First Research Results

Objective: Randomized studies from the past demonstrate the effectiveness of CT lung cancer screening, sparking discussions about population-based programs. Smoking is the primary risk factor for developing lung cancer, making screening risk-based. Selecting high-risk individuals is crucial for cost-effective implementation. Further risk analysis can enhance efficiency, personalize the intervals between scans, and reduce inequalities. However, challenges exist, as risk-based methods can negatively impact the balance between benefits and drawbacks. Widespread implementation has been limited so far, raising questions about efficiently identifying high-risk individuals. This review examines the opportunities and challenges of risk assessment in lung cancer screening.  

Conclusion: Challenges persist, but studies such as the ILST, SUMMIT, Manchester Long Health Check, Ontario's High-Risk Lung Cancer Screening Program, and 4-IN-THE-LUNG-RUN are evaluating risk-based lung cancer screening. These studies aim to address existing challenges and identify new opportunities for risk stratification.

van der Aalst C, Vonder M, Hubert J, Moldovanu D, Schmitz A, Delorme S, et al. P1.14-04 European Lung Cancer Screening Implementation: 4-IN-THE-LUNG-RUN trial. Journal of Thoracic Oncology. 2023;18(11):S217.

Objective: The European Commission has recommended expanding targeted lung cancer screening in their 2022 recommendation to improve early detection. However, many relevant questions remain regarding the optimal screening policy for lung cancer for individuals. The 4-IN-THE-LUNG-RUN (Towards INdividually tailored INvitations, screening INtervals, and INtegrated co-morbidity reducing strategies in lung cancer screening): A randomized comparison of personalized lung cancer screening regimes will be conducted. The aim of the 4-IN-THE-LUNG-RUN study is to develop and implement the most optimal and personalized CT lung cancer screening program for high-risk individuals and to integrate (co-) morbidity reducing strategies.  

Method: Approximately 900,000 individuals will be recruited in 5 European countries. A population approach as well as a tailored screening approach will be applied. In the Netherlands, individuals from the general population aged 60-79 years will be approached via: standard paper, standard online, or tailored online invitations. The inclusion criteria are as follows: Individuals aged 60-79 years who meet criterion a) or b): a) ≥35 pack years; current smoker or <10 years since quitting. b) PLCOm2012NoRace risk ≥2.60% (6yr) to achieve a power of 70%. All participating individuals will receive a single baseline low-dose thoracic CT scan. The use of a specialized CT protocol will enable evaluation of lung nodules, coronary calcium, and emphysema. Individuals with a positive baseline screening will not be randomized; however, they will receive two additional CT scans with an annual screening interval. Individuals with a negative baseline screening will be randomized 1:1 to either the standard annual screening arm (which adheres to an annual interval between screenings (up to two CT screens after baseline)) or the risk-based biennial screening arm (which adheres to a biennial interval between screenings (up to one CT screen after baseline)). Randomization will be stratified by country and gender. All participants will be informed about the possibility of using certified smoking cessation coaches at or around the screening location.  

Results: In the coming two years, the expected number of included individuals is estimated to be 26,000. Each participant will be followed for at least 5 years to enable analyses of the primary and key secondary endpoints: The primary analysis will compare the cumulative hazard ratio of stage I/II cancers between the two randomized groups. Secondary endpoints will include the rates of (late-stage) interval cancers in each arm, gross costs, and the comparison of the (cost-) effectiveness of the evaluated recruitment, screening, and smoking cessation strategies in each arm, as well as evaluating gender and sex differences in lung cancer risk and screening effectiveness.  

Conclusion: This is the first large-scale multicenter implementation study of Volume CT lung cancer screening in multiple European countries. A total of 26,000 participants will be included and screened annually or biennially in the coming two years. The relative safety (i.e., comparable detection of favorable lung cancer stages I-II) of a personalized risk-based less intensive screening regime based on a combination of health risk factors, baseline CT scan results, and possibly eventual biomarker outcomes among individuals aged 60-79 years with a high risk of developing lung cancer will be assessed.

van der Aalst CM, Ten Haaf K, de Koning HJ. Implementation of lung cancer screening: what are the main issues? Transl Lung Cancer Res. 2021;10(2):1050-63.

Two large-scale randomized trials have previously demonstrated that computed tomography (CT) lung cancer screening is effective in reducing lung cancer mortality (8-24% in men, 26-59% in women). However, lung cancer screening implies personal and risk-based approaches. The implementation of personalized screening and prevention by healthcare systems is still scarce and likely of variable quality, due to significant remaining uncertainties that have not been fully addressed so far. Further optimization of lung cancer screening programs is expected to reduce harm and maintain or increase the benefit for eligible European citizens, while significantly lowering healthcare costs. Several key 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 (an acronym for: Towards INdividually tailored INvitations, screening INtervals and INtegrated co-morbidity reducing strategies in lung cancer screening) is the first multicentre implementation study on volume CT lung cancer screening among 24,000 men and women at high risk of developing lung cancer, in five European countries, launched in January 2020. By providing answers to the remaining questions with this study, many EU citizens will soon benefit from this high-quality screening technology, others will experience less harm than previously expected, and healthcare costs will be significantly reduced. Implementing a new cancer screening program is a major task, with many stakeholders and numerous potential facilitators, but also barriers and obstacles.

Hubert J, Moldovanu D, van den Bosch I, de Nijs K, Haaf KT, Oudkerk M, et al. Impact of recruitment method on informed decision-making in lung cancer screening in the 4-IN-THE-LUNG-RUN trial. Lung Cancer. 2025;207:108686.

Objective: It is relatively unknown how to inform individuals about lung cancer screening to enable informed decision-making (IDM). This study aims to determine the level of IDM among different recruitment methods among participants invited to the 4-IN-THE-LUNG-RUN study, the European implementation study for lung cancer screening.  

Method: An online questionnaire of 23 items regarding decision-relevant knowledge was sent to 848 Dutch men and women aged 60-79 years, who were randomized in 4-IN-THE-LUNG-RUN. Respondents were considered sufficiently informed when they answered at least 12 items correctly. Informed choice was determined as 1) having sufficient knowledge and 2) consistency between the intention to be screened and actual participation.  

Results: Participants were recruited between July 2024 and August 2024. Of the 386 respondents (45.5%) with fully completed questionnaires, 327 (84.7%) had sufficient knowledge and made an informed decision, 283 (85.2%) of the screened participants (n = 332) did so. Knowledge scores increased with the level of tailoring compared to standard paper information (p = 0.015). While 78.1% of the standard paper group made an informed choice, 89.0% of the tailored group did so (p = 0.088). IDM was similar between groups with different socioeconomic status (SES): 79.8% (95/119) of participants in the lower, 84.5% (93/110) in the middle, and 88.5% (139/157) in the high SES group made an informed decision (p = 0.138). No gender-related differences were found in informed decision-making: 196 of 231 men (84.8%) versus 131 of 155 women (84.5%), p = 0.929. Even if it is assumed that all respondents with incomplete questionnaires had insufficient knowledge, 69.6% were able to make an informed decision.  

Conclusion: The way participants are informed contributes to the extent to which they can make an informed decision. A more tailored approach leads to improved knowledge, facilitating IDM. The results indicate that there is an equivalent level of IDM across different SES and gender groups.

Jiang B, Han D, van der Aalst CM, Lancaster HL, Vonder M, Gratama JC, et al. Lung cancer volume doubling time by computed tomography: A systematic review and meta-analysis. Eur J Cancer. 2024;212:114339.

Objective: The growth rate of lung cancer influences screening strategies and treatment decisions. This review aims to provide an overview of the growth rate of primary lung cancer, quantified by the volume doubling time (VDT) through computed tomography (CT) measurements.  

Methods: According to the PRISMA-DTA guidelines, PubMed, EMBASE, and Web of Science were searched until March 2024 for studies reporting CT-measured VDT of pathologically confirmed primary lung cancer prior to intervention. Summary data were extracted from published reports by two independent researchers. Primary outcomes were the average pooled VDT of lung cancer by nodule type and histology, the distribution of indolent lung cancer (defined as VDT > 400 days or negative), and correlated factors.  

Results: Thirty-three studies were eligible, with a total of 3959 patients with primary lung cancer (mean age: 57.6-77.0 years; 60.0% men). The average pooled VDT for solid, part-solid, and non-solid lung cancer was 207, 536, and 669 days, respectively (p < 0.001). When stratification by histology within solid lung cancer was applied, the average pooled VDT of adenocarcinoma, squamous cell carcinoma, small cell lung cancer, and others was 223, 140, 73, and 178 days, respectively (p < 0.001). Indolent lung cancer was observed in 34.9% of lung cancer cases, primarily in adenocarcinoma (68.9%). Adenocarcinoma was associated with slower growth, while factors such as tumor size, solidity, TNM staging, and smoking history were positively associated with growth rates.  

Conclusion: The average pooled VDT of solid lung cancer was approximately 207 days, demonstrating significant variability in histology, but remains below the referral threshold of 400 days. Important predictors of growth rate are histology, size, solidity, and smoking history, essential for tailoring early intervention strategies.

Jiang B, Lancaster HL, Davies MPA, Gratama JC, Silva M, Han D, et al. AI performance for nodule volume doubling time in the follow-up of the UKLS lung cancer screening study compared to expert consensus and histological validation. Eur J Cancer. 2025;232:116137.

Objective: Validating an artificial intelligence (AI) software for the automated assessment of nodule growth by measuring the volume doubling time (VDT) on protocol-prescribed follow-up low-dose CT (LDCT) scans from the UK lung cancer screening (UKLS) study.  

Methods: This validation study involved 710 UKLS participants with 939 LDCT follow-up scans (361 3-month and 578 12-month). Follow-up scans were independently assessed by both AI and human readers. A positive finding that warranted referral was defined as the largest nodule with a solid component ≥ 100 mm3 that exhibited VDT ≤ 400 days at follow-up. Performance was compared to the European expert panel (reference standard) and then to the histological outcomes (gold standard).  

Results: Compared to the expert panel, AI achieved the lowest 3-month negative misclassification (NM) rate (1/11, 9.1%), compared to human readers (range: 18.2-63.6%). The positive misclassification (PM) rate of AI was initially 7.8% (28/361) after 3 months, but decreased to 0.9% (5/578) after 12 months. Relative to histological outcomes of 9 screen-detected lung cancers, AI identified VDT ≤ 400 days in all 4 cancers that were also rated positive by the expert panel at the earliest 3-month follow-up, while human readers missed or delayed referrals in 1-3 of these cases. AI also identified VDT ≤ 400 days in 3 of the 5 cancers that the panel classified as negative, primarily due to their sub-threshold volume (<100mm³).  

Conclusion: The automated AI system demonstrated strong VDT assessment performance in follow-up screening and outperformed human readers in the early identification of rapid growth in histologically confirmed cancers, supporting the potential to improve risk stratification and facilitate earlier detection of lung cancer.

Lancaster HL, Heuvelmans MA, Oudkerk M. Low-dose computed tomography lung cancer screening: Clinical evidence and implementation research. J Intern Med. 2022;292(1):68-80.

Lung cancer causes more deaths than breast cancer, cervical cancer, and colorectal cancer combined. Nevertheless, population screening for lung cancer is still not considered standard practice in most countries worldwide. Early detection of lung cancer leads to better survival outcomes: patients diagnosed with stage 1A lung cancer have a >75% 5-year survival rate, compared to <5% at stage 4. Low-dose CT (LDCT) thoracic imaging for the secondary prevention of lung cancer has been extensively studied and has shown to significantly reduce lung cancer mortality in at-risk populations. The American National Lung Screening Trial (NLST) reported an overall 20% reduction in lung cancer mortality when comparing LDCT to a chest X-ray, and the Dutch-Belgian Lung Cancer Screening (NELSON) study recently reported a 24% reduction when comparing LDCT to no screening. Therefore, the focus has now shifted to implementation research. Consequently, the 4-IN-THE-LUNG-RUN consortium, based in five European countries, has established a large-scale multicentre implementation study. Successful implementation of and access to LDCT lung cancer screening depend on many factors, including population selection, recruitment strategies, frequency of CT screening, management of lung nodules, participant compliance, and cost-effectiveness. This review provides an overview of the current evidence for LDCT lung cancer screening and highlights key factors that need to be addressed to successfully implement standardized, effective, and accessible screening across Europe. Evidence shows that by the appropriate use of risk prediction models and a more personalized approach to screening, effectiveness can be improved. Furthermore, extending the screening interval for low-risk individuals to reduce costs and associated harm is a possibility, and by using volumetric measurements and follow-up, false-positive results can be significantly reduced. Finally, smoking cessation programs could be a valuable addition to screening programs, and artificial intelligence could provide a solution to the additional workload faced by radiologists.

Lancaster HL, Jiang B, Davies MPA, Gratama JWC, Silva M, Yi J, et al. Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction. Eur J Cancer. 2025;220:115324.

Objective: Artificial intelligence (AI) could reduce the workload of reading computed tomography (CT) in lung cancer screening if used as the primary reader by excluding negative CT scans at baseline. There is a lack of evidence to support the performance of AI compared to the gold standard lung cancer outcomes. This study validated the performance of commercially available AI software in the UK lung cancer screening (UKLS) trial dataset, comparing it to human assessments and histological lung cancer outcomes, and estimated the reduction in workload for reading CT scans.  

Methods: 1252 UKLS baseline CT scans were independently evaluated by AI and human reviewers. The performance of AI was assessed at two levels. First, the AI classification and individual assessments were compared to a EU reference standard (based on NELSON2.0 European Position Statement) determined by a European expert group who were blind to the individual results. A positive misclassification was defined as a nodule positive assessment ≥ 100mm3 and no/<100mm3 nodules in the expert assessment; a negative misclassification was defined as a nodule negative assessment while there was an indeterminate or positive finding in the expert assessment. Second, the AI nodule classification was compared to the gold standard histological lung cancer outcomes. The reduction in workload for reading CT scans was calculated based on AI negative CT scans when AI was used as the primary reader.  

Results: The reference standard of the expert group reported 815 (65%) negative and 437 (35%) indeterminate/positive CT scans in the dataset of 1252 UKLS participants. Compared to the reference standard, AI resulted in fewer misclassifications than human assessments, NPV 92.0% (90.2%-95.3%). When compared to the gold standard, AI detected all 31 lung cancers in the baseline round but classified one as negative due to the 100mm3 threshold, NPV 99.8% (99.0%-99.9%). The estimated maximum reduction in workload for reading CT scans was 79%.  

Conclusion: The implementation of AI as the primary reader to exclude negative CT scans shows significant potential to reduce the workload for reading CT scans and does not result in missed lung cancers.

Lancaster HL, Walstra ANH, Myers K, Avila RS, Gratama JWC, Heuvelmans MA, et al. Action plan for an international imaging framework for implementation of global low-dose CT screening for lung cancer. Eur J Cancer. 2025;220:115323.

Reduction of mortality from lung cancer is achievable through low-dose computed tomography (LDCT) screening in high-risk individuals. Many countries are transitioning from local LDCT screening studies to national screening programs. The implementation of effective large-scale screening programs is complex and requires a multidisciplinary approach. A recent overview of the technical aspects of implementing high-quality LDCT for screening has emerged from the inaugural international expert meeting of the Alliance for Global Implementation of Lung and Cardiac Early Disease Detection and Treatment (AGILE). This addresses the key aspects of the CT imaging process: standardization in CT image acquisition and interpretation, management of CT protocols, technological developments and minimum requirements, integration of lung cancer biomarkers, and the role of AI in the detection, segmentation, and classification of CT lung nodules, as well as related data security issues.

Vonder M, van der Aalst C, Hubert J, Moldovanu D, Schmitz A, Delorme S, et al. MA19.06 Artificial Intelligence as Concurrent Reader in Prospective European Lung Cancer Screening (4-IN-THE-LUNG-RUN) Trial. Journal of Thoracic Oncology. 2023;18(11):S172.

Introduction: In the recently initiated European 4-IN-THE-LUNG-RUN (4ITLR) study, participants are screened for lung cancer and randomized for annual or semi-annual screening. Conventionally, low-dose thoracic CT (LDCT) scans in lung cancer screening are assessed by two independent human readers. With the rapidly increasing number of LDCTs for lung cancer screening and emerging robust AI software for the detection and classification of lung nodules, the workload for human readers could be reduced. The aim of the current study was to prospectively evaluate the feasibility and potential of fully integrated AI as a simultaneous (second) reader in lung cancer screening.  

Methods: In the 4ITLR study, individuals had to meet the following inclusion criteria: age 60-79 years, ≥35 pack-years; current smoker or <10 years since cessation. The first 380 participants were included and screened with a single low-dose thoracic scan on a third-generation dual-source CT. The thoracic CT scan was evaluated for the presence of lung nodules ≥30 mm3, and the participants were categorized based on the nodule findings into the groups 'negative', 'indeterminate', or 'positive'. Clinical management for each category was as follows: 1) negative: next screening round, 2) indeterminate: follow-up scan after 3 months, and 3) positive: referral to a specialist. Details of each nodule were recorded in a data management system (DMS) by experienced radiologists as a first independent reading. A second independent reading was automatically performed by AI-based Lung Screen Software (AVIEW, Coreline Soft, Seoul), and details were automatically recorded in the DMS. For participants with a discrepancy in categorization between the first and second readings, a third unblinded arbitration reading was conducted by a panel (experienced radiologists, technical physician), and the final findings were recorded in the DMS.  

Results: The average age was 68.2 (SD: 5.0) and 57.1% were male. The overall agreement for the categorization of nodules was 78.7% between the first and second readings. In total, 81 cases required a (third) arbitration reading. Of the arbitration cases, 45% were classified in the same category as determined by the first radiologist reading, and 34% were classified in the same category as determined by the AI reading. The remaining 21% were classified in a different category than that assigned by the radiologist or AI. Ultimately, 72.1%, 23.4%, and 4.5% of participants were categorized as 'negative', 'indeterminate', and 'positive', respectively. The final figures will be presented in September 2023.  

Conclusion: The current study demonstrates that it is feasible to integrate AI as a simultaneous reader in a prospective lung cancer screening study, eliminating the need for a second human reader, resulting in an arbitration reading in only 1 out of 5 cases. Less than 5% of participants undergoing a single baseline CT scan are referred to a specialist. In future research, including follow-up details, we will evaluate the diagnostic performance of the current reading strategy.

Walstra ANH, Lancaster HL, Heuvelmans MA, van der Aalst CM, Hubert J, Moldovanu D, et al. Feasibility of AI as first reader in the 4-IN-THE-LUNG-RUN lung cancer screening trial: impact on negative-misclassifications and clinical referral rate. Eur J Cancer. 2025;216:115214.

Background: Lung cancer screening (LCS) with low-dose CT (LDCT) reduces lung cancer-related mortality in high-risk individuals. AI may potentially reduce the workload of radiologists as a first reader filter by excluding negative cases. The feasibility of AI as a first reader was evaluated in the European 4-IN-THE-LUNG-RUN (4ITLR) trial, comparing negative misclassifications (NMs) with those of radiologists and the impact on referral rates.  

Methods: NMs were collected from 3,678 baseline LDCTs from the 4ITLR dataset. LDCTs were independently read by radiologists and specialized AI software (AVIEW-LCS, v1.1.42.92, Coreline-Soft, Seoul, Korea). A case was marked as an NM when nodules >100 mm3 were present and either the radiologist or the AI provided a negative classification (only nodules 300 mm3), which required referral for clinical investigation. In total, there were 102 referrals (2.8%) at baseline.  

Results: Of the 3,678 baseline scans, 438 NMs (11.9%) were identified (age of individuals: 68 (IQR: 64–73) years, 241 men); 31 (0.8%) by AI and 407 (11.1%) by radiologists. Of the 31 AI-NMs, 3 were classified as positive and 28 as indeterminate. Of the 407 radiologist-NMs, 4 were classified as positive, and 403 as indeterminate, of which 8 were classified as positive after a follow-up CT of three months. Radiologists, as the first reader, would have led to 12/102 (11.8%) missed referrals, higher than the 3/102 (2.9%) from AI.  

Conclusion: This study demonstrated that AI performs better than radiologists with significantly fewer NMs and is therefore promising as a first reader in an LCS program at baseline, by independently excluding negative cases without significantly increasing the risk of missed clinical referrals.

Boeri M, Sabia F, Ledda RE, Balbi M, Suatoni P, Segale M, et al. Blood microRNA testing in participants with suspicious low-dose CT findings: follow-up of the BioMILD lung cancer screening trial. Lancet Reg Health Eur. 2024;46:101070.

Background: The proper management of suspicious radiological findings is crucial to optimize the effectiveness of low-dose computed tomography (LDCT) lung cancer screening trials. In the BioMILD study, we evaluated the utility of combining a plasma 24-microRNA signature classifier (MSC) and LDCT to define individual risk and personalize screening strategies. Here, we aim to assess the utility of repeated MSC testing during annual screening rounds in 1024 participants with suspicious LDCT findings.  

Methods: The primary outcome was the two-year lung cancer incidence in relation to MSC test results, reported as relative risk (RR) with a 95% confidence interval (CI). Lung cancer incidence and mortality were estimated using extended Cox models for time-dependent covariates, yielding the respective hazard ratios (HR). Clinicaltrials.gov ID: NCT02247453.  

Results: With a median follow-up of 8.5 years, the full study population included 1403 indeterminate LDCT (CTind) and 584 positive LDCT (CT+) results. An increase in lung cancer RR in MSC+ compared to MSC- participants was observed in both the CTind (RR: 2.5; 95% CI: 1.4–4.32) and the CT+ (RR: 2.6; 95% CI: 1.81–3.74) groups and was maintained when only stage I or operable tumors were considered. A negative predictive value of 98% in CTind/MSC− and a positive predictive value of 30% in CT+/MSC+ lesions were recorded. At a seven-year follow-up, MSC+ participants had a cumulative HR of 4.4 (95% CI: 3.0–6.4) for lung cancer incidence and 8.1 (95% CI: 2.7–24.5) for lung cancer mortality.  

Conclusion: Our study demonstrates that MSC can be reliably performed during LDCT screening rounds to enhance the accuracy of lung cancer risk and mortality prediction and supports its clinical utility in managing LDCT findings of uncertain malignancy.

Sozzi G, Sabia F, Rolli L, Segale M, Suatoni P, Zanghi A, et al. Upfront blood microRNA test in LDCT-reluctant individuals: insights from the biomild trial. J Exp Clin Cancer Res. 2025;44(1):168.

Background: Screening for lung cancer with low-dose computed tomography (LDCT) can reduce mortality rates among high-risk individuals, but many people with a heavy smoking history may be reluctant to undergo radiological examinations. A non-invasive blood test may help overcome this barrier. The BioMILD study evaluated the combination of a plasma microRNA signature classifier (MSC) and LDCT for personalized lung cancer screening in 4,119 individuals who smoke or have smoked. Based on the results of BioMILD, we aim to conduct a projection analysis to estimate the number of early lung cancers that could be detected if MSC were used as an initial screening tool for individuals who are hesitant to undergo LDCT. This model explores the potential of a biomarker-driven approach to address screening reluctance.  

Results: The analysis focuses on 3,139 volunteers who meet the NLST criteria. At baseline, 24.9% tested positive for MSC. In a two-year period, 63 cases of lung cancer were detected, with a significantly higher incidence among MSC-positive participants (4.1% vs. 1.1%, p < 0.001). A biomarker-driven approach, where only MSC-positive individuals undergo annual LDCT, was compared with standard LDCT screening for all participants. This strategy could identify 58.7% of lung cancers detected through standard screening, including 56.5% of early cases. A rough cost analysis estimated the cost per case for lung cancer detection at approximately €14,000 for the biomarker-driven strategy versus about €12,000 for standard screening.  

Conclusion: The blood test for MSC demonstrated reasonable sensitivity for lung cancer detection, even in early disease, with affordable costs. Such a non-invasive blood test strategy may contribute to improving the acceptance of lung cancer screening in the high-risk population.  

de Nijs K, Ten Haaf K, van der Aalst C, de Koning HJ. Projected effectiveness of lung cancer screening and concurrent smoking cessation support in the Netherlands. EClinicalMedicine. 2024;71:102570.

Background: The NELSON study demonstrated a 24% reduction in lung cancer mortality through regular screening with low-dose computed tomography. Implementation efforts in Europe are underway, but still await country-specific and NELSON-adjusted estimates of the benefits and drawbacks of screening.  

Methods: We use the MISCAN-Lung microsimulation model, calibrated to individual outcomes from the NELSON study, to estimate the effectiveness under 100% adherence to biennial lung cancer screening with simultaneous smoking cessation support for Dutch cohorts born between 1942 and 1961. The model simulates smoking behaviour, lung cancer incidence, and the effects of screening and smoking cessation on lung and other causes of mortality.  

Results: We find that biennial screening with eligibility criteria equivalent to those of the 4-IN-THE-LUNG-RUN implementation study reduces lung cancer mortality by 16.9% among the eligible population, which translates to 1,076 lung cancer deaths per year that could be prevented over the next two decades. Eligible individuals account for 21.5% of the studied cohorts and represent 61% of the projected lung cancer mortality burden in the absence of screening. 10.3 life years are gained per prevented lung cancer death, with 14.9 screens per life year gained. Concurrent smoking cessation interventions could increase the expected gain in life years from screening by up to 20%.  

Conclusion: Policymakers should immediately consider the implementation of lung cancer screening in Europe, coupled with effective smoking cessation interventions. Smoking cessation interventions alone are not estimated to yield a gain in remaining life expectancy of the magnitude provided even by a single CT screening.

Moldovanu D, de Koning HJ, van der Aalst CM. Lung cancer screening and smoking cessation efforts. Transl Lung Cancer Res. 2021;10(2):1099-109.

Randomized controlled trials have confirmed significant reductions in lung cancer mortality with screenings using low-dose computed tomography (LDCT). However, evidence on how to integrate smoking cessation support into lung cancer screening is scarce. This represents a significant gap in the literature, as a combined strategy of lung cancer screening and smoking cessation substantially reduces the mortality risk from lung cancer and other related comorbidities. In this review, a literature search was conducted in MEDLINE, Embase, Web of Science, the Cochrane Central Register of Controlled Trials, and Google Scholar to identify randomized controlled and observational studies examining the effect of lung cancer screening trials and integrated cessation interventions on smoking cessation. Of the 236 identified records, we included 32 original publications. The quit rates among participants in lung cancer screening trials are promising. In particular, findings that are suspicious for lung cancer and referral to a physician can serve as a teachable moment to discourage smoking among current smokers or recent quitters. Intensive, personalized, and multimodal cessation interventions offered by a healthcare provider appear to be most successful in influencing smoking behaviour. Although it is clear that smoking cessation must be integrated into lung cancer screening, further research is needed to establish the optimal type of treatment, modality, timing, and content of communication, including the integration of CT results to motivate health behaviour change.

Vonder M, van der Aalst C, Moldovanu D, Hubert J, Schmitz A, Gratama J, et al. Cardiovascular Screening In Lung Cancer Screening: The European Prospective Approach 4-in-the-lung-run. Journal of Cardiovascular Computed Tomography. 2023;17(4):S46.

Introduction: The recently initiated European 4-IN-THE-LUNG-RUN study enables specific prospective cardiovascular screening within a lung cancer screening program, aiming to include 26,000 participants. Current guidelines recommend the evaluation of coronary calcifications on (any type of) chest CT. Nevertheless, a reliable assessment of the Agatston score requires specific imaging and reconstruction. The aim of the current study was to preliminarily evaluate the potential for specific cardiovascular screening within lung cancer screening among the first 4ITLR participants.  

Methods: Individuals had to meet the following inclusion criteria: age 60-79 years, ≥35 pack-years; current smoker or <10 years since quitting. The first 319 participants were included and screened with a single low-dose chest CT with high temporal resolution using third-generation dual-source CT. So far, participants have been screened between January 15 and March 10, 2023, at a single centre. The expected number of inclusions will be >1000 by July 2023 (multi-centre). Based on the single scan, evaluations for lung nodules and coronary calcifications were performed. For the current study, automatic evaluation of the Agatston score (previously validated and published) was conducted on specific cardiac reconstructions: 120 kVp, FBP, slice thickness/increment of 3.0/1.5, medium-sharp kernel, and high-pitch. This allowed for a reliable assessment of 0-score and risk categorization. Risk was categorized as follows: low, moderate, high, and very high risk for Agatston scores of 0, 1-99, 100-399, and >=400, respectively.  

Results: Of all participants, 16.3% had low risk, 30.1% had moderate risk, 19.1% had high risk, and 34.9% had very high risk. Approximately 46% of participants have a low/moderate risk of cardiovascular disease.  

Conclusions: 1 in 3 participants in lung cancer screening had a very high risk for cardiovascular disease. Half of the lung cancer screening population are candidates for preventive treatment for cardiovascular disease. Notably, more than 16% have a low risk of cardiovascular disease, and preventive cardiovascular medication is not indicated for these individuals according to current guidelines.

Vonder M, Van der Aalst C, Hubert J, Moldovanu D, Schmitz A, Gratama JWC, et al. P1.15-03 Dedicated Cardiovascular Screening in Lung Cancer Screening: Preliminary Results from the European 4-IN-THE-LUNG-RUN Trial. Journal of Thoracic Oncology. 2023;18(11):S218-S9.

Introduction: The 4-IN-THE-LUNG-RUN (4ITLR) study, which recently commenced and aims to recruit 26,000 participants, provides the opportunity for prospective cardiovascular screening within a lung cancer screening program. Although current guidelines advise assessing coronary calcifications on chest CT scans of any kind, this specific imaging requires acquisition and reconstruction techniques for accurate evaluation of the Agatston score. This study aims to conduct a preliminary evaluation of the potential benefits of dedicated cardiovascular screening in the first group of 4ITLR participants.  

Methods: The study included individuals who met the following criteria: age between 60-79 years, a smoking history of 35 pack-years or more, currently smoking or having quit within the last 10 years. The initial group of 443 participants was selected and underwent a single low-dose chest CT acquisition, which was performed with high temporal resolution using a third-generation dual-source CT scanner. This screening took place between January 15 and March 29, 2023, at a single centre, and the expected number of participants to be enrolled will exceed 1,000 by September 2023 across multiple centres. During the screening, participants were evaluated for the presence of lung nodules and coronary calcifications. For this study, an automated assessment of the Agatston score was performed on dedicated cardiac reconstructions that utilized a slice thickness/increment of 3.0/1.5 mm, a medium-sharp kernel, and high pitch acquisition, with an FBP algorithm and 120 kVp. This allowed for reliable categorization of participants' risk based on their Agatston score, with categories such as low risk (0 score), moderate risk (1-99), high risk (100-399), and very high risk (≥400).  

Results: The average age was 68.6 years (SD 4.9) and 56.9% were male. The median Agatston score for men was 242.1 (IQR 34.8-939.9) and for women 56.3 (IQR 2.5-365.0). Of all participants, 16.0%, 30.7%, 19.6%, and 33.6% were at low, moderate, high, and very high risk, respectively. Approximately 47% of participants have a low/moderate risk of coronary heart disease. The final figures will be presented in September 2023.  

Conclusions: The current lung cancer screening demonstrated that one-third of participants had a significantly high risk of coronary heart disease, while half of the population were suitable candidates for preventive treatment of coronary heart disease. Notably, 16% of individuals were found to have a low risk of coronary heart disease, and based on existing guidelines, they do not require preventive medication for coronary heart disease.

Walstra ANH, Gratama JWC, Heuvelmans MA, Oudkerk M. Early detection of cardiovascular disease in chest population screening: challenges for a rapidly emerging cardiac CT application. Br J Radiol. 2025;98(1175):1912-22.

Although lung cancer screening (LCS) reduces lung cancer-related mortality in high-risk individuals, cardiovascular disease (CVD) remains a significant cause of death due to shared risk factors such as smoking and age. The assessment of coronary artery calcium (CAC) provides an opportunity for simultaneous cardiovascular screening, with higher CAC scores indicating increased CVD risk and mortality. Despite guidelines recommending CAC scoring for all non-contrast chest CT scans, a lack of standardization leads to underreporting and missed opportunities for preventive care. Routine CAC scoring in LCS could enable personalized CVD management and reduce unnecessary treatments. However, challenges remain in achieving adequate diagnostic quality with a single combined imaging acquisition for both lung and cardiovascular assessment. Advances in CT technology have improved CAC quantification on low-dose CT scans. Electron beam tomography, valued for its superior temporal resolution, has been replaced by multi-detector CT for better spatial resolution and overall usability. Dual-source CT further improved temporal resolution and reduced motion artifacts, enabling non-gated CT protocols for CAC assessment. Additionally, AI-based CAC quantification may reduce the extra workload of cardiovascular screening within LCS programs. This review explores recent advancements in cardiac CT technologies that address previous challenges in opportunistic CVD screening and considers key factors for integrating CVD screening into LCS programs, aiming for high-quality standardization in CAC reporting.

Walstra AZ, S., Togka K, van der Aalst C, de Koning H, Oudkerk M. Annual Progression of Coronary Artery Calcium Agatston Score in The 4-IN-THE-LUNG-RUN Lung Cancer Screening Trial. Journal of Cardiovascular Computed Tomography. 2025;19(1):S31.

Introduction: Coronary Artery Calcium (CAC) Agatston score, as measured by cardiac CT, is currently integrated in several guidelines to establish cardiovascular risk of ischemic heart disease, with greater CAC progression associated with greater risk of coronary heart disease events. No progression was found in CAC score after three-month follow-up in the European 4-IN-THE-LUNG-RUN (4ITLR) lung cancer screening trial, with optimized one-run non-ECG triggered dual-source CT acquisition protocols. It was investigated if progression of CAC Agatston scores could be shown after a time-interval of one year in this high-risk population of a lung cancer screening trial.

Methods: High-pitch acquisition (3.0 pitch), ultra-low-dose chest CT scans (< 1.5 mSv) were performed in 1241 participants at baseline and annual time-interval, approximately 377 ± 8 days apart, from January 2023 to September 2024. Fully automated AI assessment of the Agatston score was performed on dedicated cardiac reconstructions with a slice thickness/increment of 3.0/1.5 mm, a medium-sharp kernel, with a FBP algorithm at 120 kVp. Wilcoxon signed-rank test was conducted to evaluate the difference in total calcification scores between the two time points. Participants were stratified by Agatston score into risk categories (0-99, 100-399, ≥400), followed by Quadratic Cohen’s Weighted Kappa analysis to evaluate inter-scan agreement.

Results: The mean age was 67 ± 5 years with 57.2% male. Significant progression (p<0.001, z = -14.8) in CAC Agatston scores was found between baseline (118.0, IQR 7.8-546.3) and annual follow-up (154.6, IQR 11.6-595.2). Among the participants, 1147 (92.4%) showed no difference between the two time points, while 93 (7.5%) had one class-level difference, 1 (0.1%) had two class-level difference. Progression from low to intermediate risk was seen in 45 (3.6%) participants and from intermediate to high risk in 25 (2.0%) participants. An overall upwards classification shift was observed in 71 (5.7%) participants. Regression in risk category from intermediate to low risk was seen in 10 (0.8%) participants and from high to intermediate risk in 13 (1.0%) participants. Inter-scan agreement was robust (k=0.95, 95%CI: 0.94-0.96).

Conclusions: Progression in the mean CAC Agatston score was observed after a one-year interval in the 4ITLR lung cancer screening population.

Callender T, Payne K, Pashayan N, Mackie A. Screening for multiple cancers: evaluation must go beyond aggregate measures. BMJ. 2025;388:e081098.

In this article, the authors advocate that when assessing screening programs that detect multiple types of cancer simultaneously (for example, through blood tests that can screen for many types of cancer at once), we should not only look at one summary measure. Simple 'total figures' for all cancer types combined can conceal important differences between the individual cancer types, such as how well a test works for each type, what the risks are, and what the impact is on people and policy.  
The main points are:  

• Differences between cancer types are crucial: Each type of cancer has its own progression and responds differently to screening. Total figures (such as the total number of detections) do not provide a good representation of this.  
• Evaluation needs to be more detailed: Test results should be analysed by cancer type and by clinically relevant outcomes (such as how many early cases are found and what the consequences are).  
• Policy decisions and clinical value: By focusing on aggregated results, decisions regarding the implementation of such screening tests can be misleading. There must be clear insight into the benefits, limitations, and potential drawbacks of screening by cancer type.  

Conclusion: The authors emphasize that a more detailed and nuanced evaluation is needed to understand whether screening strategies that detect multiple cancers simultaneously are truly beneficial for patients and healthcare systems.