quantification using routine lung cancer screening chest computed tomography. We investigated the prognostic value of deep learning-based automated epicardial adipose tissue quantification and compared it to established cardiovascular risk factors and coronary artery calcium.

METHODS

We investigated the prognostic value of automated epicardial adipose tissue quantification in heavy smokers enrolled in the National Lung Screening Trial and followed for 12.3 (11.9-12.8) years. The epicardial adipose tissue was segmented and quantified on non-ECG-synchronized, non-contrast low-dose chest computed tomography scans using a validated deep-learning algorithm. Multivariable survival regression analyses were then utilized to determine the associations of epicardial adipose tissue volume and density with all-cause and cardiovascular mortality (myocardial infarction and stroke).

RESULTS

Here we show in 24,090 adult heavy smokers (59% men; 61 ± 5 years) that epicardial adipose tissue volume and density are independently associated with all-cause (adjusted hazard ratios: 1.10 and 1.38; P < 0.001) and cardiovascular mortality (adjusted hazard ratios: 1.14 and 1.78; P < 0.001) beyond demographics, clinical risk factors, body habitus, level of education, and coronary artery calcium score.

CONCLUSIONS

Our findings suggest that automated assessment of epicardial adipose tissue from low-dose lung cancer screening images offers prognostic value in heavy smokers, with potential implications for cardiovascular risk stratification in this high-risk population.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations

The ACR created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

Performance of Lung-RADS in different target populations: a systematic review and meta-analysis

OBJECTIVES

Multiple lung cancer screening studies reported the performance of Lung CT Screening Reporting and Data System (Lung-RADS), but none systematically evaluated its performance across different populations. This systematic review and meta-analysis aimed to evaluate the performance of Lung-RADS (versions 1.0 and 1.1) for detecting lung cancer in different populations.

METHODS

We performed literature searches in PubMed, Web of Science, Cochrane Library, and Embase databases on October 21, 2022, for studies that evaluated the accuracy of Lung-RADS in lung cancer screening. A bivariate random-effects model was used to estimate pooled sensitivity and specificity, and heterogeneity was explored in stratified and meta-regression analyses.

RESULTS

A total of 31 studies with 104,224 participants were included. For version 1.0 (27 studies, 95,413 individuals), pooled sensitivity was 0.96 (95% confidence interval [CI]: 0.90-0.99) and pooled specificity was 0.90 (95% CI: 0.87-0.92). Studies in high-risk populations showed higher sensitivity (0.98 [95% CI: 0.92-0.99] vs. 0.84 [95% CI: 0.50-0.96]) and lower specificity (0.87 [95% CI: 0.85-0.88] vs. 0.95 (95% CI: 0.92-0.97]) than studies in general populations. Non-Asian studies tended toward higher sensitivity (0.97 [95% CI: 0.91-0.99] vs. 0.91 [95% CI: 0.67-0.98]) and lower specificity (0.88 [95% CI: 0.85-0.90] vs. 0.93 [95% CI: 0.88-0.96]) than Asian studies. For version 1.1 (4 studies, 8811 individuals), pooled sensitivity was 0.91 (95% CI: 0.83-0.96) and specificity was 0.81 (95% CI: 0.67-0.90).

CONCLUSION

Among studies using Lung-RADS version 1.0, considerable heterogeneity in sensitivity and specificity was noted, explained by population type (high risk vs. general), population area (Asia vs. non-Asia), and cancer prevalence.

CLINICAL RELEVANCE STATEMENT

Meta-regression of lung cancer screening studies using Lung-RADS version 1.0 showed considerable heterogeneity in sensitivity and specificity, explained by the different target populations, including high-risk versus general populations, Asian versus non-Asian populations, and populations with different lung cancer prevalence.

KEY POINTS

• High-risk population studies showed higher sensitivity and lower specificity compared with studies performed in general populations by using Lung-RADS version 1.0. • In non-Asian studies, the diagnostic performance of Lung-RADS version 1.0 tended to be better than in Asian studies. • There are limited studies on the performance of Lung-RADS version 1.1, and evidence is lacking for Asian populations.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations

The American College of Radiology created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

Study rationale and design of the PEOPLHE trial

PURPOSE

Lung cancer screening (LCS) by low-dose computed tomography (LDCT) demonstrated a 20-40% reduction in lung cancer mortality. National stakeholders and international scientific societies are increasingly endorsing LCS programs, but translating their benefits into practice is rather challenging. The "Model for Optimized Implementation of Early Lung Cancer Detection: Prospective Evaluation Of Preventive Lung HEalth" (PEOPLHE) is an Italian multicentric LCS program aiming at testing LCS feasibility and implementation within the national healthcare system. PEOPLHE is intended to assess (i) strategies to optimize LCS workflow, (ii) radiological quality assurance, and (iii) the need for dedicated resources, including smoking cessation facilities.

METHODS

PEOPLHE aims to recruit 1.500 high-risk individuals across three tertiary general hospitals in three different Italian regions that provide comprehensive services to large populations to explore geographic, demographic, and socioeconomic diversities. Screening by LDCT will target current or former (quitting < 10 years) smokers (> 15 cigarettes/day for > 25 years, or > 10 cigarettes/day for > 30 years) aged 50-75 years. Lung nodules will be volumetric measured and classified by a modified PEOPLHE Lung-RADS 1.1 system. Current smokers will be offered smoking cessation support.

CONCLUSION

The PEOPLHE program will provide information on strategies for screening enrollment and smoking cessation interventions; administrative, organizational, and radiological needs for performing a state-of-the-art LCS; collateral and incidental findings (both pulmonary and extrapulmonary), contributing to the LCS implementation within national healthcare systems.

Clinic information, pathological, and imaging characteristics in 2 058 surgical patients with lung cancer from a single center

OBJECTIVES

Lung cancer is characterized by its high incidence and case fatality rate. Factors related to population composition and cancer prevention programme policy have an effect on the incidence and diagnosis of lung cancer. This study aims to provide scientific support for early diagnosis and treatment of lung cancer by investigating the clinic information, pathological, and imaging characteristics of surgical patients with lung cancer.

METHODS

The data of 2 058 patients, who underwent surgery for lung cancer in the Department of Thoracic Surgery of Xiangya Hospital of Central South University from 2016 to 2019, were retrospectively collected to analyze changes in clinic information, pathological, and imaging characteristics.

RESULTS

From 2016 to 2019, the number of patients per year was 280, 376, 524, and 878, respectively. Adenocarcinoma (68.1%) was the most common pathological type of surgical patients with lung cancer. From 2016 to 2019, the proportion of adenocarcinoma was increased from 55.5% to 74.1%. The proportion lung cancer patients in stage IA was increased from 38.9% to 62.3%, and the proportion of patients who underwent sublobar resection was increased from 1.8% to 8.6%. The proportion of lymph node sampling was increased in 2019. Compared with the rate in 2016, the detection rate of nodules with diameter≤1 cm detected by CT before surgery in 2019 was significantly improved (2.0% vs 18.2%), and the detection rate of nodules with diameter>3 cm was decreased (34.7% vs 18.3%). From 2016 to 2019, the proportion of lesions with pure ground-glass density and partial solid density detected by CT was increased from 2.0% and 16.6% to 20.0% and 37.3%, respectively. The proportion of solid density was decreased from 81.4% to 42.7%.

CONCLUSIONS

The number of lung cancer surgery patients is rapidly increasing year by year, the proportion of CT-detected purely ground-glass density and partially solid density lesions are increasing, the proportion of patients with adenocarcinoma is rising, the proportion of early-stage lung cancer is increasing, smaller lung cancers are detected in earlier clinical stage leading to a more minimally invasive approach to the surgical methods.

State of the science and future directions for research on HIV and cancer: Summary of a joint workshop sponsored by IARC and NCI

An estimated 38 million people live with human immunodeficiency virus (HIV) worldwide and are at excess risk for multiple cancer types. Elevated cancer risks in people living with HIV (PLWH) are driven primarily by increased exposure to carcinogens, most notably oncogenic viruses acquired through shared transmission routes, plus acceleration of viral carcinogenesis by HIV-related immunosuppression. In the era of widespread antiretroviral therapy (ART), life expectancy of PLWH has increased, with cancer now a leading cause of co-morbidity and death. Furthermore, the types of cancers occurring among PLWH are shifting over time and vary in their relative burden in different parts of the world. In this context, the International Agency for Research on Cancer (IARC) and the US National Cancer Institute (NCI) convened a meeting in September 2022 of multinational and multidisciplinary experts to focus on cancer in PLWH. This report summarizes the proceedings, including a review of the state of the science of cancer descriptive epidemiology, etiology, molecular tumor characterization, primary and secondary prevention, treatment disparities and survival in PLWH around the world. A consensus of key research priorities and recommendations in these domains is also presented.

Effectiveness of a single low-dose computed tomography screening for lung cancer: A population-based perspective cohort study in China

The purpose of this perspective cohort study was to evaluate the effectiveness of low-dose computed tomography (LDCT) screening for lung cancer in China. This study was conducted under the China Urban Cancer Screening Program (CanSPUC). The analysis was based on participants aged 40 to 74 years from 2012 to 2019. A total of 255 569 eligible participants were recruited in the study. Among the 58 136 participants at high risk of lung cancer, 20 346 (35.00%) had a single LDCT scan (defined as the screened group) and 37 790 (65.00%) not (defined as the non-screened group). Overall, 1162 participants were diagnosed with lung cancer at median follow-up time of 5.25 years. The screened group had the highest cumulative incidence of lung cancer and the non-screened group had the highest cumulative lung cancer mortality and all-cause cumulative mortality. We performed inverse probability weighting (IPW) to account for potential imbalances, and Cox proportional hazards model to estimate the weighted association between mortality and LDCT scans. After IPW adjusted with baseline characteristics, the lung cancer incidence density was significantly increased (37.0% increase) (HR1.37 [95%CI 1.12-1.69]), lung cancer mortality was decreased (31.0% decrease) (HR0.69 [95%CI 0.49-0.97]), and the all-cause mortality was significantly decreased (23.0% lower) (HR0.77 [95% CI 0.68-0.87]) in the screened group. In summary, a single LDCT for lung cancer screening will reduce the mortality of lung cancer and all-cause mortality in China.

[Statement Paper on the Implementation of a National Organized Program in Germany for the Early Detection of Lung Cancer in Risk Populations Using Low-dose CT Screening Including Management of Screening Findings]

The process of implementing early detection of lung cancer with low-dose CT (LDCT) in Germany has gained significant momentum in recent years. It is expected that the ordinance of the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) on early detection of lung cancer, which has been commented on by the professional societies, will come into effect by the end of 2023. Based on this regulation, the Federal Joint Committee (G-BA) will set up a program for early lung cancer detection with LDCT in the near future. In this position paper, the specialist societies involved in lung cancer screening present concrete cornerstones for a uniform, structured and quality-assured early detection program for lung cancer in Germany to make a constructive contribution to this process.

Optimizing tissue stewardship in non-small cell lung cancer to support molecular characterization and treatment selection: statement from a working group of thoracic pathologists

Many patients with non-small cell lung cancer do not receive guideline-recommended, biomarker-directed therapy, despite the potential for improved clinical outcomes. Access to timely, accurate, and comprehensive molecular profiling, including targetable protein overexpression, is essential to allow fully informed treatment decisions to be taken. In turn, this requires optimal tissue management to protect and maximize the use of this precious finite resource. Here, a group of leading thoracic pathologists recommend factors to consider for optimal tissue management. Starting from when lung cancer is first suspected, keeping predictive biomarker testing in the front of the mind should drive the development of practices and procedures that conserve tissue appropriately to support molecular characterization and treatment selection.

[Statement paper on the implementation of a national organized program in Germany for the early detection of lung cancer in risk populations using low-dose CT screening including management of screening findings]

The process of implementing early detection of lung cancer with low-dose CT (LDCT) in Germany has gained significant momentum in recent years. It is expected that the ordinance of the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) on the early detection of lung cancer, which has been commented on by the professional societies, will come into effect by the end of 2023. Based on this regulation, the Federal Joint Committee (G-BA) will set up a program for early lung cancer detection with LDCT in the near future. In this position paper, the specialist societies involved in lung cancer screening present key points for a uniform, structured and quality-assured early detection program for lung cancer in Germany to make a constructive contribution to this process. CITATION FORMAT: · Vogel-Claussen J, Blum TG, Andreas S et al. Position paper on the implementation of a nationally organized program in Germany for the early detection of lung cancer in high-risk populations using low-dose CT screening including the management of screening findings requiring further workup. Fortschr Röntgenstr 2024; 196: DOI 10.1055/a-2178-2846.

Can Artificial Intelligence Replace Humans for Detecting Lung Tumors on Radiographs? An Examination of Resected Malignant Lung Tumors

OBJECTIVE

Although lung cancer screening trials have showed the efficacy of computed tomography to decrease mortality compared with chest radiography, the two are widely taken as different kinds of clinical practices. Artificial intelligence can improve outcomes by detecting lung tumors in chest radiographs. Currently, artificial intelligence is used as an aid for physicians to interpret radiograms, but with the future evolution of artificial intelligence, it may become a modality that replaces physicians. Therefore, in this study, we investigated the current situation of lung cancer diagnosis by artificial intelligence.

METHODS

In total, we recruited 174 consecutive patients with malignant pulmonary tumors who underwent surgery after chest radiography that was checked by artificial intelligence before surgery. Artificial intelligence diagnoses were performed using the medical image analysis software EIRL X-ray Lung Nodule version 1.12, (LPIXEL Inc., Tokyo, Japan).

RESULTS

The artificial intelligence determined pulmonary tumors in 90 cases (51.7% for all patients and 57.7% excluding 18 patients with adenocarcinoma in situ). There was no significant difference in the detection rate by the artificial intelligence among histological types. All eighteen cases of adenocarcinoma in situ were not detected by either the artificial intelligence or the physicians. In a univariate analysis, the artificial intelligence could detect cases with larger histopathological tumor size (p < 0.0001), larger histopathological invasion size (p < 0.0001), and higher maximum standardized uptake values of positron emission tomography-computed tomography (p < 0.0001). In a multivariate analysis, detection by AI was significantly higher in cases with a large histopathological invasive size (p = 0.006). In 156 cases excluding adenocarcinoma in situ, we examined the rate of artificial intelligence detection based on the tumor site. Tumors in the lower lung field area were less frequently detected (p = 0.019) and tumors in the middle lung field area were more frequently detected (p = 0.014) compared with tumors in the upper lung field area.

CONCLUSIONS

Our study showed that using artificial intelligence, the diagnosis of tumor-associated findings and the diagnosis of areas that overlap with anatomical structures is not satisfactory. While the current standing of artificial intelligence diagnostics is to assist physicians in making diagnoses, there is the possibility that artificial intelligence can substitute for humans in the future. However, artificial intelligence should be used in the future as an enhancement, to aid physicians in the role of a radiologist in the workflow.

How well does your e-nose detect cancer? Application of artificial breath analysis for performance assessment

Comparing electronic nose (e-nose) performance is a challenging task because of a lack of standardised method. This paper proposes a method for defining and quantifying an indicator of the effectiveness of multi-sensor systems in detecting cancers by artificial breath analysis. To build this method, an evaluation of the performances of an array of metal oxide sensors built for use as a lung cancer screening tool was conducted. Breath from 20 healthy volunteers has been sampled in fluorinated ethylene propylene sampling bags. These healthy samples were analysed with and without the addition of nine volatile organic compound (VOC) cancer biomarkers, chosen from literature. The concentration of the VOC added was done in increasing amounts. The more VOC were added, the better the discrimination between 'healthy' samples (breath without additives) and 'cancer' samples (breath with additives) was. By determining at which level of concentration the e-nose fails to reliably discriminate between the two groups, we estimate its ability to well predict the presence of the disease or not in a realistic situation. In this work, a home-made e-nose is put to the test. The results underline that the biomarkers need to be about 5.3 times higher in concentration than in real breath for the home-made nose to tell the difference between groups with a sufficient confidence.

[Effectiveness Evaluation of Low-dose Spiral Computed Tomography for Lung Cancer Screening in Minhang District of Shanghai]

BACKGROUND

Low-dose spiral computed tomography (LDCT) has been recommended for lung cancer screening in high-risk populations. However, evidence from Chinese populations was limited due to the different criteria for high-risk populations and the short-term follow-up period. This study aimed to evaluate the effectiveness in Chinese adults based on the Lung Cancer Screening Program in Minhang District of Shanghai initiated in 2013.

METHODS

A total of 26,124 subjects aged 40 years or above were enrolled in the Lung Cancer Screening Program during the period of 2013 and 2017. Results of LDCT examination, and screen-detected cancer cases in all participants were obtained from the Reporting System of the Lung Cancer Screening Program. The newly-diagnosed cases and their vital status up to December 31, 2020 were identified through a record linkage with the Shanghai Cancer Registry and the Shanghai Vital Statistics. Standardized incidence ratio (SIR) and 95%CI were calculated using the local population at ages of 40 or above as the reference. Proportions of early-stage cancer (stage 0-I), pathological types, and 5-year observed survival rates of lung cancer cases were estimated and compared between the cases derived from the screened and non-screened populations. Cox regression models were applied to evaluate the hazard ratio (HR) and 95%CI of LDCT screening with all-cause death of the lung cancer cases.

RESULTS

The crude and age-standardized incidence of lung cancer in screened population were 373.3 (95%CI: 343.1-406.1) and 70.3 per 100,000 person-years, respectively, with an SIR of 1.8 (95%CI: 1.6-1.9), which was observed to decrease with following-up time. The early-stage cancer accounted for 49.4% of all lung cancer cases derived from the screened population, significantly higher than 38.4% in cases from the non-screened population during the same period (P<0.05). The proportion of lung adenocarcinoma (40.7% vs 35.9%) and 5-year survival rate (53.7% vs 41.5%) were also significantly higher in the cases from the screened population (all P<0.05). LDCT screening was associated with 30% (HR=0.7, 95%CI: 0.6-0.8) reduced all-cause deaths of the cases.

CONCLUSIONS

The participants of the screening program are at high-risk of lung cancer. LDCT favors the early-detection of lung cancer and improves 5-year survival of the screened cases, indicating a great potential of LDCT in reducing the disease burden of lung cancer in Chinese populations.

Long-term trends of lung cancer incidence and survival in southeastern China, 2011-2020: a population-based study

BACKGROUND

Lung cancer is the primary cause of cancer-related deaths in China. This study analysed the incidence and survival trends of lung cancer from 2011 to 2020 in Fujian Province, southeast of China, and provided basis for formulating prevention and treatment strategies.

METHODS

The population-based cancer data was used to analyse the incidence of lung cancer between 2011 and 2020, which were stratified by sex, age and histology. The change of incidence trend was analysed using Joinpoint regression. The relative survival of lung cancer with onset in 2011-2014, 2015-2017 and 2018-2020 were calculated using the cohort, complete and period methods, respectively.

RESULTS

There were 23,043 patients diagnosed with lung cancer in seven registries between 2011 and 2020, with an age-standardized incidence rate (ASIR) of 37.7/100,000. The males ASIR increased from 51.1/100,000 to 60.5/100,000 with an annual percentage change (APC) of 1.5%. However, females ASIR increased faster than males, with an APC of 5.7% in 2011-2017 and 21.0% in 2017-2020. Compared with 2011, the average onset age of males and females in 2020 was 1.5 years and 5.9 years earlier, respectively. Moreover, the proportion of adenocarcinoma has increased, while squamous cell carcinoma and small cell carcinoma have decreased over the past decade. The 5-year relative survival of lung cancer increased from 13.8 to 23.7%, with a greater average increase in females than males (8.7% and 2.6%). The 5-year relative survival of adenocarcinoma, squamous cell carcinoma and small cell carcinoma reached 47.1%, 18.3% and 6.9% in 2018-2020, respectively.

CONCLUSIONS

The incidence of lung cancer in Fujian Province is on the rise, with a significant rise in adenocarcinoma, a younger age of onset and the possibility of overdiagnosis. Thus, Fujian Province should strengthen the prevention and control of lung cancer, giving more attention to the prevention and treatment of lung cancer in females and young populations.

Evaluation of Conventional Cardiovascular Risk Factors and Ordinal Coronary Artery Calcium Scoring in a Lung Cancer Screening Cohort

(1) Background: Lung cancer screening (LCS) consists of low-dose computed tomography (LDCT) results to reduce lung cancer-related mortality. The LCS program has a unique opportunity to impact CVD mortality by providing tools for CVD risk assessment and implementing preventative strategies. In this study, we estimated standardized CVD risk (SCORE) and assessed the prevalence of coronary artery calcium (CAC) in a Polish LCS cohort. (2) Methods: In this observational study, 494 LCS participants aged 50-79 years with a cigarette smoking history of at least 30 pack-years were included. Medical history, anthropometric measurements, blood pressure measurements, serum glucose, and cholesterol levels were assessed in one visit. CVD risk assessment using SCORE tables was performed. The results were compared to the general population (NATPOL 2011 study). On LDCT scans, CAC was classified using an Ordinal Score ranging from 0 to 12. (3) Results: The prevalence of classic cardiovascular risk factors was very high. Among study participants, 83.7% of men and 40.7% of women were classified with a very high CVD SCORE risk (>10%). CAC was reported in 190 (47%) participants. Calcification was categorized as severe (CAC ≥ 4) in 84 (21%) participants. (4) Conclusions: Due to the high cardiovascular risk, intensive preventive strategies are recommended for LCS participants.

Integrative Multianalytical Model Based on Novel Plasma Protein Biomarkers for Distinguishing Lung Adenocarcinoma and Benign Pulmonary Nodules

Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis (data are available via ProteomeXchange with identifier PXD046731), 12 differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of DEPs were validated in two independent validation cohorts. The results showed that the levels of three candidate proteins (PRDX2, PON1, and APOC3) were lower in the plasma of LUAD than in BPN. The three candidate proteins were combined with three promising computed tomography indicators (spiculation, vascular notch sign, and lobulation) and three traditional markers (CEA, CA125, and CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with an AUC of 0.904, a sensitivity of 81.44%, and a specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity, and accuracy of 0.868, 65.63%, 90.14%, and 82.52%, respectively. This model may be a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity.

The International Association for the Study of Lung Cancer Early Lung Imaging Confederation Open-Source Deep Learning and Quantitative Measurement Initiative

INTRODUCTION

With global adoption of computed tomography (CT) lung cancer screening, there is increasing interest to use artificial intelligence (AI) deep learning methods to improve the clinical management process. To enable AI research using an open-source, cloud-based, globally distributed, screening CT imaging data set and computational environment that are compliant with the most stringent international privacy regulations that also protect the intellectual properties of researchers, the International Association for the Study of Lung Cancer sponsored development of the Early Lung Imaging Confederation (ELIC) resource in 2018. The objective of this report is to describe the updated capabilities of ELIC and illustrate how this resource can be used for clinically relevant AI research.

METHODS

In this second phase of the initiative, metadata and screening CT scans from two time points were collected from 100 screening participants in seven countries. An automated deep learning AI lung segmentation algorithm, automated quantitative emphysema metrics, and a quantitative lung nodule volume measurement algorithm were run on these scans.

RESULTS

A total of 1394 CTs were collected from 697 participants. The LAV950 quantitative emphysema metric was found to be potentially useful in distinguishing lung cancer from benign cases using a combined slice thickness more than or equal to 2.5 mm. Lung nodule volume change measurements had better sensitivity and specificity for classifying malignant from benign lung nodules when applied to solid lung nodules from high-quality CT scans.

CONCLUSIONS

These initial experiments revealed that ELIC can support deep learning AI and quantitative imaging analyses on diverse and globally distributed cloud-based data sets.

[Statement paper on the implementation of a national organized program in Germany for the early detection of lung cancer in risk populations using low-dose CT screening including management of screening findings]

The process of implementing early detection of lung cancer with low-dose CT (LDCT) in Germany has gained significant momentum in recent years. It is expected that the ordinance of the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) on early detection of lung cancer, which has been commented on by the professional societies, will come into effect by the end of 2023. Based on this regulation, the Federal Joint Committee (G-BA) will set up a program for early lung cancer detection with LDCT in the near future. In this position paper, the specialist societies involved in lung cancer screening present concrete cornerstones for a uniform, structured and quality-assured early detection program for lung cancer in Germany to make a constructive contribution to this process.

Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities

Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.

Hypoxia A Typical Target in Human Lung Cancer Therapy

Lung cancer (LC) is the leading cause of cancer-related death globally. Comprehensive knowledge of the cellular and molecular etiology of LC is perilous for the development of active treatment approaches. Hypoxia in cancer is linked with malignancy, and its phenotype is implicated in the hypoxic reaction, which is being studied as a prospective cancer treatment target. The hypervascularization of the tumor is the main feature of human LC, and hypoxia is a major stimulator of neo-angiogenesis. It was seen that low oxygen levels in human LC are a critical aspect of this lethal illness. However, as there is a considerable body of literature espousing the presumed functional relevance of hypoxia in LC, the direct measurement of oxygen concentration in Human LC is yet to be determined. This narrative review aims to show the importance and as a future target for novel research studies that can lead to the perception of LC therapy in hypoxic malignancies.

Opportunistic Screening With Low-Dose Computed Tomography and Lung Cancer Mortality in China

Importance

Despite the recommendations of lung cancer screening guidelines and the evidence supporting the effectiveness of population-based lung screening, a common barrier to effective lung cancer screening is that the participation rates of low-dose computed tomography (LDCT) screening among individuals with the highest risk are not large. There are limited data from clinical practice regarding whether opportunistic LDCT screening is associated with reduced lung-cancer mortality.

Objective

To evaluate whether opportunistic LDCT screening is associated with improved prognosis among adults with lung cancer in mainland China.

Design, Setting, and Participants

This cohort study included patients diagnosed with lung cancer at Weihai Municipal Hospital Healthcare Group, Weihai City, China, from 2016 to 2021. Data were analyzed from January 2022 to February 2023.

Exposures

Data collected included demographic indicators, tumor characteristics, comorbidities, blood indexes, and treatment information. Patients were classified into screened and nonscreened groups on the basis of whether or not their lung cancer diagnosis occurred through opportunistic screening.

Main Outcomes and Measures

Follow-up outcome indicators included lung cancer-specific mortality and all-cause mortality. Propensity score matching (PSM) was adopted to account for potential imbalanced factors between groups. The associations between LDCT screening and outcomes were analyzed using Cox regression models based on the matched data. Propensity score regression adjustment and inverse probability treatment weighting were used for sensitivity analysis.

Results

A total of 5234 patients (mean [SD] baseline age, 61.8 [9.8] years; 2518 [48.1%] female) with complete opportunistic screening information were included in the analytical sample, with 2251 patients (42.91%) receiving their lung cancer diagnosis through opportunistic screening. After 1:1 PSM, 2788 patients (1394 in each group) were finally included. The baseline characteristics of the matched patients were balanced between groups. Opportunistic screening with LDCT was associated with a 49% lower risk of lung cancer death (HR, 0.51; 95% CI, 0.42-0.62) and 46% lower risk of all-cause death (HR, 0.54; 95% CI, 0.45-0.64).

Conclusions and Relevance

In this cohort study of patients with lung cancer, opportunistic lung cancer screening with LDCT was associated with lower lung cancer mortality and all-cause mortality. These findings suggest that opportunistic screening is an important supplement to population screening to improve prognosis of adults with lung cancer.

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

BACKGROUND

The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.

METHODS

In this retrospective study, an AI algorithm was proposed for measuring the solid components ratio in SSNs, which was used to assess the diameter ratio (1D), area ratio (2D), and volume ratio (3D). The radiologist measured each SSN's consolidation to tumor ratio (CTR) twice, four weeks apart. The area under the receiver-operating characteristic (ROC) curve (AUC) was calculated for each method used to discriminate an Invasive Adenocarcinoma (IA) from a non-IA. The AUC and the time cost of each measurement were compared. Furthermore, we examined the consistency of measurements made by the radiologist on two separate occasions.

RESULTS

A total of 379 patients (the primary dataset n = 278, the validation dataset n = 101) were included. In the primary dataset, compared to the manual approach (AUC: 0.697), the AI algorithm (AUC: 0.811) had better predictive performance (P =.0027) in measuring solid components ratio in 3D. Algorithm measurement in 3D had an AUC no inferior to 1D (AUC: 0.806) and 2D (AUC: 0.796). In the validation dataset, the AI 3D method also achieved superior diagnostic performance compared to the radiologist (AUC: 0.803 vs 0.682, P =.046). The two measurements of the CTR in the primary dataset, taken 4 weeks apart, have 7.9 % cases in poor consistency. The measurement time cost by the radiologist is about 60 times that of the AI algorithm (P <.001).

CONCLUSION

The 3D measurement of solid components using AI, is an effective and objective approach to predict the pathological invasiveness of SSNs. It can be a preoperative interpretable indicator of pathological invasiveness in patients with lung adenocarcinoma.

A novel fusion algorithm for benign-malignant lung nodule classification on CT images

The accurate recognition of malignant lung nodules on CT images is critical in lung cancer screening, which can offer patients the best chance of cure and significant reductions in mortality from lung cancer. Convolutional Neural Network (CNN) has been proven as a powerful method in medical image analysis. Radiomics which is believed to be of interest based on expert opinion can describe high-throughput extraction from CT images. Graph Convolutional Network explores the global context and makes the inference on both graph node features and relational structures. In this paper, we propose a novel fusion algorithm, RGD, for benign-malignant lung nodule classification by incorporating Radiomics study and Graph learning into the multiple Deep CNNs to form a more complete and distinctive feature representation, and ensemble the predictions for robust decision-making. The proposed method was conducted on the publicly available LIDC-IDRI dataset in a 10-fold cross-validation experiment and it obtained an average accuracy of 93.25%, a sensitivity of 89.22%, a specificity of 95.82%, precision of 92.46%, F1 Score of 0.9114 and AUC of 0.9629. Experimental results illustrate that the RGD model achieves superior performance compared with the state-of-the-art methods. Moreover, the effectiveness of the fusion strategy has been confirmed by extensive ablation studies. In the future, the proposed model which performs well on the pulmonary nodule classification on CT images will be applied to increase confidence in the clinical diagnosis of lung cancer.

Long-term outcomes of lung cancer screening in males and females

BACKGROUND

This study explored female and male overall mortality and lung cancer (LC) survival in two LC screening (LCS) populations, focusing on the predictive value of coronary artery calcification (CAC) at baseline low-dose computed tomography (LDCT).

METHODS

This retrospective study analysed data of 6495 heavy smokers enrolled in the MILD and BioMILD LCS trials between 2005 and 2016. The primary objective of the study was to assess sex differences in all-cause mortality and LC survival. CAC scores were automatically calculated on LDCT images by a validated artificial intelligence (AI) software. Sex differences in 12-year cause-specific mortality rates were stratified by age, pack-years and CAC score.

RESULTS

The study included 2368 females and 4127 males. The 12-year all-cause mortality rates were 4.1 % in females and 7.7 % in males (p < 0.0001), and median CAC score was 8.7 vs. 41 respectively (p < 0.0001). All-cause mortality increased with rising CAC scores (log-rank test, p < 0.0001) for both sexes. Although LC incidence was not different between the two sexes, females had lower rates of 12-year LC mortality (1.0 % vs. 1.9 %, p = 0.0052), and better LC survival from diagnosis (72.3 % vs. 51.7 %; p = 0.0005), with a similar proportion of stage I (58.1 % vs. 51.2 %, p = 0.2782).

CONCLUSIONS

Our findings demonstrate that female LCS participants had lower rates of all-cause mortality at 12 years and better LC survival than their male counterparts, with similar LC incidence rates and stage at diagnosis. The lower CAC burden observed in women at all ages might contribute to explain their lower rates of all-cause mortality and better LC survival.