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

Computer-aided diagnosis system versus conventional reading system in low-dose (< 2 mSv) computed tomography: comparative study for patients at risk of lung cancer

BACKGROUND

Computer-aided diagnosis in low-dose (≤ 3 mSv) computed tomography (CT) is a potential screening tool for lung nodules, with quality interpretation and less inter-observer variability among readers. Therefore, we aimed to determine the screening potential of CT using a radiation dose that does not exceed 2 mSv.

OBJECTIVE

We aimed to compare the diagnostic parameters of low-dose (< 2 mSv) CT interpretation results using a computer-aided diagnosis system for lung cancer screening with those of a conventional reading system used by radiologists.

DESIGN AND SETTING

We conducted a comparative study of chest CT images for lung cancer screening at three private institutions.

METHODS

A database of low-dose (< 2 mSv) chest CT images of patients at risk of lung cancer was viewed with the conventional reading system (301 patients and 226 nodules) or computer-aided diagnosis system without any subsequent radiologist review (944 patients and 1,048 nodules).

RESULTS

The numbers of detected and solid nodules per patient (both P < 0.0001) were higher using the computer-aided diagnosis system than those using the conventional reading system. The nodule size was reported as the maximum size in any plane in the computer-aided diagnosis system. Higher numbers of patients (102 [11%] versus 20 [7%], P = 0.0345) and nodules (154 [15%] versus 17 [8%], P = 0.0035) were diagnosed with cancer using the computer-aided diagnosis system.

CONCLUSIONS

The computer-aided diagnosis system facilitates the diagnosis of cancerous nodules, especially solid nodules, in low-dose (< 2 mSv) CT among patients at risk for lung cancer.

A modeling analysis to compare eligibility strategies for lung cancer screening in Brazil

BACKGROUND

Country-specific evidence is needed to guide decisions regarding whether and how to implement lung cancer screening in different settings. For this study, we estimated the potential numbers of individuals screened and lung cancer deaths prevented in Brazil after applying different strategies to define screening eligibility.

METHODS

We applied the Lung Cancer Death Risk Assessment Tool (LCDRAT) to survey data on current and former smokers (ever-smokers) in 15 Brazilian state capital cities that comprise 18% of the Brazilian population. We evaluated three strategies to define eligibility for screening: (1) pack-years and cessation time (≥30 pack-years and <15 years since cessation); (2) the LCDRAT risk model with a fixed risk threshold; and (3) LCDRAT with age-specific risk thresholds.

FINDINGS

Among 2.3 million Brazilian ever-smokers aged 55-79 years, 21,459 (95%CI 20,532-22,387) lung cancer deaths were predicted over 5 years without screening. Applying the fixed risk-based eligibility definition would prevent more lung cancer deaths than the pack-years definition [2,939 (95%CI 2751-3127) vs. 2,500 (95%CI 2318-2681) lung cancer deaths], and with higher screening efficiency [NNS=177 (95%CI 170-183) vs. 205 (95%CI 194-216)], but would tend to screen older individuals [mean age 67.8 (95%CI 67.5-68.2) vs. 63.4 (95%CI 63.0-63.9) years]. Applying age-specific risk thresholds would allow younger ever-smokers to be screened, although these individuals would be at lower risk. The age-specific thresholds strategy would avert three-fifths (60.1%) of preventable lung cancer deaths [N = 2629 (95%CI 2448-2810)] by screening 21.9% of ever-smokers.

INTERPRETATION

The definition of eligibility impacts the efficiency of lung cancer screening and the mean age of the eligible population. As implementation of lung screening proceeds in different countries, our analytical framework can be used to guide similar analyses in other contexts. Due to limitations of our models, more research would be needed.

Results of the cancer screening feasibility study in China: a multicentered randomized controlled trial of lung and colorectal cancer screening

Background

To provide an understanding of important aspects of the participant recruitment and data collection, become aware of any potential problems, and obtain necessary information in order to design a large-scale randomized controlled trial (RCT) for lung cancer and colorectal cancer (CRC) screening in China.

Methods

This feasibility study was a multicentered, open-label, pilot randomized trial. A total of 2696 participants who were at high risk of lung cancer were recruited from three screening centers and randomly allocated to arm 1 (n = 894), annual low-dose computed tomography (LDCT) plus a baseline colonoscopy; arm 2 (n = 902), biennial LDCT plus annual fecal immunochemical test (FIT) with OC-Sensor (OC-FIT); and arm 3 (n = 900), annual Insure-FIT plus Septin 9 blood test. Information on randomization, compliance, positivity rate, cancer case detection, and contamination with screening for lung cancer and CRC were collected.

Results

Participant characteristics were similar across study arms. The compliance rate of annual LDCT screening in arm 1 was 86.4% (95% CI: 83.9%, 88.5%) at baseline (T0), and 69.0% (95% CI: 65.8%, 72.0%) and 70.7% (95% CI: 67.6%, 73.7%) at the following two rounds (T1 and T2). The compliance rates of biennial LDCT screening in arm 2 were similar to those in arm 1 in the corresponding rounds. The compliance rate was 55.5% (95% CI: 52.2%, 58.8%) for colonoscopy in arm 1, while the compliance rates of OC-FIT, Insure-FIT, and the Septin 9 test in arms 2 and 3 were all approximately 90% at T0, decreasing to 65%-80% at T1 and T2. The positivity rate, cancer case detection rate, and contamination rate of screening for lung cancer and CRC were also reported.

Conclusion

In this pilot study, the feasibility of an RCT in China of lung cancer and CRC screening was demonstrated.

Lung Cancer Screening Knowledge Among Internal Medicine Residents in a University Program

Lung cancer remains the main cause of cancer-related death. Even though several societies recommend that certain populations may benefit from lung cancer screening with low-dose computed tomography (LDCT), its nationwide adoption has been slow. Practices in primary care are closely linked to residency training. Recognizing gaps in knowledge during training may translate into increased utilization of life-saving measures. Sixty internal medicine residents training at a university-based program were presented with an anonymous online-based survey designed to measure their knowledge about lung cancer screening. In the second phase, residents were presented with an infographic containing the answers to the initial survey. They were surveyed again 30 days after this intervention. The average correct response rate among all years was 42%. PGY-1 residents performed better compared with PGY-2 and PGY-3 residents (p = 0.015). Ninety-two percent of residents did not think screening improved all-cause mortality. Less than half thought screening had a lung cancer-specific mortality benefit. Fifty-three percent rated their self-perceived knowledge above 50%. There was no difference in knowledge after the intervention. Specific populations may benefit from LDCT screening. Even if these benefits do not directly translate to population settings, the burden and mortality of lung cancer calls for urgent measures to attempt an earlier diagnosis. Internal medicine residents in this program may have several concerns about lung cancer screening including coverage, benefit, and false positive rate. Educational methods such as infographics may not be effective in improving knowledge among residents. Lung cancer screening should be a priority in medical education, especially in states with high smoking rates and lung cancer mortality.

Improved outcomes and staging in non-small-cell lung cancer guided by a molecular assay

There remains a critical need for improved staging of non-small-cell lung cancer, as recurrence and mortality due to undetectable metastases at the time of surgery remain high even after complete resection of tumors currently categorized as 'early stage.' A 14-gene quantitative PCR-based expression profile has been extensively validated to better identify patients at high-risk of 5-year mortality after surgical resection than conventional staging - mortality that almost always results from previously undetectable metastases. Furthermore, prospective studies now suggest a predictive benefit in disease-free survival when the assay is used to guide adjuvant chemotherapy decisions in early-stage non-small-cell lung cancer patients.

Outcomes of Positive and Suspicious Findings in Clinical CT Lung Cancer Screening and the Road Ahead

Rationale

Future optimization of computed tomography (CT) lung cancer screening (CTLS) algorithms will depend on clinical outcomes data.

Objectives

To report the outcomes of positive and suspicious findings in a clinical CTLS program.

Methods

We retrospectively reviewed results for patients from our institution undergoing lung cancer screening from January 2012 through December 2018, with follow-up through December 2019. All exams were retrospectively rescored using Lung-RADS v1.1 (LR). Metrics assessed included positive, probably benign, and suspicious exam rates, frequency/nature of care escalation, and lung cancer detection rates after a positive, probably benign, and suspicious exam result and overall. We calculated time required to resolve suspicious exams as malignant or benign. Results were broken down by subcategories, reason for positive/suspicious designation, and screening round.

Results

During the study period 4,301 individuals underwent a total of 10,897 exams. The number of positive (13.9%), suspicious (5.5%), and significant incidental (6.4%) findings was significantly higher at baseline screening. Cancer detection and false-positive rates were 2.0% and 12.3% at baseline versus 1.3% and 5.1% across subsequent screening rounds, respectively. Baseline solid nodule(s) 6 to <8 mm were the only probably benign findings resulting in lung cancer detection within 12 months. New solid nodules 6 to <8 mm were the only LR category 4A (LR4A) findings falling within the LR predicted cancer detection range of 5–15% (12.8%). 38.5% of LR4A cancers were detected within 3 months.

Conclusions

Modification of the definition and suggested workup of positive and suspicious lung cancer screening findings appears warranted.

Lung cancer screening primer: Key information for primary care providers

OBJECTIVE

To review new evidence reported since the 2016 publication of the Canadian Task Force on Preventive Health Care recommendations and to summarize key facets of lung cancer screening to better equip primary care providers (PCPs) in anticipation of wider implementation of the recommendations.

QUALITY OF EVIDENCE

A new, large randomized controlled trial has been published since 2016, as have updates from 4 other trials. PubMed was searched for studies published between January 1, 2004, and December 31, 2020, using search words including lung cancer screening eligibility, lung cancer screening criteria, and lung cancer screening guidelines. All information from peer-reviewed articles, reference lists, books, and websites was considered.

MAIN MESSAGE

Lung cancers diagnosed at stage 4 have a 5-year survival rate of only 5% and have a disproportionate impact on those with lower socioeconomic status, rural populations, and Indigenous populations. By downstaging, or diagnosing lung cancers at an earlier and more treatable stage, lung cancer screening reduces mortality with a number needed to screen of 250 to prevent 1 death. Practical aspects of lung cancer screening are reviewed, including criteria to screen, appropriate low-dose computed tomography screening, and management of findings. Harms of screening, such as overdiagnosis and incidental findings, are discussed to allow PCPs to appropriately counsel their patients in the face of ongoing implementation of new lung cancer screening programs.

CONCLUSION

Lung cancer screening, with its embedded emphasis on smoking cessation, is an excellent addition to PCPs' preventive health care tools. The implementation of formal and pilot lung cancer screening programs across Canada means that PCPs will be increasingly required to counsel their patients around the uptake of lung cancer screening.

Pathologic and gene expression comparison of CT- screen detected and routinely detected stage I/0 lung adenocarcinoma in NCCN risk-matched cohorts

INTRODUCTION

Although three randomized control trials have proven mortality benefit of CT lung cancer screening (CTLS), <5% of eligible US smokers are screened. Some attribute this to fear of harm conveyed at shared decision visits, including the harm of overdiagnosis/overtreatment of indolent BAC-like adenocarcinoma.

METHODS

Since the frequency of indolent cancers has not been compared between CTLS and routinely detected cohorts, we compare pathology and RNA expression of 86 NCCN high-risk CTLS subjects to 83 high-risk (HR-R) and 51 low-risk (LR-R) routinely detected patients. Indolent adenocarcinoma was defined as previously described for low malignant potential (LMP) adenocarcinoma along with AIS/MIA. Exome RNA sequencing was performed on a subset of high-risk (CTLS and HR-R) FFPE tumor samples.

RESULTS

Indolent adenocarcinoma (AIS, MIA, and LMP) showed 100% disease-specific survival (DSS) with similar frequency in CTLS (18%) and HR-R (20%) which were comparatively lower than LR-R (33%). Despite this observation, CTLS exhibited intermediate DSS between HR-R and LR-R (5-year DSS: 88% CTLS, 82% HR-R, & 95% LR-R, p = 0.047), possibly reflecting a 0.4 cm smaller median tumor size and lower frequency of tumor necrosis compared to HR-R. WGCNA gene modules derived from TCGA lung adenocarcinoma correlated with aggressive histologic patterns, mitotic activity, and tumor invasive features, but no significant differential expression between CTLS and HR-R was observed.

CONCLUSION

CTLS subjects are at no greater risk of overdiagnosis from indolent adenocarcinoma (AIS, MIA, and LMP) than risk-matched patients whose cancers are discovered in routine clinical practice. Improved outcomes likely reflect detection and treatment at smaller size.

Lung cancer risk following previous abnormal chest radiographs: A 27-year follow-up study of a Chinese lung screening cohort

Background

Chest radiograph (CXR) is still one of the most commonly used diagnostic tools for chest diseases. In this cohort study, we attempted to investigate the magnitude and temporal pattern of lung cancer risk following abnormal CXR findings.

Methods

We conducted an extended follow‐up of an occupational screening cohort in Yunnan, China. The associations between abnormal CXR results from baseline screening, the first four consecutive rounds of CXR screening, all previous rounds of screening and lung cancer risk were analyzed using time‐varying coefficient Cox regression model. The associations of lung cancer risk and previous CXR‐screening results according to histology were also considered. Sensitivity analyses were conducted to assess the robustness of the previous abnormal CXR findings on subsequent lung cancer risk.

Results

Abnormal CXR findings were associated with a significantly increased lung cancer risk. This relative hazard significantly decreased over time. Compared to negative screening results, the adjusted hazard ratios (HR) of baseline abnormal CXR results, and at least one abnormal result in the first four consecutive screening rounds during the first 5 years of follow‐up were 17.06 (95% CI: 11.74–24.79) and 13.77 (95%: 9.58–17.79), respectively. This significantly increased lung cancer risk continued over the next 5 years. These associations were stronger for persistent abnormal findings, and abnormal findings identified in recent screening rounds.

Conclusions

The increased risk was significant for both squamous cell carcinoma and adenocarcinoma. Although decreased over time, an increased lung cancer risk relative to abnormal CXR findings can continue for 10 years.

The perspectives of survivors of Hodgkin lymphoma on lung cancer screening: A qualitative study

BACKGROUND

Hodgkin lymphoma survivors (HLS) are at excess risk of lung cancer as a consequence of HL treatment. HLS without a heavy smoking history are currently unable to access lung cancer screening (LCS) programmes aimed at ever smokers, and there is an unmet need to develop a targeted LCS programme. In this study we prospectively explored HLS perspectives on a future LCS programme, including motivating factors and potential barriers to participation, with the aim of identifying ways to optimise uptake in a future programme.

METHODS

Semistructured telephone interviews were conducted with HLS, aged 18-80 and lymphoma-free for ≥5 years, selected from a clinical database (ADAPT). Participants provided informed consent. Data were analysed using inductive thematic analysis.

RESULTS

Despite awareness of other late effects, most participants were unaware of their excess risk of lung cancer. Most were willing to participate in a future LCS programme, citing the potential curability of early-stage lung cancer and reassurance as motivating factors, whilst prior experience of healthcare was a facilitator. Whilst the screening test (a low dose CT scan) was considered acceptable, radiation risk was a concern for some and travel and time off work were potential barriers to participation.

CONCLUSIONS

Our results suggest that most HLS would participate in a future LCS programme, motivated by perceived benefits. Their feedback identified a need to develop educational materials addressing lung cancer risk and concerns about screening, including radiation risk. Such materials could be provided upon an invitation to LCS. Uptake in a future programme may be further optimized by offering flexible screening appointments close to home.

ABC du dépistage du cancer du poumon

Objectif

Examiner les nouvelles données probantes rapportées depuis la publication, en 2016, des recommandations du Groupe d’étude canadien sur les soins de santé préventifs et résumer les facettes clés du dépistage du cancer du poumon afin de mieux équiper les médecins de première ligne avant la mise en œuvre généralisée des recommandations.

Qualité des données

Depuis 2016, une vaste nouvelle étude randomisée et contrôlée, de même que la mise à jour de 4 autres études ont été publiées. Une recherche d’études publiées entre le 1er janvier 2004 et le 31 décembre 2020 a été effectuée dans PubMed à l’aide des mots-clés anglais lung cancer screening eligibility, lung cancer screening criteria et lung cancer screening guidelines . On a tenu compte de toute l’information trouvée dans les articles revus par les pairs, les listes de références, les manuels et les sites Web.

Message principal

Le cancer du poumon diagnostiqué au stade 4 a un taux de survie à 5 ans d’à peine 5 %, et son impact est disproportionné dans les populations à faible statut socio-économique, rurales et autochtones. En déstadifiant , c’est-à-dire en diagnostiquant le cancer du poumon à un stade plus précoce et plus facilement traitable, le dépistage du cancer du poumon réduit la mortalité, le nombre de sujets à soumettre au dépistage étant de 250 pour prévenir 1 décès. Nous examinons les aspects pratiques du dépistage du cancer du poumon, y compris les critères de dépistage, le dépistage approprié par tomodensitométrie à faible dose et la prise en charge des trouvailles. On parle des préjudices liés au dépistage, comme le surdiagnostic et les trouvailles fortuites, afin de permettre aux médecins de première ligne de bien conseiller leurs patients devant l’adoption de nouveaux programmes de dépistage du cancer du poumon.

Conclusion

Le dépistage du cancer du poumon, qui met l’accent sur l’abandon du tabac, est un excellent ajout à la boîte à outils de prévention du médecin de première ligne. La mise en œuvre de programmes formels et de programmes pilotes de dépistage du cancer du poumon partout au Canada signifie que les médecins de première ligne devront de plus en plus conseiller à leurs patients d’accepter le dépistage du cancer du poumon.

Lung cancer mortality reduction by LDCT screening: UKLS randomised trial results and international meta-analysis

BACKGROUND

The NLST reported a significant 20% reduction in lung cancer mortality with three annual low-dose CT (LDCT) screens and the Dutch-Belgian NELSON trial indicates a similar reduction. We present the results of the UKLS trial.

METHODS

From October 2011 to February 2013, we randomly allocated 4 055 participants to either a single invitation to screening with LDCT or to no screening (usual care). Eligible participants (aged 50-75) had a risk score (LLPv2) ≥ 4.5% of developing lung cancer over five years. Data were collected on lung cancer cases to 31 December 2019 and deaths to 29 February 2020 through linkage to national registries. The primary outcome was mortality due to lung cancer. We included our results in a random-effects meta-analysis to provide a synthesis of the latest randomised trial evidence.

FINDINGS

1 987 participants in the intervention and 1 981 in the usual care arms were followed for a median of 7.3 years (IQR 7.1-7.6), 86 cancers were diagnosed in the LDCT arm and 75 in the control arm. 30 lung cancer deaths were reported in the screening arm, 46 in the control arm, (relative rate 0.65 [95% CI 0.41-1.02]; p=0.062). The meta-analysis indicated a significant reduction in lung cancer mortality with a pooled overall relative rate of 0.84 (95% CI 0.76-0.92) from nine eligible trials.

INTERPRETATION

The UKLS trial of single LDCT indicates a reduction of lung cancer death of similar magnitude to the NELSON and NLST trials and was included in a meta-analysis of nine randomised trials which provides unequivocal support for lung cancer screening in identified risk groups.

FUNDING

NIHR Health Technology Assessment programme; NIHR Policy Research programme; Roy Castle Lung Cancer Foundation.

Patient-centered Reporting in Radiology: A Single-site Survey Study of Lung Cancer Screening Results

PURPOSE

This study aimed to assess whether patients preferred traditional or patient-friendly radiology reports and, secondarily, whether one reporting style led to a subjective improvement in patients' understanding of their imaging results and next steps in their clinical care.

MATERIALS AND METHODS

This randomized study included patients who had previously enrolled in an institutional comprehensive lung cancer screening program. Three hundred patients were randomly selected from the program database to receive both traditional and patient-centered radiology reports. Randomization also occurred at both the risk level of the fictitious test results (low, intermediate, or high) and the order in which the reports were read by each participant. Participants completed a survey providing demographic information and indicating which report style was preferred and which report style led to a better understanding of screening results and future options. In addition, each report style was rated (from 1 to 5) for clarity, understandability, attractiveness, and helpfulness.

RESULTS

A total of 46 responses for report preference data and 41 responses for attribute rating data were obtained. Overall, participants demonstrate a preference for patient-friendly reports (65.2%) over traditional reports (21.7%). On a 5-point scale, average ratings for patient-friendly reports were higher than traditional reports by 1.2 (P<0.001) for clarity, 1.5 (P<0.001) for understandability, 1.5 (P<0.001) for attractiveness, and 1.0 (P<0.001) for helpfulness.

CONCLUSION

Data suggest that patients prefer patient-friendly reports over traditional reports and find them to be clearer, more comprehensible, more attractive, and more helpful.

Screening for Lung Cancer: CHEST Guideline and Expert Panel Report

BACKGROUND

Low-dose chest CT screening for lung cancer has become a standard of care in the United States, in large part because of the results of the National Lung Screening Trial (NLST). Additional evidence supporting the net benefit of low-dose chest CT screening for lung cancer, and 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 Population, Intervention, Comparator, Outcome format to address the benefit and harms of low-dose CT screening, and 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 Grading of Recommendations, Assessment, Development, and Evaluation approach. Meta-analyses were performed when enough evidence was available. Important clinical questions were addressed based on the evidence developed from the systematic literature review. Graded recommendations and ungraded 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 seven graded recommendations and nine 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.

Community-based lung cancer screening by low-dose computed tomography in China: First round results and a meta-analysis

OBJECTIVE

To evaluate the efficiency of low-dose computed tomography (LDCT) screening for lung cancer in China by analyzing the baseline results of a community-based screening study accompanied with a meta-analysis.

METHODS

A first round of community-based lung cancer screening with LDCT was conducted in Tianjin, China, and a systematic literature search was performed to identify LDCT screening and registry-based clinical studies for lung cancer in China. Baseline results in the community-based screening study were described by participant risk level and the lung cancer detection rate was compared with the pooled rate among the screening studies. The percentage of patients per stage was compared between the community-based study and screening and clinical studies.

RESULTS

In the community-based study, 5523 participants (43.6% men) underwent LDCT. The lung cancer detection rate was 0.5% (high-risk, 1.2%; low-risk, 0.4%), with stage I disease present in 70.0% (high-risk, 50.0%; low-risk, 83.3%), and the adenocarcinoma present in 84.4% (high-risk, 61.5%; low-risk, 100%). Among all screen-detected lung cancer, women accounted for 8.3% and 66.7% in the high- and low-risk group, respectively. In the screening studies from mainland China, the lung cancer detection rate 0.6% (95 %CI: 0.3%-0.9%) for high-risk populations. The proportions with carcinoma in situ and stage I disease in the screening and clinical studies were 76.4% (95 %CI: 66.3%-85.3%) and 15.2% (95 %CI: 11.8%-18.9%), respectively.

CONCLUSIONS

The stage shift of lung cancer due to screening suggests a potential effectiveness of LDCT screening in China. Nearly 70% of screen-detected lung cancers in low-risk populations are identified in women.

Detection and verification of coexisting diagnostic markers in plasma and serum of patients with non-small-cell lung cancer

Aim: To screen and identify the potential biomarkers co-existing in plasma and serum of patients with non-small-cell lung cancer (NSCLC), and establish appropriate diagnostic models. Methods: A cohort of 195 plasma samples and 180 serum samples were obtained from healthy controls (HCs), adenocarcinoma (AdC) and squamous cell carcinoma (SqCC) patients enrolled from the First Affiliated Hospital of Nanjing Medical University. Metabolites in plasma and serum were analyzed by GC-MS. Results: Hypoxanthine was found to have good performance in the differential diagnosis of NSCLC (including AdC and SqCC) and HC (area under the receiver operating characteristic [AUROC] ≥0.85). Combinations of metabolites could be used for differential diagnosis of NSCLC and HC (AUROC >0.93), AdC and HC (AUROC >0.91), SqCC and HC (AUROC >0.95), AdC and SqCC (AUROC >0.72). Conclusions: Metabolomics based on GC-MS can screen and identify the differential metabolites coexisting in plasma and serum of patients with NSCLC, and prediction models established by this method can be used for the differential diagnosis of patients with NSCLC.

Scan-based competing death risk model for reevaluating lung cancer computed tomography screening eligibility

PURPOSE

A baseline CT scan for lung cancer (LC) screening may reveal information indicating that certain LC screening participants can be screened less, and instead require dedicated early cardiac and respiratory clinical input. We aimed to develop and validate competing death (CD) risk models using CT information to identify participants with a low LC and a high CD risk.

METHODS

Participant demographics and quantitative CT measures of LC, cardiovascular disease, and chronic obstructive pulmonary disease were considered for deriving a logistic regression model for predicting five-year CD risk using a sample from the National Lung Screening Trial (n=15 000). Multicentric Italian Lung Detection data was used to perform external validation (n=2287).

RESULTS

Our final CD model outperformed an external pre-scan model (CDRAT) in both the derivation (Area under the curve=0.744 [95% confidence interval=0.727 to 0.761] and 0.677 [0.658 to 0.695], respectively) and validation cohorts (0.744 [0.652 to 0.835] and 0.725 [0.633 to 0.816], respectively). By also taking LC incidence risk into consideration, we suggested a risk threshold where a subgroup (6258/23 096, 27%) was identified with a number needed to screen to detect one LC of 216 (versus 23 in the remainder of the cohort) and ratio of 5.41 CDs per LC case (versus 0.88). The respective values in the validation cohort subgroup (774/2287, 34%) were 129 (versus 29) and 1.67 (versus 0.43).

CONCLUSIONS

Evaluating both LC and CD risks post-scan may improve the efficiency of LC screening and facilitate the initiation of multidisciplinary trajectories among certain participants.

PULMONARY NODULE DETECTION IN CHEST CT USING A DEEP LEARNING-BASED RECONSTRUCTION ALGORITHM

This study's aim was to assess whether deep learning image reconstruction (DLIR) techniques are non-inferior to ASIR-V for the clinical task of pulmonary nodule detection in chest computed tomography. Up to 6 (range 3-6, mean 4.2) artificial lung nodules (diameter: 3, 5, 8 mm; density: -800, -630, +100 HU) were inserted at different locations in the Kyoto Kagaku Lungman phantom. In total, 16 configurations (10 abnormal, 6 normal) were scanned at 7.6, 3, 1.6 and 0.38 mGy CTDIvol (respectively 0, 60, 80 and 95% dose reduction). Images were reconstructed using 50% ASIR-V and a deep learning-based algorithm with low (DL-L), medium (DL-M) and high (DL-H) strength. Four chest radiologists evaluated 256 series by locating and scoring nodules on a five-point scale. No statistically significant difference was found among the reconstruction algorithms (p = 0.987, average across readers AUC: 0.555, 0.561, 0.557, 0.558 for ASIR-V, DL-L, DL-M, DL-H).

Results of Second Round Lung Cancer Screening by Low-Dose CT scan - French Cohort Study (DEP-KP80)

INTRODUCTION

Over the last few years, lung cancer screening by low-dose CT scan has demonstrated a decrease in lung cancer mortality. While this method has been in use since 2013 in the United States of America, no European country has yet implemented a systematic screening program. We hereby report the results from the second round of screening from a French cohort study.

PATIENTS AND METHODS

DEP KP80 is a prospective study evaluating lung cancer screening by means of three low-dose computer tomography (CT) scans at 1-year intervals in 1,307 participants, aged 55 to 74 years old, all smokers or former smokers, having quit within the last 15 years, with over 30 pack years. The results of the first round demonstrated it was possible to conduct effective screening in real-life situations.

RESULTS

Participation was lower in this second round than in the first (35.3% vs. 73.1%, P < .001). The rate of negative results was significantly higher and that of undetermined results lower than those produced in the first round. Overall, 75% of cancers revealed were Stage 1 and 87.5% benefitted from surgical treatment. The incidence of cancer in the second round was 2.43%.

CONCLUSION

As with the first round, the results of this second round confirm the feasibility and efficacy of lung cancer screening. The lower participation rate for this second round is proof of the need to improve awareness among participants and healthcare professionals of the relevance of committing to an annual screening program.

Total and Out-of-Pocket Costs of Procedures After Lung Cancer Screening in a National Commercially Insured Population: Estimating an Episode of Care

OBJECTIVE

Consequences of lung cancer screening (LCS) with low-dose chest CT in clinical settings, including procedures, costs, and complications, are incompletely understood. We evaluated downstream invasive procedures after LCS, total and out-of-pocket (OOP) costs of these procedures, and correlates of procedural rates and costs.

METHODS

Using the Clinformatics Data Mart, we retrospectively included patients between ages 55 and 79 years receiving LCS between 2015 and 2017. The types and frequency of downstream invasive procedures (including needle biopsy, bronchoscopy, surgery, and cytology) were described. Treating the LCS examination and downstream procedures as a single LCS episode, we described the per-episode total costs (insurance reimbursement + OOP costs of LCS and downstream procedures) and OOP costs. Correlates of costs were determined using linear and logistic regression.

RESULTS

A total of 6,268 patients received at least one low-dose chest CT; 462 patients (7.4%) received at least one procedure within 12 months after LCS (needle biopsy 69.0%, cytology 23.6%, bronchoscopy 18.6%, surgery 23.8%). Women and patients ≥65 years were more likely to receive a downstream procedure. Ninety-three patients (20.1%) were diagnosed with lung cancer after LCS. The total cost of managing this population of lung screeners was $5,060,511.04, with an average per-episode total cost of $740.06. The aggregate OOP costs to this population of lung screeners was $427,069.74, with an average per-episode OOP cost of $62.46.

CONCLUSIONS

Rates of invasive procedures after LCS in a commercially insured population exceeded those of clinical trials. Considering LCS and associated downstream procedures as an episode of care results in modest OOP cost.

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.

Establishing a Cohort and a Biorepository to Identify Biomarkers for Early Detection of Lung Cancer: The Nashville Lung Cancer Screening Trial Cohort

Rationale: A prospective longitudinal cohort of individuals at high risk of developing lung cancer was established to build a biorepository of carefully annotated biological specimens and low-dose computed tomography (LDCT) chest images for derivation and validation of candidate biomarkers for early detection of lung cancer.Objectives: The goal of this study is to characterize individuals with high risk for lung cancer, accumulating valuable biospecimens and LDCT chest scans longitudinally over 5 years.Methods: Participants 55-80 years of age with a 5-year estimated risk of developing lung cancer >1.5% were recruited and enrolled from clinics at the Vanderbilt University Medical Center, Veteran Affairs Medical Center, and Meharry Medical Center. Individual demographic characteristics were assessed via questionnaire at baseline. Participants underwent an LDCT scan, spirometry, sputum cytology, and research bronchoscopy at the time of enrollment. Participants will be followed yearly for 5 years. Positive LDCT scans are followed-up according to standard of care. The clinical, imaging, and biospecimen data are collected prospectively and stored in a biorepository. Participants are offered smoking cessation counseling at each study visit.Results: A total of 480 participants were enrolled at study baseline and consented to sharing their data and biospecimens for research. Participants are followed with yearly clinic visits to collect imaging data and biospecimens. To date, a total of 19 cancers (13 adenocarcinomas, four squamous cell carcinomas, one large cell neuroendocrine, and one small-cell lung cancer) have been identified.Conclusions: We established a unique prospective cohort of individuals at high risk for lung cancer, enrolled at three institutions, for whom full clinical data, well-annotated LDCT scans, and biospecimens are being collected longitudinally. This repository will allow for the derivation and independent validation of clinical, imaging, and molecular biomarkers of risk for diagnosis of lung cancer.Clinical trial registered with ClinicalTrials.gov (NCT01475500).

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs.

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.

Impact of low-dose computed tomography for lung cancer screening on lung cancer surgical volume: The urgent need in health workforce education and training

This study aimed to investigate the time trend variation in the surgical volume and prognostic outcome of patients with lung cancer after the gradual prolonged implementation of a low-dose computed tomography (LDCT) lung cancer screening program.Using the hospital-based cancer registry data on number of patients with lung cancer and deaths from 2008 to 2017, we conducted a retrospective study using a hospital-based cohort to investigate the relationship between changes in lung cancer surgical volume, the proportion of lung-sparing surgery, and prolonged prognostic outcomes after the gradual implementation of the LDCT lung cancer screening program in recent years.From 2008 to 2017, 3251 patients were diagnosed with lung cancer according to the hospital-based cancer registry. The 5-year mortality rate decreased gradually from 83.54% to 69.44% between 2008 and 2017. The volume of total lung cancer surgical procedures and proportion of lung-sparing surgery performed gradually increased significantly from 2008 to 2017, especially from 2014 to 2017 after implementation of a large volume of LDCT lung cancer screening examinations. In conclusion, our real-world data suggest that there will be an increase in cases of operable early-stage lung cancers, which in turn will increase the surgical volume and proportion of lung-sparing surgery, after the gradual implementation of the LDCT lung cancer screening program in recent years. These findings suggest the importance of a successful national policy regarding LDCT screening programs, regulation of shortage of thoracic surgeons, thoracic radiologist workforce training positions, and education programs.

Racial Differences in Adherence to Lung Cancer Screening Follow-Up: A Systematic Review and Meta-Analysis

BACKGROUND

In 2013 the United States Preventive Services Taskforce (USPSTF) instituted recommendations for annual lung cancer screening (LCS) with low dose chest computed tomography for high-risk individuals. LCS reduces lung cancer mortality, with greater reduction observed in Black participants in clinical trials. While racial disparities in lung cancer mortality have been well documented, less is known about disparities in LCS participation and adherence to follow-up in clinical practice.

RESEARCH QUESTION

What is the association between race and adherence to LCS follow-up?

STUDY DESIGN & METHODS

A systematic review was conducted through a search of published studies in MEDLINE, PubMed, EMBASE, Web of Science, and Cumulative Index to Nursing and Allied Health Literature Database, from database inception through October 2020. We included studies that examined rates of adherence to LCS follow-up and compared rates by race. Studies were pooled using random-effects meta-analysis.

RESULTS

We screened 18,300 titles/abstracts and 229 studies were selected for full-text review. Nine studies met inclusion criteria; seven were included in the meta-analysis. Median adherent follow-up rate was 37% (range 16-82%). Notable differences among the studies included the proportion of the Black population (range 4-47%) and the structure of the LCS programs. The meta-analyses showed lower adherence to LCS follow-up in the Black population (Odds Ratio [OR]=0.67, [95% CI: 0.55, 0.80]). This disparity persisted across all malignancy risk levels determined by initial screening results.

INTERPRETATION

There is lower adherence to LCS follow-up in Black compared to White patients despite the higher potential lung cancer mortality benefit. Literature specifically addressing race-related barriers to LCS adherence is still limited. To ensure equity in LCS benefits, greater outreach to eligible Black patients should be implemented through increased physician education and utilization of screening program coordinators to focus on this patient population.

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.

Association of Inclusion of More Black Individuals in Lung Cancer Screening With Reduced Mortality

Importance

The potential to achieve greater reductions in lung cancer mortality than originally estimated by the National Lung Screening Trial with the inclusion of more Black participants stresses the importance of improving access to lung cancer screening for Black current and former smokers, a population presently with the highest lung cancer morbidity and mortality.

Objective

To estimate lung cancer and all-cause mortality reductions achievable with lung cancer screening via low-dose computed tomography (LDCT) of the chest in populations with greater proportions of Black screening participants than seen in the original NLST cohort.

Design, Setting, and Participants

This cohort study was conducted as a secondary analysis of existing data from the National Lung Screening Trial, a large national randomized clinical trial conducted from 2002 through 2009. NLST participants were current or former smokers, aged between 55 and 74 years, with at least 30 pack-years of smoking history and less than 15 years since quitting. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% CIs of lung cancer mortality and all-cause mortality according to LDCT screening compared with chest radiograph screening. Using a transportability formula, we estimated outcomes for LDCT screening among hypothetical populations by varying the distributions of Black individuals, women, and current smokers. Data were analyzed between September 2020 and March 2021.

Exposures

Lung screening with LDCT of the chest compared with chest radiography.

Main Outcomes and Measures

Lung cancer mortality and all-cause mortality.

Results

This study included a total of 53 452 participants enrolled in the NLST. Of 2376 Black individuals and 51 076 non-Black individuals, 21 922 (41.0%) were women and the mean (SD) age was 61.4 (5.0) years. Over a median (interquartile range) follow-up of 6.7 (6.2-7.0) years, LDCT screening among the synthesized population with a higher proportion of Black individuals (13.4%, mirroring US Census data) was associated with a greater relative reduction of lung cancer mortality (eg, Black individuals: HR, 0.82; 95% CI, 0.72-0.92; vs entire NLST cohort: HR, 0.84; 95% CI, 0.76-0.96). Further reductions in lung cancer mortality by LDCT screening were found among a hypothetical population with a higher proportion of men or current smokers, along with a higher proportion of Black individuals (ie, 60% Black participants; 20% to 40% women) (HR, 0.68; 95% CI, 0.48-0.97).

Conclusions and Relevance

The potential to achieve greater reductions in lung cancer mortality than originally estimated by the NLST with the inclusion of more Black participants stresses the critical importance of improving access to lung cancer screening for Black current and former smokers.

Performance of Lung Nodule Management Algorithms for Lung-RADS Category 4 Lesions

PURPOSE

To test the performance of the American College of Chest Physicians (ACCP) and British Thoracic Society (BTS) algorithms to stratify high-risk nodules identified at lung cancer screening.

METHOD AND MATERIALS

Patients with Lung-RADS category 4 nodules identified on lung cancer screening computed tomography (CT) between March 2014 and August 2018 were identified, and a subset of 150 were randomly selected. Nodule characteristics and, if available, fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET)-CT scan were recorded. Radiologists blinded to final diagnosis and downstream testing performed five-point visual assessment score for probability of nodule malignancy; their accuracies are averaged below. Probabilities of malignancy according to Brock and Herder models were calculated. ACCP and BTS algorithms were applied to the nodules.

RESULTS

Final diagnosis of malignancy was made in 65/150 (43%) of patients. The sensitivity, specificity and accuracy for nodule malignancy were: radiologist visual score (92%, 85%, 88%); BTS (76%, 91%, 85%); ACCP (63%, 89%, 78%); and Brock calculator (77%, 71%, 73%). The sensitivity, specificity, and accuracy for nodule malignancy in patients with FDG PET-CT scan (n = 78) were: FDG uptake (91%, 64%, 83%); Herder probability (91%, 68%, 83%); radiologist visual score (93%, 69%, 86%); BTS (84%, 64%, 78%); Brock probability (82%, 50%, 72%); and ACCP (68%, 59%, 65%).

CONCLUSION

Thoracic radiologist visual analysis yielded the greatest accuracy for nodule triage in the entire cohort. BTS performed better than ACCP guidelines and both performed better than the Brock model alone.

Application of computer-aided diagnosis for Lung-RADS categorization in CT screening for lung cancer: effect on inter-reader agreement

OBJECTIVES

To evaluate the effects of computer-aided diagnosis (CAD) on inter-reader agreement in Lung Imaging Reporting and Data System (Lung-RADS) categorization.

METHODS

Two hundred baseline CT scans covering all Lung-RADS categories were randomly selected from the National Lung Cancer Screening Trial. Five radiologists independently reviewed the CT scans and assigned Lung-RADS categories without CAD and with CAD. The CAD system presented up to five of the most risk-dominant nodules with measurements and predicted Lung-RADS category. Inter-reader agreement was analyzed using multirater Fleiss κ statistics.

RESULTS

The five readers reported 139-151 negative screening results without CAD and 126-142 with CAD. With CAD, readers tended to upstage (average, 12.3%) rather than downstage Lung-RADS category (average, 4.4%). Inter-reader agreement of five readers for Lung-RADS categorization was moderate (Fleiss kappa, 0.60 [95% confidence interval, 0.57, 0.63]) without CAD, and slightly improved to substantial (Fleiss kappa, 0.65 [95% CI, 0.63, 0.68]) with CAD. The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% [201/371] vs. 63.6% [232/365]). The proportion of disagreement in nodule size measurement was reduced from 5.1% (102/2000) to 3.1% (62/2000) with the use of CAD (p < 0.001). In 31 cancer-positive cases, substantial management discrepancies (category 1/2 vs. 4A/B) between reader pairs decreased with application of CAD (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004).

CONCLUSIONS

Application of CAD demonstrated a minor improvement in inter-reader agreement of Lung-RADS category, while showing the potential to reduce measurement variability and substantial management change in cancer-positive cases.

KEY POINTS

• Inter-reader agreement of five readers for Lung-RADS categorization was minimally improved by application of CAD, with a Fleiss kappa value of 0.60 to 0.65. • The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% vs. 63.6%). • In 31 cancer-positive cases, substantial management discrepancies between reader pairs, referring to a difference in follow-up interval of at least 9 months (category 1/2 vs. 4A/B), were reduced in half by application of CAD (32/310 to 16/310) (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004).

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.

Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial

OBJECTIVE

To explore the value of a deep learning-based algorithm in detecting Lung CT Screening Reporting and Data System category 4 nodules on chest radiographs from an asymptomatic health checkup population.

METHODS

Data from an annual retrospective cohort of individuals who underwent chest radiographs for health checkup purposes and chest CT scanning within 3 months were collected. Among 3073 individuals, 118 with category 4 nodules on CT were selected. A reader performance test was performed using those 118 radiographs and randomly selected 51 individuals without any nodules. Four radiologists independently evaluated the radiographs without and with the results of the algorithm; and sensitivities/specificities were compared. The sample size needed to confirm the difference in detection rates was calculated, i.e., the number of true-positive radiographs divided by the total number of radiographs.

RESULTS

The sensitivity of the radiologists substantially increased aided by the algorithm (38.8% [183/472] to 45.1% [213/472]; p < .001) without significant change in specificity (94.1% [192/204] vs. 92.2% [188/204]; p = .22). Pooled radiologists detected more nodules with the algorithm (32.0% [156/488] vs. 38.9% [190/488]; p < .001), without alteration of false-positive rates (0.09 [62/676], both). Pooled detection rates for the annual cohort were 1.49% (183/12,292) and 1.73% (213/12,292) without and with the algorithm, respectively. A sample size of 41,776 in each arm would be required to demonstrate significant detection rate difference with < 5% type I error and > 80% power.

CONCLUSION

Although readers substantially increased sensitivity in detecting nodules on chest radiographs from a health checkup population aided by the algorithm, detection rate difference was only 0.24%, requiring a sample size >80,000 for a randomized controlled trial.

KEY POINTS

• Aided by a deep learning algorithm, pooled radiologists improved their sensitivity in detecting Lung-RADS category 4 nodules on chest radiographs from a health checkup population (38.8% [183/472] to 45.1% [213/472]; p < .001), without increasing false-positive rate. • The prevalence of the Lung-RADS category 4 nodules was 3.8% (118/3073) on the population, resulting in only 0.24% increase of the detection rate for the radiologists with assistance of the algorithm. • To confirm the significant detection rate increase by a randomized controlled trial, a sample size of 84,000 would be required.

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.

A model based on the quantification of complement C4c, CYFRA 21-1 and CRP exhibits high specificity for the early diagnosis of lung cancer

Lung cancer screening detects early-stage cancers, but also a large number of benign nodules. Molecular markers can help in the lung cancer screening process by refining inclusion criteria or guiding the management of indeterminate pulmonary nodules. In this study, we developed a diagnostic model based on the quantification in plasma of complement-derived fragment C4c, cytokeratin fragment 21-1 (CYFRA 21-1) and C-reactive protein (CRP). The model was first validated in two independent cohorts, and showed a good diagnostic performance across a range of lung tumor types, emphasizing its high specificity and positive predictive value. We next tested its utility in two clinically relevant contexts: assessment of lung cancer risk and nodule malignancy. The scores derived from the model were associated with a significantly higher risk of having lung cancer in asymptomatic individuals enrolled in a computed tomography (CT)-screening program (OR = 1.89; 95% CI = 1.20-2.97). Our model also served to discriminate between benign and malignant pulmonary nodules (AUC: 0.86; 95% CI = 0.80-0.92) with very good specificity (92%). Moreover, the model performed better in combination with clinical factors, and may be used to reclassify patients with intermediate-risk indeterminate pulmonary nodules into patients who require a more aggressive work-up. In conclusion, we propose a new diagnostic biomarker panel that may dictate which incidental or screening-detected pulmonary nodules require a more active work-up.

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.

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

OBJECTIVES

Low-dose computed tomography (LDCT) screening is an important tool for reducing lung cancer mortality. This study describes a single center's experience with LDCT and attempts to identify any barriers to compliance with standard guidelines.

MATERIALS AND METHODS

This is a retrospective review of a single university-based hospital system from 2015 to 2019. All individuals who met eligibility for lung cancer screening were entered into a database. The definition of adherence with the screening program was determined by the recommended timeline for the follow-up LDCT. Cohorts were split by adherence and demographics were compared.

RESULTS

A total of 203 LDCTs were performed in 121 patients who met eligibility for LDCT and had appropriate surveillance from 2015 to 2019. The average age was 64 years old. The overall adherence rate for prescribed LDCTs was 59.1%. Patients with Lung-RADS score 2 had 2.43 times higher odds of adherence relative to patients with Lung-RADS score 1 (odds ratio [OR]=2.43; 95% confidence interval [CI]: 1.23-4.83; P=0.011). African American patients had 42% lower odds of adherence relative to white patients (OR=0.58; 95% CI: 0.32-1.06; P=0.076). Patients with non-District of Columbia zip codes had 57% higher odds of adherence relative to those with District of Columbia zip codes, although this did not reach statistical significance (OR=1.57; 95% CI: 0.87-2.82; P=0.136).

CONCLUSIONS

Despite the implementation of a multidisciplinary, academic LDCT screening program, overall adherence rate to prescribed follow-up scans was suboptimal. Socioeconomic disparities and African American race may negatively affect adherence to lung cancer screening LDCT guidelines. Patients with concerning findings on initial LDCT had a higher association of adherence to guidelines.

Utility of incorporating a gene-based lung cancer risk test on uptake and adherence in a community-based lung cancer screening pilot study

Based on the results of randomized control trials, screening for lung cancer using computed tomography (CT) is now widely recommended. However, adherence to screening remains an issue outside the clinical trial setting. This study examines the utility of biomarker-based risk assessment on uptake and subsequent adherence in a community screening study.

In a single arm pilot study, current or former smokers > 50 years old with 20 + pack year history were recruited following local advertising. One hundred and fifty seven participants volunteered to participate in the study that offered an optional gene-based lung cancer risk assessment followed by low-dose CT according to a standardised screening protocol.

All 157 volunteers who attended visit 1 underwent the gene-based risk assessment comprising of a clinical questionnaire and buccal swab. Of this group, 154 subsequently attended for CT screening (98%) and were followed prospectively for a median of 2.7 years. A participant’s adherence to screening was influenced by their baseline lung cancer risk category, with overall adherence in those with a positive scan being significantly greater in the “very high” risk group compared to “moderate” and “high” risk categories (71% vs 52%, Odds ratio = 2.27, 95% confidence interval of 1.02–5.05, P = 0.047). Those in the “moderate” risk group were not different to those in the “high” risk group (52% and 52%, P > 0.05).

In this proof-of-concept study, personalised gene-based lung cancer risk assessment was well accepted, associated with a 98% uptake for screening and increased adherence for those in the highest risk group.

[Lung cancer screening with low dose computed tomography : a systematic review]

INTRODUCTION

Bronchial cancer, often diagnosed at a late stage, is the leading cause of cancer death. As early detection could potentially lead to curative treatment, several studies have evaluated low-dose chest CT (LDCT) as a screening method. The main objective of this work is to determine the impact of LDCT screening on overall mortality of a smoking population.

METHODS

Systematic review of randomised controlled screening trials comparing LDCT with no screening or chest x-ray.

RESULTS

Thirteen randomised controlled trials were identified, seven of which reported mortality results. NSLT showed a significant reduction of 6.7% in overall mortality and 20% in lung cancer mortality after 6.5 years of follow-up. NELSON showed a significant reduction in lung cancer mortality of 24% at 10 years among men. LUSI and MILD showed a reduction in lung cancer mortality of 69% at 8 years among women and 39% at 10 years, respectively.

CONCLUSION

Screening for bronchial cancer is a complex issue. Clarification is needed regarding the selection of individuals, the definition of a positive result and the attitude towards a suspicious nodule.

Optimizing the timing of diagnostic testing after positive findings in lung cancer screening: a proof of concept radiomics study

BACKGROUND

The timeliness of diagnostic testing after positive screening remains suboptimal because of limited evidence and methodology, leading to delayed diagnosis of lung cancer and over-examination. We propose a radiomics approach to assist with planning of the diagnostic testing interval in lung cancer screening.

METHODS

From an institute-based lung cancer screening cohort, we retrospectively selected 92 patients with pulmonary nodules with diameters ≥ 3 mm at baseline (61 confirmed as lung cancer by histopathology; 31 confirmed cancer-free). Four groups of region-of-interest-based radiomic features (n = 310) were extracted for quantitative characterization of the nodules, and eight features were proven to be predictive of cancer diagnosis, noise-robust, phenotype-related, and non-redundant. A radiomics biomarker was then built with the random survival forest method. The patients with nodules were divided into low-, middle- and high-risk subgroups by two biomarker cutoffs that optimized time-dependent sensitivity and specificity for decisions about diagnostic workup within 3 months and about repeat screening after 12 months, respectively. A radiomics-based follow-up schedule was then proposed. Its performance was visually assessed with a time-to-diagnosis plot and benchmarked against lung RADS and four other guideline protocols.

RESULTS

The radiomics biomarker had a high time-dependent area under the curve value (95% CI) for predicting lung cancer diagnosis within 12 months; training: 0.928 (0.844, 0.972), test: 0.888 (0.766, 0.975); the performance was robust in extensive cross-validations. The time-to-diagnosis distributions differed significantly between the three patient subgroups, p < 0.001: 96.2% of high-risk patients (n = 26) were diagnosed within 10 months after baseline screen, whereas 95.8% of low-risk patients (n = 24) remained cancer-free by the end of the study. Compared with the five existing protocols, the proposed follow-up schedule performed best at securing timely lung cancer diagnosis (delayed diagnosis rate: < 5%) and at sparing patients with cancer-free nodules from unnecessary repeat screenings and examinations (false recommendation rate: 0%).

CONCLUSIONS

Timely management of screening-detected pulmonary nodules can be substantially improved with a radiomics approach. This proof-of-concept study's results should be further validated in large programs.

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.

Managing of screening-detected sub-solid nodules-a European perspective

Since the National Lung Screening Trial in 2011 showed a 20% reduction in lung cancer mortality using annual low-dose computed tomography (LDCT), several randomised controlled trials and studies have been started in Europe. These include the Italian lung study (ITALUNG), the Dutch-Belgian lung cancer screening trial (NELSON), the UK lung cancer screening trial (UKLS), the Detection and screening of early lung cancer with novel imaging technology (DANTE), the Danish lung cancer screening trial (DLCST), the German lung cancer screening intervention trial (LUSI), the Multicentric Italian lung detection trial (MILD) and the CT screening for lung cancer study (COSMOS). As a result of the increasing number of screening trials and the growing utilization of LDCT, the high detection of subsolid nodules is an increasingly important clinical problem. In the last few years, several guidelines have been published and providing guidance on the optimal management of subsolid nodules, but many controversies still exist. Follow-up imaging plays an important role in clinical assessment and subsequent management of this particular type of lung nodules, since they can be transient inflammatory lesions, and if persistent they can be both benign lesions or lung cancers of variable clinical behaviour. However, the vast majority of subsolid nodules retain an indolent course over many years. The aim of this review is to present a European perspective in management of screening detected subsolid nodules.

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.