Lung cancer mortality reduction by LDCT screening-Results from the randomized German LUSI trial

Generalizability and Transportability of the National Lung Screening Trial Data: Extending Trial Results to Different Populations

BACKGROUND

Randomized controlled trials (RCT) play a central role in evidence-based healthcare. However, the clinical and policy implications of implementing RCTs in clinical practice are difficult to predict as the studied population is often different from the target population where results are being applied. This study illustrates the concepts of generalizability and transportability, demonstrating their utility in interpreting results from the National Lung Screening Trial (NLST).

METHODS

Using inverse-odds weighting, we demonstrate how generalizability and transportability techniques can be used to extrapolate treatment effect from (i) a subset of NLST to the entire NLST population and from (ii) the entire NLST to different target populations.

RESULTS

Our generalizability analysis revealed that lung cancer mortality reduction by LDCT screening across the entire NLST [16% (95% confidence interval [CI]: 4-24)] could have been estimated using a smaller subset of NLST participants. Using transportability analysis, we showed that populations with a higher prevalence of females and current smokers had a greater reduction in lung cancer mortality with LDCT screening [e.g., 27% (95% CI, 11-37) for the population with 80% females and 80% current smokers] than those with lower prevalence of females and current smokers.

CONCLUSIONS

This article illustrates how generalizability and transportability methods extend estimation of RCTs' utility beyond trial participants, to external populations of interest, including those that more closely mirror real-world populations.

IMPACT

Generalizability and transportability approaches can be used to quantify treatment effects for populations of interest, which may be used to design future trials or adjust lung cancer screening eligibility criteria.

Next Generation Sequencing Technology in Lung Cancer Diagnosis

Simple Summary

Lung cancer is still one of the most commonly diagnosed and deadliest cancers in the world. Its diagnosis at an early stage is highly necessary and will improve the standard of care of this disease. The aim of this article is to review the importance and applications of next generation sequencing in lung cancer diagnosis. As observed in many studies, next generation sequencing has been proven as a very helpful tool in the early detection of different types of cancers, including lung cancer, and has been used in the clinic, mainly due to its many advantages, such as low cost, speed, efficacy, low quantity usage of biological samples, and diversity.

Abstract

Lung cancer is still one of the most commonly diagnosed cancers, and one of the deadliest. The high death rate is mainly due to the late stage of diagnosis and low response rate to therapy. Previous and ongoing research studies have tried to discover new reliable and useful cbiomarkers for the diagnosis and prognosis of lung cancer. Next generation sequencing has become an essential tool in cancer diagnosis, prognosis, and evaluation of the treatment response. This article aims to review the leading research and clinical applications in lung cancer diagnosis using next generation sequencing. In this scope, we identified the most relevant articles that present the successful use of next generation sequencing in identifying biomarkers for early diagnosis correlated to lung cancer diagnosis and treatment. This technique can be used to evaluate a high number of biomarkers in a short period of time and from small biological samples, which makes NGS the preferred technique to develop clinical tests for personalized medicine using liquid biopsy, the new trend in oncology.

Combining pulmonary and cardiac computed tomography biomarkers for disease-specific risk modelling in lung cancer screening

OBJECTIVES

Combined assessment of cardiovascular disease (CVD), COPD and lung cancer may improve the effectiveness of lung cancer screening in smokers. The aims were to derive and assess risk models for predicting lung cancer incidence, CVD mortality and COPD mortality by combining quantitative computed tomography (CT) measures from each disease, and to quantify the added predictive benefit of self-reported patient characteristics given the availability of a CT scan.

METHODS

A survey model (patient characteristics only), CT model (CT information only) and final model (all variables) were derived for each outcome using parsimonious Cox regression on a sample from the National Lung Screening Trial (n=15 000). Validation was performed using Multicentric Italian Lung Detection data (n=2287). Time-dependent measures of model discrimination and calibration are reported.

RESULTS

Age, mean lung density, emphysema score, bronchial wall thickness and aorta calcium volume are variables that contributed to all final models. Nodule features were crucial for lung cancer incidence predictions but did not contribute to CVD and COPD mortality prediction. In the derivation cohort, the lung cancer incidence CT model had a 5-year area under the receiver operating characteristic curve of 82.5% (95% CI 80.9-84.0%), significantly inferior to that of the final model (84.0%, 82.6-85.5%). However, the addition of patient characteristics did not improve the lung cancer incidence model performance in the validation cohort (CT model 80.1%, 74.2-86.0%; final model 79.9%, 73.9-85.8%). Similarly, the final CVD mortality model outperformed the other two models in the derivation cohort (survey model 74.9%, 72.7-77.1%; CT model 76.3%, 74.1-78.5%; final model 79.1%, 77.0-81.2%), but not the validation cohort (survey model 74.8%, 62.2-87.5%; CT model 72.1%, 61.1-83.2%; final model 72.2%, 60.4-84.0%). Combining patient characteristics and CT measures provided the largest increase in accuracy for the COPD mortality final model (92.3%, 90.1-94.5%) compared to either other model individually (survey model 87.5%, 84.3-90.6%; CT model 87.9%, 84.8-91.0%), but no external validation was performed due to a very low event frequency.

CONCLUSIONS

CT measures of CVD and COPD provides small but reproducible improvements to nodule-based lung cancer risk prediction accuracy from 3 years onwards. Self-reported patient characteristics may not be of added predictive value when CT information is available.

Long-term Lung Cancer Risk Associated with Sputum Atypia: A 27-Year Follow-up Study of an Occupational Lung Screening Cohort in Yunnan, China

BACKGROUND

Sputum cytologic atypia is associated with increased lung cancer risk. However, little is known about the long-term magnitude and temporal trend of this risk.

METHODS

An extended follow-up was conducted in a prospective screening cohort among occupational tin miners in Yunnan, China. Sputum samples were collected prospectively at baseline and 7 annual screenings since enrollment. The associations between sputum cytologic results from baseline screening, the first 4 consecutive rounds of sputum screening, and lung cancer risk were analyzed by time-varying covariate Cox regression model.

RESULTS

A moderate or worse cytologic result was associated with a significantly increased lung cancer risk. This relative hazard significantly decreased over time. Compared with negative screening results, the adjusted hazard ratios of baseline-moderate or worse atypia, at least one moderate or worse atypia in the first 4 consecutive screening rounds during the first 10 years of follow-up were 3.11 [95% confidence interval (CI): 2.37-4.07], 3.25 (95% CI: 2.33-4.54) respectively. This association was stronger for persistent atypia (adjusted hazard ratio = 17.55, 95% CI: 8.32-37.03); atypia identified in the recent screening rounds (adjusted HR = 4.14, 95% CI: 2.70-6.35), and those were old in age, had higher level of smoking, occupational radon, and arsenic exposure. In terms of histology, this increased risk was significant for squamous cell carcinoma and small cell lung cancer.

CONCLUSIONS

Although decreasing over time, an increased lung cancer risk concerning moderate or worse sputum atypia can continue at least for 10 years.

IMPACT

Sputum atypia might be helpful for identifying high-risk individuals for screening, surveillance, or chemoprevention of lung cancer.

Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine

Medical imaging is the standard-of-care for early detection, diagnosis, treatment planning, monitoring, and image-guided interventions of lung cancer patients. Most medical images are stored digitally in a standardized Digital Imaging and Communications in Medicine format that can be readily accessed and used for qualitative and quantitative analysis. Over the several last decades, medical images have been shown to contain complementary and interchangeable data orthogonal to other sources such as pathology, hematology, genomics, and/or proteomics. As such, "radiomics" has emerged as a field of research that involves the process of converting standard-of-care images into quantitative image-based data that can be merged with other data sources and subsequently analyzed using conventional biostatistics or artificial intelligence (AI) methods. As radiomic features capture biological and pathophysiological information, these quantitative radiomic features have shown to provide rapid and accurate noninvasive biomarkers for lung cancer risk prediction, diagnostics, prognosis, treatment response monitoring, and tumor biology. In this review, radiomics and emerging AI methods in lung cancer research are highlighted and discussed including advantages, challenges, and pitfalls.

Does lung cancer screening with low-dose computerized tomography improve survival?

A best evidence topic in thoracic surgery was written according to a structured protocol. The question addressed was 'Does lung cancer screening with low-dose computerised tomography (LDCT) improve survival?' More than 963 papers were found, of which 8 randomized control trials and 1 meta-analysis represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers were tabulated. The majority of studies trended towards greater incidence of early lung cancer detection, and subsequent curative treatment, in the LDCT screening populations with appropriately powered randomized control trials (NELSON and NLST) demonstrating survival benefits of >20% in lung cancer-specific mortality. However, this reduction must be evaluated against the potential harms associated with screening, including complications from diagnostic procedures, and costs of overdiagnosis, as evidenced in several studies. We conclude that in high-risk populations, lung cancer screening with LDCT results in earlier detection of low-stage cancers and improved survival when compared to usual clinical care or screening with a chest X-ray.

Contemporary issues in the implementation of lung cancer screening

Lung cancer screening with low-dose computed tomography can reduce death from lung cancer by 20-24% in high-risk smokers. National lung cancer screening programmes have been implemented in the USA and Korea and are being implemented in Europe, Canada and other countries. Lung cancer screening is a process, not a test. It requires an organised programmatic approach to replicate the lung cancer mortality reduction and safety of pivotal clinical trials. Cost-effectiveness of a screening programme is strongly influenced by screening sensitivity and specificity, age to stop screening, integration of smoking cessation intervention for current smokers, screening uptake, nodule management and treatment costs. Appropriate management of screen-detected lung nodules has significant implications for healthcare resource utilisation and minimising harm from radiation exposure related to imaging studies, invasive procedures and clinically significant distress. This review focuses on selected contemporary issues in the path to implement a cost-effective lung cancer screening at the population level. The future impact of emerging technologies such as deep learning and biomarkers are also discussed.

Addressing Gender Disparities in Lung Cancer Screening Eligibility: USPSTF versus PLCOm2012 Criteria

BACKGROUND

Lung cancer is the leading cause of cancer death in women in the United States. Prospective randomized lung screening trials suggest a greater lung cancer mortality benefit from screening women compared to men.

RESEARCH QUESTION

Do the United States Preventative Services Task Force (USPSTF) lung screening guidelines that are based solely on age and smoking history contribute to gender disparities in eligibility, and if so, does the use of the PLCOm2012 risk prediction model that is based on 11 predictors of lung cancer reduce gender disparities?

STUDY DESIGN AND METHODS

This retrospective analysis of 883 lung cancer cases in the Chicago Race Eligibility for Screening Cohort (CREST) determined the sensitivity of USPSTF versus PLCOm2012 eligibility criteria, stratified by gender. For comparisons to the USPSTF 2013and the recently published USPSTF 2021(released March 9^th, 2021) eligibility criteria, the PLCOm2012 model was used with risk thresholds of ≥1.7%/6y and >1.0%/6y, respectively.

RESULTS

The sensitivities for screening by the USPSTF 2013were 46.7% for women and 64.6% for men (p=0.003) and by the USPSTF 2021were 56.8% and 71.8%, respectively (p=0.02). In contrast, the PLCOm2012 ≥1.7%/6y sensitivities were 64.6% and 70.4%, respectively, and the PLCOm2012 ≥1.0%/6y sensitivities were 77.4% and 82.4%, respectively. The PLCOm2012 differences in sensitivity using ≥1.7%/6y and ≥1.0%/6y thresholds between women and men were nonsignificant (both p=0.07). Compared to men, women were more likely to be ineligible by the USPSTF 2021criteria because their smoking exposures were <20 pack-years (22.8% vs 14.8%, OR_{Women vs Men} 1.70, 95% CI 1.19-2.44; p=0.002) and 27% of these ineligible women were eligible by the PLCOm2012 >1.0%/6y criteria.

INTERPRETATION

Although the USPSTF 2021eligibility criteria are more sensitive than the USPSTF 2013guidelines, there remains gender disparities in eligibility. Adding the PLCOm2012 risk prediction model to the USPSTF guidelines would improve sensitivity and attenuate gender disparities.

Screening for Lung Cancer: CHEST Guideline and Expert Panel Report - Executive Summary

BACKGROUND

Low-dose chest CT screening for lung cancer has become a standard of care in the United States, in large part due to the results of the National Lung Screening Trial. Additional evidence supporting the net benefit of low-dose chest CT screening for lung cancer, as well as increased experience in minimizing the potential harms, has accumulated since the prior iteration of these guidelines. Here, we update the evidence base for the benefit, harms, and implementation of low-dose chest CT screening. We use the updated evidence base to provide recommendations where the evidence allows, and statements based on experience and expert consensus where it does not.

METHODS

Approved panelists reviewed previously developed key questions using the PICO (population, intervention, comparator, and outcome) format to address the benefit and harms of low-dose CT screening, as well as key areas of program implementation. A systematic literature review was conducted using MEDLINE via PubMed, Embase, and the Cochrane Library on a quarterly basis since the time of the previous guideline publication. Reference lists from relevant retrievals were searched, and additional papers were added. Retrieved references were reviewed for relevance by two panel members. The quality of the evidence was assessed for each critical or important outcome of interest using the GRADE approach. Meta-analyses were performed where appropriate. Important clinical questions were addressed based on the evidence developed from the systematic literature review. Graded recommendations and un-graded statements were drafted, voted on, and revised until consensus was reached.

RESULTS

The systematic literature review identified 75 additional studies that informed the response to the 12 key questions that were developed. Additional clinical questions were addressed resulting in 7 graded recommendations and 9 ungraded consensus statements.

CONCLUSIONS

Evidence suggests that low-dose CT screening for lung cancer can result in a favorable balance of benefit and harms. The selection of screen-eligible individuals, the quality of imaging and image interpretation, the management of screen detected findings, and the effectiveness of smoking cessation interventions, can impact this balance.

Lung cancer screening implementation: Complexities and priorities

Lung cancer is the number one cause of cancer death worldwide. The benefits of lung cancer screening to reduce mortality and detect early-stage disease are no longer in any doubt based on the results of two landmark trials using LDCT. Lung cancer screening has been implemented in the US and South Korea and is under consideration by other communities. Successful translation of demonstrated research outcomes into the routine clinical setting requires careful implementation and co-ordinated input from multiple stakeholders. Implementation aspects may be specific to different healthcare settings. Important knowledge gaps remain, which must be addressed in order to optimize screening benefits and minimize screening harms. Lung cancer screening differs from all other cancer screening programmes as lung cancer risk is driven by smoking, a highly stigmatized behaviour. Stigma, along with other factors, can impact smokers' engagement with screening, meaning that smokers are generally 'hard to reach'. This review considers critical points along the patient journey. The first steps include selecting a risk threshold at which to screen, successfully engaging the target population and maximizing screening uptake. We review barriers to smoker engagement in lung and other cancer screening programmes. Recruitment strategies used in trials and real-world (clinical) programmes and associated screening uptake are reviewed. To aid cross-study comparisons, we propose a standardized nomenclature for recording and calculating recruitment outcomes. Once participants have engaged with the screening programme, we discuss programme components that are critical to maximize net benefit. A whole-of-programme approach is required including a standardized and multidisciplinary approach to pulmonary nodule management, incorporating probabilistic nodule risk assessment and longitudinal volumetric analysis, to reduce unnecessary downstream investigations and surgery; the integration of smoking cessation; and identification and intervention for other tobacco related diseases, such as coronary artery calcification and chronic obstructive pulmonary disease. National support, integrated with tobacco control programmes, and with appropriate funding, accreditation, data collection, quality assurance and reporting mechanisms will enhance lung cancer screening programme success and reduce the risks associated with opportunistic, ad hoc screening. Finally, implementation research must play a greater role in informing policy change about targeted LDCT screening programmes.

Performance of the EarlyCDT® Lung test in detection of lung cancer and pulmonary metastases in a high-risk cohort

OBJECTIVES

Early detection of lung cancer is pivotal for an optimal prognosis. CT screening is currently implemented in USA. To decrease the amount of CT scans, the application of a blood-based biomarker as part of screening criteria is desirable.

MATERIALS AND METHODS

The EarlyCDT® Lung test was performed in a high-risk cohort composed 246 patients referred from their GP on suspicion of lung cancer. Blood samples were taken at first visit and patients underwent diagnostic workup on suspicion of lung cancer resulting in either a malignant diagnosis or ruled out cancer. Sensitivity and specificity of the EarlyCDT® Lung were calculated in the cohort and subgroups based on age, smoking history, sex and lung cancer stage.

RESULTS

Overall sensitivity in the cohort was 33 % for lung cancer and 31 % for primary lung cancer and lung metastases combined. Sensitivity in age groups was 11 % (60 years or below), 31 % (61-75 years) and 55 % (>75 years). In patients with at least 10 tobacco pack years, sensitivity was 33 % while the sensitivity in patients with at least 50 tobacco pack years was 44 %. The assay sensitivity in stage I-II lung cancer patients was 21 %, while this was 40 % in stage III-IV lung cancer patients. In a subgroup of patients that met current CT screening criteria (age 55-80 years and minimum 30 tobacco pack years) the sensitivity was 37 %.

CONCLUSION

The rationale of screening for lung cancer is to find patients in an early and resectable stage. However, the EarlyCDT® Lung test performed best in elderly, late stage lung cancer patients with a heavy smoking history. Based on these results, the current study finds insufficient sensitivity of the EarlyCDT® Lung test to be used as part of inclusion criteria in a low-dose CT program for detection of lung cancer.

Characteristics and Outcomes of Lung Cancers Detected on Low-Dose Lung Cancer Screening CT

BACKGROUND

Lung cancer screening (LCS) with low-dose CT (LDCT) was implemented in the United States following the National Lung Screening Trial (NLST). The real-world benefits of implementing LCS are yet to be determined with outcome-oriented data. The study objective is to investigate the characteristics and outcomes of screening-detected lung cancers.

METHODS

This single-institution retrospective study included LCS patients between June 2014 and December 2019. Patient demographics, number of screening rounds, imaging features, clinical workup, disease extent, histopathology, treatment, complications, and mortality outcomes of screening-detected lung cancers were extracted and compared with NLST data.

RESULTS

LCS LDCTs (7,480) were performed on 4,176 patients. The cancer detection rate was 3.8%, higher than reported by NLST (2.4%, P < 0.0001), and cancers were most often found in patients ≥65 years (62%), older than those in NLST (41%, P < 0.0001). The patients' ethnicity was similar to NLST, P = 0.87. Most LCS-detected cancers were early stage I tumors (71% vs. 54% in NLST, P < 0.0001). Two thirds of cancers were detected in the first round of screening (67.1%) and were multifocal lung cancers in 15%. As in NLST, the complication rate after invasive workup or surgery was low (24% vs. 28% in NLST, P = 0.32). Over a median follow-up of 3.3 years, the mortality rate was 0.45%, lower than NLST (1.33%, P < 0.0001).

CONCLUSIONS

LCS implementation achieved a higher cancer detection rate, detection of early-stage cancers, and more multifocal lung cancers compared with the NLST, with low complications and mortality.

IMPACT

The real-world implementation of LCS has been successful for detection of lung cancer with favorable outcomes.

Lung Cancer Screening with Low-Dose CT in Smokers: A Systematic Review and Meta-Analysis

Lung cancer continues to be one of the main causes of cancer death in Europe. Low-dose computed tomography (LDCT) has shown high potential for screening of lung cancer in smokers, most recently in two European trials. The aim of this review was to assess lung cancer screening of smokers by LDCT with respect to clinical effectiveness, radiological procedures, quality of life, and changes in smoking behavior. We searched electronic databases in April 2020 for publications of randomized controlled trials (RCT) reporting on lung cancer and overall mortality, lung cancer morbidity, and harms of LDCT screening. A meta-analysis was performed to estimate effects on mortality. Forty-three publications on 10 RCTs were included. The meta-analysis of eight studies showed a statistically significant relative reduction of lung cancer mortality of 12% in the screening group (risk ratio = 0.88; 95% CI: 0.79-0.97). Between 4% and 24% of screening-LDCT scans were classified as positive, and 84-96% of them turned out to be false positive. The risk of overdiagnosis was estimated between 19% and 69% of diagnosed lung cancers. Lung cancer screening can reduce disease-specific mortality in (former) smokers when stringent requirements and quality standards for performance are met.

Benefits and Harms of Lung Cancer Screening by Chest Computed Tomography: A Systematic Review and Meta-Analysis

PURPOSE

This meta-analysis aims to combine and analyze randomized clinical trials comparing computed tomography lung screening (CTLS) versus either no screening (NS) or chest x-ray (CXR) in subjects with cigarette smoking history, to provide a precise and reliable estimation of the benefits and harms associated with CTLS.

MATERIALS AND METHODS

Data from all published randomized trials comparing CTLS versus either NS or CXR in a highly tobacco-exposed population were collected, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Subgroup analyses by comparator (NS or CXR) were performed. Pooled risk ratio (RR) and relative 95% CIs were calculated for dichotomous outcomes. The certainty of the evidence was assessed using the GRADE approach.

RESULTS

Nine eligible trials (88,497 patients) were included. Pooled analysis showed that CTLS is associated with: a significant reduction of lung cancer-related mortality (overall RR, 0.87; 95% CI, 0.78 to 0.98; NS RR, 0.80; 95% CI, 0.69 to 0.92); a significant increase of early-stage tumors diagnosis (overall RR, 2.84; 95% CI 1.76 to 4.58; NS RR, 3.33; 95% CI, 2.27 to 4.89; CXR RR, 1.52; 95% CI, 1.04 to 2.23); a significant decrease of late-stage tumors diagnosis (overall RR, 0.75; 95% CI, 0.68 to 0.83; NS RR, 0.67; 95% CI, 0.56 to 0.80); a significant increase of resectability rate (NS RR, 2.57; 95% CI, 1.76 to 3.74); a nonsignificant reduction of all-cause mortality (overall RR, 0.99; 95% CI, 0.94 to 1.05); and a significant increase of overdiagnosis rate (NS, 38%; 95% CI, 14 to 63). The analysis of lung cancer-related mortality by sex revealed nonsignificant differences between men and women (P = .21; I-squared = 33.6%).

CONCLUSION

Despite there still being uncertainty about overdiagnosis estimate, this meta-analysis suggested that the CTLS benefits outweigh harms, in subjects with cigarette smoking history, ultimately supporting the systematic implementation of lung cancer screening worldwide.

An x-ray crosstalk correction method using FCNN for a novel energy resolving scheme in spectral CT

Spectral computed tomography has great potential for multi-energy imaging and anti-artifacts. The complete absorption-based energy resolving scheme of x-rays has been used for the integrity of detected information. However, this scheme is limited by the fact that the detector pixel thickness is high and fixed. Here, an energy resolving scheme is proposed using the crosstalk correction method for the incomplete absorption detection of x-rays. A fully connected neural network (FCNN)-based method was used to correct the difference caused by internal x-ray crosstalk of the edge-on detector. The energy and spatial features of the data which is collected in layers were combined to establish the mapping between the ideal data and the data with crosstalk at the pre-processing stage. Thereafter, to reconstruct the stable and highly accurate energy-resolving equations, the layers with low relative energy difference were selected and grouped together to reduce the accumulation difference. The experiment results demonstrate the feasibility of this energy resolving scheme. The differences caused by crosstalk can be suppressed through the proposed FCNN-based method. The resolving accuracy can be further improved by grouping more layers at forward positions in the pixel. Moreover, this improvement can be observed in the reconstructed images with reduced artifacts and improved quality.

Higher prevalence of incidental findings identified upon coronary calcium score assessment in type 2 and type 3 diabetes versus type 1 diabetes

Aim

Noninvasive assessment of infraclinic coronary atherosclerosis by coronary artery calcium score (CAC) measurement leads to the identification of incidental findings. The aim of this study was to determine the prevalence of incidental findings following systematic CAC assessment in diabetic patients with high cardiovascular risk, to identify the determinants, and to assess the midterm consequences of these findings in patient care.

Methods

732 consecutive asymptomatic patients (187 type 1 diabetes (TD1), 482 type 2 diabetes (TD2) and 63 type 3 diabetes (TD3)) aged 60.6±0.7 years who had a CAC assessment by Multiple Detector Computed Tomography between 2015 and 2017 were systematically included. Clinical and biological data were collected from medical electronic files.

Results

117/732 diabetic patients (16.0%) had incidental findings of which 105 (14.3%) were unknown. Incidental findings were more frequent in TD3 (23.8%) and TD2 (17.0%) than in TD1 (10.7%) (p = 0.05). 76 diabetic patients (10.4%) had lung abnormalities, mainly pulmonary nodules (31 patients, 4.2%). The other incidental finding were pericardial (1.5%), vascular (1.2%), thymic (0.7%) and digestive diseases (0.5%). 42.6% of patients with incidental findings had an additional TDM and 56.8% a specialized medical advice. In 10 patients (9.3% of incidental findings), the identification of incidental finding led to a specific treatment of the underlying disease. In multivariate analysis, microalbuminuria, type of diabetes (TD2/TD3 vs TD1) and smoking were significantly associated with incidental findings (p = 0.003; p = 0.026; p = 0.050 respectively).

Conclusions

Incidental findings are not rare in diabetic patients upon CAC assessment. A fraction of them are accessible to specific treatment. These findings raise the question if a systematic low dose chest TDM should be conducted in TD2 or TD3 patients and in any diabetic smokers by enlarging the window used for CAC assessment.

Women screened for breast cancer are dying from lung cancer: An opportunity to improve lung cancer screening in a mammography population

OBJECTIVE

Lung cancer is the leading cancer killer in women, resulting in more deaths than breast, cervical and ovarian cancer combined. Screening for lung cancer has been shown to significantly reduce mortality, with some evidence that women may have a greater benefit. This study demonstrates that a population of women being screened for breast cancer may greatly benefit from screening for lung cancer.

METHODS

Data from 18,040 women who were screened for breast cancer in 2015 at two imaging facilities that also performed lung screening were reviewed. A natural language-processing algorithm followed by a manual chart review identified women eligible for lung cancer screening by U.S. Preventive Services Task Force (USPSTF) criteria. A chart review of these eligible women was performed to determine subsequent enrollment in a lung screening program (2016-2019), current screening eligibility, cancer diagnoses and cancer-related outcomes.

RESULTS

Natural language processing identified 685 women undergoing screening mammography who were also potentially eligible for lung screening based on age and smoking history. Manual chart review confirmed 251 were eligible under USPSTF criteria. By June 2019, 63 (25%) had enrolled in lung screening, of which three were diagnosed with screening-detected lung cancer resulting in zero deaths. Of 188 not screened, seven were diagnosed with lung cancer resulting in five deaths by study end. Four women received a diagnosis of breast cancer with no deaths.

CONCLUSION

Women screened for breast cancer are dying from lung cancer. We must capitalize on reducing barriers to improve screening for lung cancer among high-risk women.

Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges

Randomised clinical trials have shown the efficacy of computed tomography lung cancer screening, initiating discussions on whether and how to implement population‐based screening programs. Due to smoking behaviour being the primary risk‐factor for lung cancer and part of the criteria for determining screening eligibility, lung cancer screening is inherently risk‐based. In fact, the selection of high‐risk individuals has been shown to be essential in implementing lung cancer screening in a cost‐effective manner. Furthermore, studies have shown that further risk‐stratification may improve screening efficiency, allow personalisation of the screening interval and reduce health disparities. However, implementing risk‐based lung cancer screening programs also requires overcoming a number of challenges. There are indications that risk‐based approaches can negatively influence the trade‐off between individual benefits and harms if not applied thoughtfully. Large‐scale implementation of targeted, risk‐based screening programs has been limited thus far. Consequently, questions remain on how to efficiently identify and invite high‐risk individuals from the general population. Finally, while risk‐based approaches may increase screening program efficiency, efficiency should be balanced with the overall impact of the screening program. In this review, we will address the opportunities and challenges in applying risk‐stratification in different aspects of lung cancer screening programs, as well as the balance between screening program efficiency and impact.

Ongoing challenges in implementation of lung cancer screening

Lung cancer is the leading cause of cancer deaths in Europe and around the world. Although available therapies have undergone considerable development in the past decades, the five-year survival rate for lung cancer remains low. This sobering outlook results mainly from the advanced stages of cancer most patients are diagnosed with. As the population at risk is relatively well defined and early stage disease is potentially curable, lung cancer outcomes may be improved by screening. Several studies already show that lung cancer screening (LCS) with low-dose computed tomography (LDCT) reduces lung cancer mortality. However, for a successful implementation of LCS programmes, several challenges have to be overcome: selection of high-risk individuals, standardization of nodule classification and measurement, specific training of radiologists, optimization of screening intervals and screening duration, handling of ancillary findings are some of the major points which should be addressed. Last but not least, the psychological impact of screening on screened individuals and the impact of potential false positive findings should not be neglected. The aim of this review is to discuss the different challenges of implementing LCS programmes and to give some hints on how to overcome them. Finally, we will also discuss the psychological impact of screening on quality of life and the importance of smoking cessation.

Artificial intelligence for detection and characterization of pulmonary nodules in lung cancer CT screening: ready for practice?

Lung cancer computed tomography (CT) screening trials using low-dose CT have repeatedly demonstrated a reduction in the number of lung cancer deaths in the screening group compared to a control group. With various countries currently considering the implementation of lung cancer screening, recurring discussion points are, among others, the potentially high false positive rates, cost-effectiveness, and the availability of radiologists for scan interpretation. Artificial intelligence (AI) has the potential to increase the efficiency of lung cancer screening. We discuss the performance levels of AI algorithms for various tasks related to the interpretation of lung screening CT scans, how they compare to human experts, and how AI and humans may complement each other. We discuss how AI may be used in the lung cancer CT screening workflow according to the current evidence and describe the additional research that will be required before AI can take a more prominent role in the analysis of lung screening CT scans.

The radiologist's role in lung cancer screening

Lung cancer is still the deadliest cancer in men and women worldwide. This high mortality is related to diagnosis in advanced stages, when curative treatment is no longer an option. Large randomized controlled trials have shown that lung cancer screening (LCS) with low-dose computed tomography (CT) can detect lung cancers at earlier stages and reduce lung cancer-specific mortality. The recent publication of the significant reduction of cancer-related mortality by 26% in the Dutch-Belgian NELSON LCS trial has increased the likelihood that implementation of LCS in Europe will move forward. Radiologists are important stakeholders in numerous aspects of the LCS pathway. Their role goes beyond nodule detection and nodule management. Being part of a multidisciplinary team, radiologists are key players in numerous aspects of implementation of a high quality LCS program. In this non-systematic review we discuss the multifaceted role of radiologists in LCS.

Lung cancer screening in Europe: where are we in 2021?

This manuscript reviews the recent evidence obtained in lung cancer screening with low dose spiral CT-scan (LDSCT) and focuses on the issues associated with its implementation in Europe. After a review of the magnitude of the lung cancer toll in lives, disease and Euro’s, the recently released data of the major lung cancer screening trials are reviewed and mirrored with the results of the US National Lung Screening Trial (NLST), comparing their strengths and weaknesses and areas of future research. The specific barriers and hurdles to be addressed for widely implementing this population screening in European countries are discussed, with special emphasis on the issues of inclusion of smokers, smoking cessation interventions, radiation injury and capacity planning. The pros and cons of including current smokers will be addressed together with the issue which is the better smoking cessation intervention. A medical physicist’s view on radiation exposure and quality control will address concerns about radiation induced cancers. The downstream effects of a LDSCT screening program on the capacity of CT-scans, radiologists, thoracic surgeons and radiation oncologists will follow. An estimated roadmap for the future is sketched with the expected role of all key stakeholders. This roadmap reflects the opinion leader’s reflections as expressed in a number of discussions with European health authorities, taking place as part of the recently released European Beating Cancer plan.

Screen-detected solid nodules: from detection of nodule to structured reporting

Lung cancer screening (LCS) is gaining some interest worldwide after positive results from International trials. Unlike other screening practices, LCS is performed by an extremely sensitive test, namely low-dose computed tomography (LDCT) that can detect the smallest nodules in lung parenchyma. Up-to-date detection approaches, such as computer aided detection systems, have been increasingly employed for lung nodule automatic identification and are largely used in most LCS programs as a complementary tool to visual reading. Solid nodules of any size are represented in the vast majority of subjects undergoing LDCT. However, less than 1% of solid nodules will be diagnosed lung cancer. This fact calls for specific characterization of nodules to avoid false positives, overinvestigation, and reduce the risks associated with nodule work up. Recent research has been exploring the potential of artificial intelligence, including deep learning techniques, to enhance the accuracy of both detection and characterisation of lung nodule. Computer aided detection and diagnosis algorithms based on artificial intelligence approaches have demonstrated the ability to accurately detect and characterize parenchymal nodules, reducing the number of false positives, and to outperform some of the currently used risk models for prediction of lung cancer risk, potentially reducing the proportion of surveillance CT scans. These forthcoming approaches will eventually integrate a new reasoning for development of future guidelines, which are expected to evolve into precision and personalized stratification of lung cancer risk stratification by continuous fashion, as opposed to the current format with a limited number of risk classes within fixed thresholds of nodule size. This review aims to detail the standard of reference for optimal management of solid nodules by low-dose computed and its projection into the fine selection of candidates for work up.

Discovering Panel of Autoantibodies for Early Detection of Lung Cancer Based on Focused Protein Array

Substantial studies indicate that autoantibodies to tumor-associated antigens (TAAbs) arise in early stage of lung cancer (LC). However, since single TAAbs as non-invasive biomarkers reveal low diagnostic performances, a panel approach is needed to provide more clues for early detection of LC. In the present research, potential TAAbs were screened in 150 serum samples by focused protein array based on 154 proteins encoded by cancer driver genes. Indirect enzyme-linked immunosorbent assay (ELISA) was used to verify and validate TAAbs in two independent datasets with 1,054 participants (310 in verification cohort, 744 in validation cohort). In both verification and validation cohorts, eight TAAbs were higher in serum of LC patients compared with normal controls. Moreover, diagnostic models were built and evaluated in the training set and the test set of validation cohort by six data mining methods. In contrast to the other five models, the decision tree (DT) model containing seven TAAbs (TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1), built in the training set, yielded the highest diagnostic value with the area under the receiver operating characteristic curve (AUC) of 0.897, the sensitivity of 94.4% and the specificity of 84.9%. The model was further assessed in the test set and exhibited an AUC of 0.838 with the sensitivity of 89.4% and the specificity of 78.2%. Interestingly, the accuracies of this model in both early and advanced stage were close to 90%, much more effective than that of single TAAbs. Protein array based on cancer driver genes is effective in screening and discovering potential TAAbs of LC. The TAAbs panel with TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1 is excellent in early detection of LC, and they might be new target in LC immunotherapy.

Comparative Effectiveness of Lobectomy, Segmentectomy, and Wedge Resection for Pathological Stage I Non-small Cell Lung Cancer in Elderly Patients: A Population-Based Study

Introduction: This study was designed to assess the long-term survival of lobectomy, segmentectomy, and wedge resection for pathological stage I non-small cell lung cancer (NSCLC) in patients over 75 years of age.

Patients and methods: Pathological stage I NSCLC patients aged ≥75 years who underwent lobectomy, segmentectomy, or wedge resection were identified from the Surveillance, Epidemiology, and End Results database. Propensity score–matched and competing risks analyses were conducted. The overall survival (OS) rate and lung cancer–specific survival (LCSS) rate were compared among the three groups based on the pathological stage.

Results: A total of 3,345 patients were included. In the full cohort, the OS rate and LCSS rate of lobectomy were superior to wedge resection, but not to segmentectomy, the OS advantage diminished when patients were over 85 years old or when at least one lymph node was examined during the procedure. Stratified analyses showed that there was no significant difference in OS and LCSS rates among the three surgical procedures for patients with tumors smaller than 1.0 cm. The OS and LCSS of wedge resection, not segmentectomy, were inferior to lobectomy in stage IA2–IB tumors.

Conclusion: Lobectomy should be recognized as the “gold standard” procedure for pathological stage I NSCLC in patients over 75 years of age, and segmentectomy could be considered as an effective alternative. Wedge resection could be considered for patients with compromised cardiopulmonary function or tumors smaller than 1.0 cm, and intraoperative lymph node examination should be conducted.

Microsimulation modeling of extended annual CT screening among lung cancer cases in the National Lung Screening Trial

PURPOSE

To microsimulate the effects of three additional annual CT screening rounds on lung cancer (LC) survival in the National Lung Screening Trial (NLST).

METHODS

We used multiple imputation to model the effect of additional screening in the full NLST cohort on the time to LC diagnosis and on LC death in those participants who were diagnosed with LC by the end of NLST. Nodule growth models were derived from a Dutch in-vivo study. Microsimulations were repeated 500 times. The method was validated by simulating three rounds of CT screening in the original chest radiography (CXR) cohort. The times up to which the simulations remained within the 95 % confidence bands of the CT cohort's original results were used to estimate the validity of the results in the CT cohort with three additional simulated screening rounds.

RESULTS

Validation of the simulation approach on the CXR cohort resulted in a LC mortality reduction which remained well within the 95 % confidence intervals of the original CT cohort up to 6.5 years after the start of simulations. Simulating additional CT screening in the CT cohort led to LCs being diagnosed earlier than originally, resulting in a relative risk reduction in LC mortality of 11 % (95 % confidence bands, 7 %-14 %) at 6.5 years. This is equivalent to preventing 71 % (48 %-94 %) more LC deaths than the original CT cohort achieved in comparison to the original CXR cohort.

CONCLUSION

Three additional annual CT screening rounds in the NLST may have led to substantial further LC mortality reduction.

Artificial intelligence-based vessel suppression for detection of sub-solid nodules in lung cancer screening computed tomography

Background

Lung cancer screening (LCS) with low-dose computed tomography (LDCT) helps early lung cancer detection, commonly presenting as small pulmonary nodules. Artificial intelligence (AI)-based vessel suppression (AI-VS) and automatic detection (AI-AD) algorithm can improve detection of subsolid nodules (SSNs) on LDCT. We assessed the impact of AI-VS and AI-AD in detection and classification of SSNs [ground-glass nodules (GGNs) and part-solid nodules (PSNs)], on LDCT performed for LCS.

Methods

Following regulatory approval, 123 LDCT examinations with sub-solid pulmonary nodules (average diameter ≥6 mm) were processed to generate three image series for each examination-unprocessed, AI-VS, and AI-AD series with annotated lung nodules. Two thoracic radiologists in consensus formed the standard of reference (SOR) for this study. Two other thoracic radiologists (R1 and R2; 5 and 10 years of experience in thoracic CT image interpretation) independently assessed the unprocessed images alone, then together with AI-VS series, and finally with AI-AD for detecting all ≥6 mm GGN and PSN. We performed receiver operator characteristics (ROC) and Cohen's Kappa analyses for statistical analyses.

Results

On unprocessed images, R1 and R2 detected 232/310 nodules (R1: 114 GGN, 118 PSN) and 255/310 nodules (R2: 122 GGN, 133 PSN), respectively (P>0.05). On AI-VS images, they detected 249/310 nodules (119 GGN, 130 PSN) and 277/310 nodules (128 GGN, 149 PSN), respectively (P≥0.12). When compared to the SOR, accuracy (AUC) for detection of PSN on the AI-VS images (AUC 0.80-0.81) was greater than on the unprocessed images (AUC 0.70-0.76). AI-VS images enabled detection of solid components in five nodules deemed as GGN on the unprocessed images. Accuracy of AI-AD was lower than both the radiologists (AUC 0.60-0.72).

Conclusions

AI-VS improved the detection and classification of SSN into GGN and PSN on LDCT of the chest for the two radiologist (R1 and R2) readers.

Lung Cancer Screening: Evidence, Risks, and Opportunities for Implementation

BACKGROUND

 Lung cancer is the most common cause of cancer death worldwide. Several trials with different screening approaches have recognized the role of lung cancer screening with low-dose CT for reducing lung cancer mortality. The efficacy of lung cancer screening depends on many factors and implementation is still pending in most European countries.

METHODS

 This review aims to portray current evidence on lung cancer screening with a focus on the potential for opportunities for implementation strategies. Pillars of lung cancer screening practice will be discussed according to the most updated literature (PubMed search until November 16, 2020).

RESULTS AND CONCLUSION

 The NELSON trial showed reduction of lung cancer mortality, thus confirming previous results of independent European studies, notably by volume of lung nodules. Heterogeneity in patient recruitment could influence screening efficacy, hence the importance of risk models and community-based screening. Recruitment strategies develop and adapt continuously to address the specific needs of the heterogeneous population of potential participants, the most updated evidence comes from the UK. The future of lung cancer screening is a tailored approach with personalized continuous stratification of risk, aimed at reducing costs and risks.

KEY POINTS

  · Secondary prevention of lung cancer by low-dose computed tomography showed a reduction of lung cancer mortality.. · Semi-automated volume measurement and use of volume doubling time should be the reference method for optimization of risks, namely controlling measurement variability and the false-positive rate.. · A conservative approach with surveillance of subsolid nodules can be one of the strategies to reduce the risk of overdiagnosis and overtreatment.. · The goal of a tailored approach with personalized risk stratification aims to reduce costs and risks. A longer interval between rounds is one option for participants at lower risk..

CITATION FORMAT

· Tringali G, Milanese G, Ledda RE et al. Lung Cancer Screening: Evidence, Risks, and Opportunities for Implementation. Fortschr Röntgenstr 2021; 193: 1153 - 1161.

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

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

Validation of multivariable lung cancer risk prediction models for the personalized assignment of optimal screening frequency: a retrospective analysis of data from the German Lung Cancer Screening Intervention Trial (LUSI)

BACKGROUND

Current guidelines for lung cancer screening via low-dose computed tomography recommend annual screening for all candidates meeting basic eligibility criteria. However, lung cancer risk of eligible screening participants can vary widely, and further risk stratification could be used to individually optimize screening intervals in view of expected benefits, possible harms and financial costs. To this effect, models have been developed in the US National Lung Screening Trial based on self-reported lung cancer risk factors and imaging data. We evaluated these models using data from an independent screening trial in Germany.

METHODS

We examined the Polynomial model by Schreuder et al., the Lung Cancer Risk Assessment Tool extended by CT characteristics (LCRAT + CT) by Robbins et al., and a criterion of presence vs. absence of pulmonary nodules ≥4 mm (Patz et al.), applied to sub-sets of screening participants according to eligibility criteria. Discrimination was evaluated via the receiver operating characteristic curve. Delayed diagnoses and false positive results were calculated at various thresholds of predicted risk. Model calibration was assessed by comparing mean predicted risk versus observed incidence.

RESULTS

One thousand five hundred and six participants were eligible for the validation of the LCRAT + CT model, and 1,889 for the validation of the Polynomial model and Patz criterion, yielding areas under the receiver operating characteristic curve of 0.73 (95% CI: 0.63, 0.82), 0.75 (0.67, 0.83), and 0.56 (0.53, 0.72) respectively. Skipping 50% annual screenings (participants within the 5 lowest risk deciles by LCRAT + CT in any round or by the Polynomial model; baseline screening round), would have avoided 75% (21.9%, 98.7%) and 40% (21.8%, 61.1%) false positive screen tests and delayed 10% (1.8%, 33.1%) or no (0%, 32.1%) diagnoses, respectively. Using the Patz criterion, referring 63.2% (61.0% to 65.4%) of participants to biennial screening would have avoided 4% (0.2% to 22.3%) of false positive screen tests but delayed 55% (24.6% to 81.9%) diagnoses.

CONCLUSIONS

In this German trial, the LCRAT + CT and Polynomial models showed useful discrimination of screening participants for one-year lung cancer risk following CT examination. Our results illustrate the remaining heterogeneity in risk within screening-eligible subjects and the trade-off between a low-frequency screening approach and delayed detection.

Intergroupe francophone de cancérologie thoracique, Société de pneumologie de langue française, and Société d'imagerie thoracique statement paper on lung cancer screening

Following the American National Lung Screening Trial results in 2011 a consortium of French experts met to edit a statement. Recent results of other randomized trials gave the opportunity for our group to meet again in order to edit updated guidelines. After literature review, we provide here a new update on lung cancer screening in France. Notably, in accordance with all international guidelines, the experts renew their recommendation in favor of individual screening for lung cancer in France as per the conditions laid out in this document. In addition, the experts recommend the very rapid organization and funding of prospective studies, which, if conclusive, will enable the deployment of lung cancer screening organized at the national level.

[Scientific assessment and regulatory approval of radiological screening examinations in Germany]

BACKGROUND

Radiologic imaging technologies like computed tomography (CT) have the potential to screen for various diseases. The potential benefits of screening are always associated with risks, particularly from the application of ionizing radiation.

MATERIALS AND METHODS

The International Basic Safety Standards as well as the Council Directive 2013/59/Euratom have set guidelines for the application of ionizing radiation in early detection which were transposed into the German Radiation Protection Law. Accordingly, the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) approves screening examinations on a generic level, based on a scientific report provided by the German Federal Office for Radiation Protection (BfS), and defines in a federal statutory ordinance which type of screening is permissible for detecting a disease for a particular group of persons and under which conditions.

RESULTS

With exception of the mammography screening programme, no radiological examination for the early detection of disease has been approved in Germany to date. However, such screenings are currently being offered in Germany. The BfS is currently conducting a scientific evaluation for lung cancer screening with low-dose CT.

CONCLUSIONS

Screening examinations with radiological imaging can only be approved when studies with the highest level of evidence have demonstrated that the benefits outweigh the risks. To translate this favourable benefit-risk balance into general health care, strict requirements for the entire screening process including quality assurance must be defined.

Implementation of lung cancer screening: what are the main issues?

Two large-scale RCTs have shown computed tomography (CT) lung cancer screening to be efficacious in reducing lung cancer mortality (8–24% in men, 26–59% in women). However, lung cancer screening implicitly means personalised and risk-based approaches. Health care systems’ implementation of personalised screening and prevention is still sparse, and likely to be of variable quality, because of important remaining uncertainties, which have been incompletely addressed or not at all so far. Further optimisation of lung cancer screening programs is expected to reduce harms and maintain or enhance benefit for eligible European citizens, whilst significantly reducing health care costs. Some main uncertainties (e.g., Risk-based eligibility, Risk-based screening intervals, Volume CT screening, Smoking Cessation, Gender and Sex differences, Cost-Effectiveness) are discussed in this review. 4-IN-THE-LUNG-RUN (acronym for: Towards INdividually tailored INvitations, screening INtervals and INtegrated co-morbidity reducing strategies in lung cancer screening) is the first multi-centred implementation trial on volume CT lung cancer screening amongst 24,000 males and females, at high risk for developing lung cancer, across five European countries, started in January 2020. Through providing answers to the remaining questions with this trial, many EU citizens will swiftly benefit from this high-quality screening technology, others will face less harms than previously anticipated, and health care costs will be substantially reduced. Implementing a new cancer screening programme is a major task, with many stakeholders and many possible facilitators but also barriers and obstacle.

Targeting lung cancer screening to individuals at greatest risk: the role of genetic factors

Lung cancer (LC) is the most common global cancer. An individual’s risk of developing LC is mediated by an array of factors, including family history of the disease. Considerable research into genetic risk factors for LC has taken place in recent years, with both low-penetrance and high-penetrance variants implicated in increasing or decreasing a person’s risk of the disease. LC is the leading cause of cancer death worldwide; poor survival is driven by late onset of non-specific symptoms, resulting in late-stage diagnoses. Evidence for the efficacy of screening in detecting cancer earlier, thereby reducing lung-cancer specific mortality, is now well established. To ensure the cost-effectiveness of a screening programme and to limit the potential harms to participants, a risk threshold for screening eligibility is required. Risk prediction models (RPMs), which provide an individual’s personal risk of LC over a particular period based on a large number of risk factors, may improve the selection of high-risk individuals for LC screening when compared with generalised eligibility criteria that only consider smoking history and age. No currently used RPM integrates genetic risk factors into its calculation of risk. This review provides an overview of the evidence for LC screening, screening related harms and the use of RPMs in screening cohort selection. It gives a synopsis of the known genetic risk factors for lung cancer and discusses the evidence for including them in RPMs, focusing in particular on the use of polygenic risk scores to increase the accuracy of targeted lung cancer screening.

Lung-RADS Version 1.1: Challenges and a Look Ahead, From the AJR Special Series on Radiology Reporting and Data Systems

In 2014, the American College of Radiology (ACR) created Lung-RADS 1.0. The system was updated to Lung-RADS 1.1 in 2019, and further updates are anticipated as additional data become available. Lung-RADS provides a common lexicon and standardized nodule follow-up management paradigm for use when reporting lung cancer screening (LCS) low-dose CT (LDCT) chest examinations and serves as a quality assurance and outcome monitoring tool. The use of Lung-RADS is intended to improve LCS performance and lead to better patient outcomes. To date, the ACR's Lung Cancer Screening Registry is the only LCS registry approved by the Centers for Medicare & Medicaid Services and requires the use of Lung-RADS categories for reimbursement. Numerous challenges have emerged regarding the use of Lung-RADS in clinical practice, including the timing of return to LCS after planned follow-up diagnostic evaluation; potential substitution of interval diagnostic CT for future LDCT; role of volumetric analysis in assessing nodule size; assessment of nodule growth; assessment of cavitary, subpleural, and category 4X nodules; and variability in reporting of the S modifier. This article highlights the major updates between versions 1.0 and 1.1 of Lung-RADS, describes the system's ongoing challenges, and summarizes current evidence and recommendations.

Duration of lead time in screening for lung cancer

BACKGROUND

Screening for lung cancer has used chest radiography (CR), low dose computed tomography (LDCT) and sputum cytology (SC). Estimates of the lead time (LT), i.e., the time interval from detection of lung cancer by screening to the development of symptoms, have been derived from longitudinal studies of populations at risk, tumor doubling time (DT), the ratio between its prevalence at the first round of screening and its annual incidence during follow-up, and by probability modeling derived from the results of screening trials.

OBJECTIVE

To review and update the estimates of LT of lung cancer.

METHODS

A non-systematic search of the literature for estimates of LT and screening trials. Search of the reference sections of the retrieved papers for additional relevant studies. Calculation of LTs derived from these studies.

RESULTS

LT since detection by CR was 0.8-1.1 years if derived from longitudinal studies; 0.6-2.1 years if derived from prevalence / incidence ratios; 0.2 years if derived from the average tumor DT; and 0.2-1.0 if derived from probability modeling. LT since detection by LDCT was 1.1-3.5 if derived from prevalence / incidence ratios; 3.9 if derived from DT; and 0.9 if derived from probability modeling. LT since detection of squamous cell cancer by SC in persons with normal CR was 1.3-1.5 if derived from prevalence/incidence ratios; and 2.1 years if derived from the DT of squamous cell cancer.

CONCLUSIONS

Most estimates of the LT yield values of 0.2-1.5 years for detection by CR; of 0.9-3.5 years for detection by LDCT; and about 2 years or less for detection of squamous cell cancer by SC in persons with normal CR. The heterogeneity of the screening trials and methods of derivation may account for the variability of LT estimates.

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

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

Can autoantibody tests enhance lung cancer screening?-an evaluation of EarlyCDT®-Lung in context of the German Lung Cancer Screening Intervention Trial (LUSI)

Background

Tumor-associated autoantibodies are considered promising markers for early lung cancer detection; so far, however, their capacity to detect cancer has been tested mostly in a clinical context, but not in population screening settings. This study evaluates the early detection accuracy, in terms of sensitivity and specificity, of EarlyCDT^®-Lung-a test panel of seven tumor-associated autoantibodies optimized for lung cancer detection-using blood samples originally collected as part of the German Lung Cancer Screening Intervention Trial.

Methods

The EarlyCDT^®-Lung test was performed for all participants with lung cancer detected via low-dose computed tomography and with available blood samples taken at detection, and for 180 retrospectively selected cancer-free participants at the end of follow-up: 90 randomly selected from among all cancer-free participants (baseline controls) and 90 randomly selected from among cancer-free participants with suspicious imaging findings (suspicious nodules controls). Sensitivity and specificity of lung cancer detection were estimated in the case group and the two control groups, respectively.

Results

In the case group, the test panel showed a sensitivity of only 13.0% (95% CI: 4.9-26.3%). Specificity was estimated at 88.9% (95% CI: 80.5-94.5%) in the baseline control group, and 91.1% (95% CI: 83.2-96.1%) among controls presenting CT-detected nodules.

Conclusions

The test panel showed insufficient sensitivity for detecting lung cancer at an equally early stage as with low-dose computed tomography screening.

Earlier diagnosis of lung cancer in a randomised trial of an autoantibody blood test followed by imaging

The EarlyCDT-Lung test is a high-specificity blood-based autoantibody biomarker that could contribute to predicting lung cancer risk. We report on the results of a phase IV biomarker evaluation of whether using the EarlyCDT-Lung test and any subsequent computed tomography (CT) scanning to identify those at high risk of lung cancer reduces the incidence of patients with stage III/IV/unspecified lung cancer at diagnosis compared with the standard clinical practice at the time the study began.The Early Diagnosis of Lung Cancer Scotland (ECLS) trial was a randomised controlled trial of 12 208 participants at risk of developing lung cancer in Scotland in the UK. The intervention arm received the EarlyCDT-Lung test and, if test-positive, low-dose CT scanning 6-monthly for up to 2 years. EarlyCDT-Lung test-negative and control arm participants received standard clinical care. Outcomes were assessed at 2 years post-randomisation using validated data on cancer occurrence, cancer staging, mortality and comorbidities.At 2 years, 127 lung cancers were detected in the study population (1.0%). In the intervention arm, 33 out of 56 (58.9%) lung cancers were diagnosed at stage III/IV compared with 52 out of 71 (73.2%) in the control arm. The hazard ratio for stage III/IV presentation was 0.64 (95% CI 0.41-0.99). There were nonsignificant differences in lung cancer and all-cause mortality after 2 years.ECLS compared EarlyCDT-Lung plus CT screening to standard clinical care (symptomatic presentation) and was not designed to assess the incremental contribution of the EarlyCDT-Lung test. The observation of a stage shift towards earlier-stage lung cancer diagnosis merits further investigations to evaluate whether the EarlyCDT-Lung test adds anything to the emerging standard of low-dose CT.

The challenges of implementing low-dose computed tomography for lung cancer screening in low- and middle-income countries

Lung cancer accounts for an alarming human and economic burden in low- and middle-income countries (LMICs). Recent landmark trials from high-income countries (HICs) by demonstrating that low-dose computed tomography (LDCT) screening effectively reduces lung cancer mortality have engendered enthusiasm for this approach. Here we examine the effectiveness and affordability of LDCT screening from the viewpoint of LMICs. We consider resource-restricted perspectives and discuss implementation challenges and strategies to enhance the feasibility and cost-effectiveness of LDCT screening in LMICs.

Artificial Intelligence Tools for Refining Lung Cancer Screening

Nearly one-quarter of all cancer deaths worldwide are due to lung cancer, making this disease the leading cause of cancer death among both men and women. The most important determinant of survival in lung cancer is the disease stage at diagnosis, thus developing an effective screening method for early diagnosis has been a long-term goal in lung cancer care. In the last decade, and based on the results of large clinical trials, lung cancer screening programs using low-dose computer tomography (LDCT) in high-risk individuals have been implemented in some clinical settings, however, this method has various limitations, especially a high false-positive rate which eventually results in a number of unnecessary diagnostic and therapeutic interventions among the screened subjects. By using complex algorithms and software, artificial intelligence (AI) is capable to emulate human cognition in the analysis, interpretation, and comprehension of complicated data and currently, it is being successfully applied in various healthcare settings. Taking advantage of the ability of AI to quantify information from images, and its superior capability in recognizing complex patterns in images compared to humans, AI has the potential to aid clinicians in the interpretation of LDCT images obtained in the setting of lung cancer screening. In the last decade, several AI models aimed to improve lung cancer detection have been reported. Some algorithms performed equal or even outperformed experienced radiologists in distinguishing benign from malign lung nodules and some of those models improved diagnostic accuracy and decreased the false-positive rate. Here, we discuss recent publications in which AI algorithms are utilized to assess chest computer tomography (CT) scans imaging obtaining in the setting of lung cancer screening.

Lung Cancer Screening by Low-Dose Computed Tomography: Part 2 - Key Elements for Programmatic Implementation of Lung Cancer Screening

PURPOSE

 For screening with low-dose CT (LDCT) to be effective, the benefits must outweigh the potential risks. In large lung cancer screening studies, a mortality reduction of approx. 20 % has been reported, which requires several organizational elements to be achieved in practice.

MATERIALS AND METHODS

 The elements to be set up are an effective invitation strategy, uniform and quality-assured assessment criteria, and computer-assisted evaluation tools resulting in a nodule management algorithm to assign each nodule the needed workup intensity. For patients with confirmed lung cancer, immediate counseling and guideline-compliant treatment in tightly integrated regional expert centers with expert skills are required. First, pulmonology contacts as well as CT facilities should be available in the participant's neighborhood. IT infrastructure, linkage to clinical cancer registries, quality management as well as epidemiologic surveillance are also required.

RESULTS

 An effective organization of screening will result in an articulated structure of both widely distributed pulmonology offices as the participants' primary contacts and CT facilities as well as central expert facilities for supervision of screening activities, individual clarification of suspicious findings, and treatment of proven cancer.

CONCLUSION

 In order to ensure that the benefits of screening more than outweigh the potential harms and that it will be accepted by the public, a tightly organized structure is needed to ensure wide availability of pulmonologists as first contacts and CT facilities with expert skills and high-level equipment concentrated in central facilities.

KEY POINTS

  · For lung cancer screening, elements must function optimally and be tightly organized.. · Lung cancer screening requires a network of expert centers and collaborating facilities.. · IT infrastructure, QM, epidemiological surveillance, and linkage to cancer registries are essential..

CITATION FORMAT

· Delorme S, Kaaks R: Lung Cancer Screening by Low-Dose Computed Tomography: Part 2 - Key Elements for Programmatic Implementation of Lung Cancer Screening. Fortschr Röntgenstr 2021; 193: 644 - 651.

Lung Cancer Screening by Low-Dose Computed Tomography - Part 1: Expected Benefits, Possible Harms, and Criteria for Eligibility and Population Targeting

BACKGROUND

 Trials in the USA and Europe have convincingly demonstrated the efficacy of screening by low-dose computed tomography (LDCT) as a means to lower lung cancer mortality, but also document potential harms related to radiation, psychosocial stress, and invasive examinations triggered by false-positive screening tests and overdiagnosis. To ensure that benefits (lung cancer deaths averted; life years gained) outweigh the risk of harm, lung cancer screening should be targeted exclusively to individuals who have an elevated risk of lung cancer, plus sufficient residual life expectancy.

METHODS AND CONCLUSIONS

 Overall, randomized screening trials show an approximate 20 % reduction in lung cancer mortality by LDCT screening. In view of declining residual life expectancy, especially among continuing long-term smokers, risk of being over-diagnosed is likely to increase rapidly above the age of 75. In contrast, before age 50, the incidence of LC may be generally too low for screening to provide a positive balance of benefits to harms and financial costs. Concise criteria as used in the NLST or NELSON trials may provide a basic guideline for screening eligibility. An alternative would be the use of risk prediction models based on smoking history, sex, and age as a continuous risk factor. Compared to concise criteria, such models have been found to identify a 10 % to 20 % larger number of LC patients for an equivalent number of individuals to be screened, and additionally may help provide security that screening participants will all have a high-enough LC risk to balance out harm potentially caused by radiation or false-positive screening tests.

KEY POINTS

  · LDCT screening can significantly reduce lung cancer mortality. · Screening until the age of 80 was shown to be efficient in terms of cancer deaths averted; in terms of LYG relative to overdiagnosis, stopping at a younger age (e. g. 75) may have greater efficiency. · Risk models may improve the overall net benefit of lung cancer screening.

CITATION FORMAT

· Kaaks R, Delorme S. Lung Cancer Screening by Low-Dose Computed Tomography - Part 1: Expected Benefits, Possible Harms, and Criteria for Eligibility and Population Targeting. Fortschr Röntgenstr 2021; 193: 527 - 536.

The mechanism of m6A methyltransferase METTL3-mediated autophagy in reversing gefitinib resistance in NSCLC cells by β-elemene

N⁶-methyladenosine (m⁶A) modification can alter gene expression by regulating RNA splicing, stability, translocation, and translation. Emerging evidence shows that m⁶A modification plays an important role in cancer development and progression, including cell proliferation, migration and invasion, cell apoptosis, autophagy, and drug resistance. Until now, the role of m⁶A modification mediated autophagy in cancer drug resistance is still unclear. In this study, we found that m⁶A methyltransferase METTL3-mediated autophagy played an important role in reversing gefitinib resistance by β-elemene in non-small cell lung cancer (NSCLC) cells. Mechanistically, in vitro and in vivo studies indicated that β-elemene could reverse gefitinib resistance in NSCLC cells by inhibiting cell autophagy process in a manner of chloroquine. β-elemene inhibited the autophagy flux by preventing autophagic lysosome acidification, resulting in increasing expression of SQSTM1 and LC3B-II. Moreover, both β-elemene and gefitinib decreased the level of m⁶A methylation of gefitinib resistance cells. METTL3 was higher expressed in lung adenocarcinoma tissues than that of paired normal tissues, and was involved in the gefitinib resistance of NSCLC cells. Furthermore, METTL3 positively regulated autophagy by increasing the critical genes of autophagy pathway such as ATG5 and ATG7. In conclusion, our study unveiled the mechanism of METTL3-mediated autophagy in reversing gefitinib resistance of NSCLC cells by β-elemene, which shed light on providing potential molecular-therapy target and clinical-treatment method in NSCLC patients with gefitinib resistance.

Evaluation of a Low-Dose Computed Tomography Lung Cancer Screening Program in Henan, China

IMPORTANCE

Lung cancer screening has been widely implemented in Europe and the US. However, there is little evidence on participation and diagnostic yields in population-based lung cancer screening in China.

OBJECTIVE

To assess the participation rate and detection rate of lung cancer in a population-based screening program and the factors associated with participation.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the Cancer Screening Program in Urban China from October 2013 to October 2019, with follow-up until March 10, 2020. The program is conducted at centers in 8 cities in Henan Province, China. Eligible participants were aged 40 to 74 and were evaluated for a high risk for lung cancer using an established risk score system.

MAIN OUTCOMES AND MEASURES

Overall and group-specific participation rates by common factors, such as age, sex, and educational level, were calculated. Differences in participation rates between those groups were compared. The diagnostic yield of both screening and nonscreening groups was calculated.

RESULTS

The study recruited 282 377 eligible participants and included 55 428 with high risk for lung cancer; the mean (SD) age was 55.3 (8.1) years, and 34 966 participants (63.1%) were men. A total of 22 260 participants underwent LDCT (participation rate, 40.16%; 95% CI, 39.82%-40.50%). The multivariable logistic regression model showed that female sex (odds ratio [OR], 1.64; 95% CI, 1.52-1.78), former smoking (OR, 1.26; 95% CI, 1.13-1.41), lack of physical activity (OR, 1.19; 95% CI, 1.14-1.24), family history of lung cancer (OR, 1.73; 95% CI, 1.66-1.79), and 7 other factors were associated with increased participation of LDCT screening. Overall, at 6-year follow-up, 78 participants in the screening group (0.35%; 95% CI, 0.29%-0.42%) and 125 in the nonscreening group (0.38%; 95% CI, 0.33%-0.44%) had lung cancer detected, which resulted in an odds ratio of 0.93 (95% CI, 0.70-1.23; P = .61).

CONCLUSIONS AND RELEVANCE

The low participations rate in the program studied suggests that an improved strategy is needed. These findings may provide useful information for designing effective population-based lung cancer screening strategies in the future.