Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial.

BACKGROUND: There are limited data from randomized trials regarding whether volume-based, low-dose computed tomographic (CT) screening can reduce lung-cancer mortality among male former and current smokers. METHODS: A total of 13,195 men (primary analysis) and 2594 women (subgroup analyses) between the ages of 50 and 74 were randomly assigned to undergo CT screening at T0 (baseline), year 1, year 3, and year 5.5 or no screening. We obtained data on cancer diagnosis and the date and cause of death through linkages with national registries in the Netherlands and Belgium, and a review committee confirmed lung cancer as the cause of death when possible. A minimum follow-up of 10 years until December 31, 2015, was completed for all participants. RESULTS: Among men, the average adherence to CT screening was 90.0%. On average, 9.2% of the screened participants underwent at least one additional CT scan (initially indeterminate). The overall referral rate for suspicious nodules was 2.1%. At 10 years of follow-up, the incidence of lung cancer was 5.58 cases per 1000 person-years in the screening group and 4.91 cases per 1000 person-years in the control group; lung-cancer mortality was 2.50 deaths per 1000 person-years and 3.30 deaths per 1000 person-years, respectively. The cumulative rate ratio for death from lung cancer at 10 years was 0.76 (95% confidence interval [CI], 0.61 to 0.94; P = 0.01) in the screening group as compared with the control group, similar to the values at years 8 and 9. Among women, the rate ratio was 0.67 (95% CI, 0.38 to 1.14) at 10 years of follow-up, with values of 0.41 to 0.52 in years 7 through 9. CONCLUSIONS: In this trial involving high-risk persons, lung-cancer mortality was significantly lower among those who underwent volume CT screening than among those who underwent no screening. There were low rates of follow-up procedures for results suggestive of lung cancer. (Funded by the Netherlands Organization of Health Research and Development and others; NELSON Netherlands Trial Register number, NL580.).

Early detection of obstructive coronary artery disease in the asymptomatic high-risk population: objectives and study design of the EARLY-SYNERGY trial.

BACKGROUND: Coronary artery disease (CAD) burden for society is expected to steeply increase over the next decade. Improved feasibility and efficiency of preventive strategies is necessary to flatten the curve. Acute myocardial infarction (AMI) is the main determinant of CAD-related mortality and morbidity, and predominantly occurs in individuals with more advanced stages of CAD causing subclinical myocardial ischemia (obstructive CAD; OCAD). Unfortunately, OCAD can remain subclinical until its destructive presentation with AMI or sudden death. Current primary preventive strategies are not designed to differentiate between non-OCAD and OCAD and the opportunity is missed to treat individuals with OCAD more aggressively. METHODS: EARLY-SYNERGY is a multicenter, randomized-controlled clinical trial in individuals with coronary artery calcium (CAC) presence to study (1.) the yield of cardiac magnetic resonance stress myocardial perfusion imaging (CMR-MPI) for early OCAD diagnosis and (2) whether early OCAD diagnosis improves outcomes. Individuals with CAC score ≥300 objectified in 2 population-based trials (ROBINSCA; ImaLife) are recruited for study participation. Eligible candidates are randomized 1:1 to cardiac magnetic resonance stress myocardial perfusion imaging (CMR-MPI) or no additional functional imaging. In the CMR-MPI arm, feedback on imaging results is provided to primary care provider and participant in case of guideline-based actionable findings. Participants are followed-up for clinical events, healthcare utilization and quality of life. CONCLUSIONS: EARLY-SYNERGY is the first randomized-controlled clinical trial designed to test the hypothesis that subclinical OCAD is widely present in the general at-risk population and that early differentiation of OCAD from non-OCAD followed by guideline-recommended treatment improves outcomes.

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

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

Persisting new nodules in incidence rounds of the NELSON CT lung cancer screening study.

BACKGROUND: The US guidelines recommend low-dose CT (LDCT) lung cancer screening for high-risk individuals. New solid nodules after baseline screening are common and have a high lung cancer probability. Currently, no evidence exists concerning the risk stratification of non-resolving new solid nodules at first LDCT screening after initial detection. METHODS: In the Dutch-Belgian Randomized Lung Cancer Screening (NELSON) trial, 7295 participants underwent the second and 6922 participants the third screening round. We included participants with solid nodules that were registered as new or <15 mm³ (study detection limit) at previous screens and received additional screening after initial detection, thereby excluding high-risk nodules according to the NELSON management protocol (nodules ≥500 mm3). RESULTS: Overall, 680 participants with 1020 low-risk and intermediate-risk new solid nodules were included. A total of 562 (55%) new solid nodules were resolving, leaving 356 (52%) participants with a non-resolving new solid nodule, of whom 25 (7%) were diagnosed with lung cancer. At first screening after initial detection, volume doubling time (VDT), volume, and VDT combined with a predefined ≥200 mm3 volume cut-off had high discrimination for lung cancer (VDT, area under the curve (AUC): 0.913; volume, AUC: 0.875; VDT and ≥200 mm3 combination, AUC: 0.939). Classifying a new solid nodule with either ≤590 days VDT or ≥200 mm3 volume positive provided 100% sensitivity, 84% specificity and 27% positive predictive value for lung cancer. CONCLUSIONS: More than half of new low-risk and intermediate-risk solid nodules in LDCT lung cancer screening resolve. At follow-up, growth assessment potentially combined with a volume limit can be used for risk stratification. TRIAL REGISTRATION NUMBER: ISRCTN63545820; pre-results.

Performance and Cost-Effectiveness of Computed Tomography Lung Cancer Screening Scenarios in a Population-Based Setting: A Microsimulation Modeling Analysis in Ontario, Canada.

BACKGROUND: The National Lung Screening Trial (NLST) results indicate that computed tomography (CT) lung cancer screening for current and former smokers with three annual screens can be cost-effective in a trial setting. However, the cost-effectiveness in a population-based setting with >3 screening rounds is uncertain. Therefore, the objective of this study was to estimate the cost-effectiveness of lung cancer screening in a population-based setting in Ontario, Canada, and evaluate the effects of screening eligibility criteria. METHODS AND FINDINGS: This study used microsimulation modeling informed by various data sources, including the Ontario Health Insurance Plan (OHIP), Ontario Cancer Registry, smoking behavior surveys, and the NLST. Persons, born between 1940 and 1969, were examined from a third-party health care payer perspective across a lifetime horizon. Starting in 2015, 576 CT screening scenarios were examined, varying by age to start and end screening, smoking eligibility criteria, and screening interval. Among the examined outcome measures were lung cancer deaths averted, life-years gained, percentage ever screened, costs (in 2015 Canadian dollars), and overdiagnosis. The results of the base-case analysis indicated that annual screening was more cost-effective than biennial screening. Scenarios with eligibility criteria that required as few as 20 pack-years were dominated by scenarios that required higher numbers of accumulated pack-years. In general, scenarios that applied stringent smoking eligibility criteria (i.e., requiring higher levels of accumulated smoking exposure) were more cost-effective than scenarios with less stringent smoking eligibility criteria, with modest differences in life-years gained. Annual screening between ages 55-75 for persons who smoked ≥40 pack-years and who currently smoke or quit ≤10 y ago yielded an incremental cost-effectiveness ratio of $41,136 Canadian dollars ($33,825 in May 1, 2015, United States dollars) per life-year gained (compared to annual screening between ages 60-75 for persons who smoked ≥40 pack-years and who currently smoke or quit ≤10 y ago), which was considered optimal at a cost-effectiveness threshold of $50,000 Canadian dollars ($41,114 May 1, 2015, US dollars). If 50% lower or higher attributable costs were assumed, the incremental cost-effectiveness ratio of this scenario was estimated to be $38,240 ($31,444 May 1, 2015, US dollars) or $48,525 ($39,901 May 1, 2015, US dollars), respectively. If 50% lower or higher costs for CT examinations were assumed, the incremental cost-effectiveness ratio of this scenario was estimated to be $28,630 ($23,542 May 1, 2015, US dollars) or $73,507 ($60,443 May 1, 2015, US dollars), respectively. This scenario would screen 9.56% (499,261 individuals) of the total population (ever- and never-smokers) at least once, which would require 4,788,523 CT examinations, and reduce lung cancer mortality in the total population by 9.05% (preventing 13,108 lung cancer deaths), while 12.53% of screen-detected cancers would be overdiagnosed (4,282 overdiagnosed cases). Sensitivity analyses indicated that the overall results were most sensitive to variations in CT examination costs. Quality of life was not incorporated in the analyses, and assumptions for follow-up procedures were based on data from the NLST, which may not be generalizable to a population-based setting. CONCLUSIONS: Lung cancer screening with stringent smoking eligibility criteria can be cost-effective in a population-based setting.

Final screening round of the NELSON lung cancer screening trial: the effect of a 2.5-year screening interval.

BACKGROUND: In the USA annual lung cancer screening is recommended. However, the optimal screening strategy (eg, screening interval, screening rounds) is unknown. This study provides results of the fourth screening round after a 2.5-year interval in the Dutch-Belgian Lung Cancer Screening trial (NELSON). METHODS: Europe's largest, sufficiently powered randomised lung cancer screening trial was designed to determine whether low-dose CT screening reduces lung cancer mortality by ≥25% compared with no screening after 10 years of follow-up. The screening arm (n=7915) received screening at baseline, after 1 year, 2 years and 2.5 years. Performance of the NELSON screening strategy in the final fourth round was evaluated. Comparisons were made between lung cancers detected in the first three rounds, in the final round and during the 2.5-year interval. RESULTS: In round 4, 46 cancers were screen-detected and there were 28 interval cancers between the third and fourth screenings. Compared with the second round screening (1-year interval), in round 4 a higher proportion of stage IIIb/IV cancers (17.3% vs 6.8%, p=0.02) and higher proportions of squamous-cell, bronchoalveolar and small-cell carcinomas (p=0.001) were detected. Compared with a 2-year interval, the 2.5-year interval showed a higher non-significant stage distribution (stage IIIb/IV 17.3% vs 5.2%, p=0.10). Additionally, more interval cancers manifested in the 2.5-year interval than in the intervals of previous rounds (28 vs 5 and 28 vs 19). CONCLUSIONS: A 2.5-year interval reduced the effect of screening: the interval cancer rate was higher compared with the 1-year and 2-year intervals, and proportion of advanced disease stage in the final round was higher compared with the previous rounds. TRIAL REGISTRATION NUMBER: ISRCTN63545820.

Risk stratification based on screening history: the NELSON lung cancer screening study.

BACKGROUND: Debate about the optimal lung cancer screening strategy is ongoing. In this study, previous screening history of the Dutch-Belgian Lung Cancer Screening trial (NELSON) is investigated on if it predicts the screening outcome (test result and lung cancer risk) of the final screening round. METHODS: 15 792 participants were randomised (1:1) of which 7900 randomised into a screening group. CT screening took place at baseline, and after 1, 2 and 2.5 years. Initially, three screening outcomes were possible: negative, indeterminate or positive scan result. Probability for screening outcome in the fourth round was calculated for subgroups of participants. RESULTS: Based on results of the first three rounds, three subgroups were identified: (1) those with exclusively negative results (n=3856; 73.0%); (2) those with ≥1 indeterminate result, but never a positive result (n=1342; 25.5%); and (3) with ≥1 positive result (n=81; 1.5%). Group 1 had the highest probability for having a negative scan result in round 4 (97.2% vs 94.8% and 90.1%, respectively, p<0.001), and the lowest risk for detecting lung cancer in round 4 (0.6% vs 1.6%, p=0.001). 'Smoked pack-years' and 'screening history' significantly predicted the fourth round test result. The third round results implied that the risk for detecting lung cancer (after an interval of 2.5 years) was 0.6% for those with negative results compared with 3.7% of those with indeterminate results. CONCLUSIONS: Previous CT lung cancer screening results provides an opportunity for further risk stratifications of those who undergo lung cancer screening. TRIAL REGISTRATION NUMBER: Results, ISRCTN63545820.

Occurrence and lung cancer probability of new solid nodules at incidence screening with low-dose CT: analysis of data from the randomised, controlled NELSON trial.

BACKGROUND: US guidelines now recommend lung cancer screening with low-dose CT for high-risk individuals. Reports of new nodules after baseline screening have been scarce and are inconsistent because of differences in definitions used. We aimed to identify the occurrence of new solid nodules and their probability of being lung cancer at incidence screening rounds in the Dutch-Belgian Randomized Lung Cancer Screening Trial (NELSON). METHODS: In the ongoing, multicentre, randomised controlled NELSON trial, between Dec 23, 2003, and July 6, 2006, 15 822 participants who had smoked at least 15 cigarettes a day for more than 25 years or ten cigarettes a day for more than 30 years and were current smokers, or had quit smoking less than 10 years ago, were enrolled and randomly assigned to receive either screening with low-dose CT (n=7915) or no screening (n=7907). From Jan 28, 2004, to Dec 18, 2006, 7557 individuals underwent baseline screening with low-dose CT; 7295 participants underwent second and third screening rounds. We included all participants with solid non-calcified nodules, registered by the NELSON radiologists as new or smaller than 15 mm(3) (study detection limit) at previous screens. Nodule volume was generated semiautomatically by software. We calculated the maximum volume doubling time for nodules with an estimated percentage volume change of 25% or more, representing the minimum growth rate for the time since the previous scan. Lung cancer diagnosis was based on histology, and benignity was based on histology or stable size for at least 2 years. The NELSON trial is registered at trialregister.nl, number ISRCTN63545820. FINDINGS: We analysed data for participants with at least one solid non-calcified nodule at the second or third screening round. In the two incidence screening rounds, the NELSON radiologists registered 1222 new solid nodules in 787 (11%) participants. A new solid nodule was lung cancer in 49 (6%) participants with new solid nodules and, in total, 50 lung cancers were found, representing 4% of all new solid nodules. 34 (68%) lung cancers were diagnosed at stage I. Nodule volume had a high discriminatory power (area under the receiver operating curve 0·795 [95% CI 0·728-0·862]; p<0·0001). Nodules smaller than 27 mm(3) had a low probability of lung cancer (two [0·5%] of 417 nodules; lung cancer probability 0·5% [95% CI 0·0-1·9]), nodules with a volume of 27 mm(3) up to 206 mm(3) had an intermediate probability (17 [3·1%] of 542 nodules; lung cancer probability 3·1% [1·9-5·0]), and nodules of 206 mm(3) or greater had a high probability (29 [16·9%] of 172 nodules; lung cancer probability 16·9% [12·0-23·2]). A volume cutoff value of 27 mm(3) or greater had more than 95% sensitivity for lung cancer. INTERPRETATION: Our study shows that new solid nodules are detected at each screening round in 5-7% of individuals who undergo screening for lung cancer with low-dose CT. These new nodules have a high probability of malignancy even at a small size. These findings should be considered in future screening guidelines, and new solid nodules should be followed up more aggressively than nodules detected at baseline screening. FUNDING: Zorgonderzoek Nederland Medische Wetenschappen and Koningin Wilhelmina Fonds Kankerbestrijding.

Airway wall thickness associated with forced expiratory volume in 1 second decline and development of airflow limitation.

Airway wall thickness and emphysema contribute to airflow limitation. We examined their association with lung function decline and development of airflow limitation in 2021 male smokers with and without airflow limitation. Airway wall thickness and emphysema were quantified on chest computed tomography and expressed as the square root of wall area of a 10-mm lumen perimeter (Pi10) and the 15th percentile method (Perc15), respectively. Baseline and follow-up (median (interquartile range) 3 (2.9-3.1) years) spirometry was available. Pi10 and Perc15 correlated with baseline forced expiratory volume in 1 s (FEV1) (r= -0.49 and 0.11, respectively (p<0.001)). Multiple linear regression showed that Pi10 and Perc15 at baseline were associated with a lower FEV1 after follow-up (p<0.05). For each sd increase in Pi10 and decrease in Perc15 the FEV1 decreased by 20 mL and 30.2 mL, respectively. The odds ratio for developing airflow limitation after 3 years was 2.45 for a 1-mm higher Pi10 and 1.46 for a 10-HU lower Perc15 (p<0.001). A greater degree of airway wall thickness and emphysema was associated with a higher FEV1 decline and development of airflow limitation after 3 years of follow-up.

Towards a close computed tomography monitoring approach for screen detected subsolid pulmonary nodules?

Pulmonary subsolid nodules (SSNs) have a high likelihood of malignancy, but are often indolent. A conservative treatment approach may therefore be suitable. The aim of the current study was to evaluate whether close follow-up of SSNs with computed tomography may be a safe approach. The study population consisted of participants of the Dutch-Belgian lung cancer screening trial (Nederlands Leuvens Longkanker Screenings Onderzoek; NELSON). All SSNs detected during the trial were included in this analysis. Retrospectively, all persistent SSNs and SSNs that were resected after first detection were segmented using dedicated software, and maximum diameter, volume and mass were measured. Mass doubling time (MDT) was calculated. In total 7135 volunteers were included in the current analysis. 264 (3.3%) SSNs in 234 participants were detected during the trial. 147 (63%) of these SSNs in 126 participants disappeared at follow-up, leaving 117 persistent or directly resected SSNs in 108 (1.5%) participants available for analysis. The median follow-up time was 95 months (range 20-110 months). 33 (28%) SSNs were resected and 28 of those were (pre-) invasive. None of the non-resected SSNs progressed into a clinically relevant malignancy. Persistent SSNs rarely developed into clinically manifest malignancies unexpectedly. Close follow-up with computed tomography may be a safe option to monitor changes.

Pulmonary function and CT biomarkers as risk factors for cardiovascular events in male lung cancer screening participants: the NELSON study.

OBJECTIVE: The objective of this study was to investigate the association of spirometry and pulmonary CT biomarkers with cardiovascular events. METHODS: In this lung cancer screening trial 3,080 male participants without a prior cardiovascular event were analysed. Fatal and non-fatal cardiovascular events were included. Spirometry included forced expiratory volume measured in units of one-second percent predicted (FEV1%predicted) and FEV1 divided by forced vital capacity (FVC; FEV1/FVC). CT examinations were quantified for coronary artery calcium volume, pulmonary emphysema (perc15) and bronchial wall thickness (pi10). Data were analysed via a Cox proportional hazard analysis, net reclassification improvement (NRI) and C-indices. RESULTS: 184 participants experienced a cardiovascular event during a median follow-up of 2.9 years. Age, pack-years and smoking status adjusted hazard ratios were 0.992 (95% confidence interval (CI) 0.985-0.999) for FEV1%predicted, 1.000 (95%CI 0.986-1.015) for FEV1/FVC, 1.014 (95%CI 1.005-1.023) for perc15 per 10 HU, and 1.269 (95%CI 1.024-1.573) for pi10 per 1 mm. The incremental C-index (<0.015) and NRI (<2.8%) were minimal. Coronary artery calcium volume had a hazard ratio of 1.046 (95%CI 1.034-1.058) per 100 mm(3), an increase in C-index of 0.076 and an NRI of 16.9% (P < 0.0001). CONCLUSIONS: Pulmonary CT biomarkers and spirometry measurements were significantly associated with cardiovascular events, but did not contain clinically relevant independent prognostic information for cardiovascular events. KEY POINTS: • Pulmonary CT biomarkers and spirometry are associated with cardiovascular events • These pulmonary measurements do not contain clinically relevant independent prognostic information • Only coronary calcium score improved cardiovascular risk prediction above age and smoking.

Detection of lung cancer through low-dose CT screening (NELSON): a prespecified analysis of screening test performance and interval cancers.

BACKGROUND: Low-dose CT screening is recommended for individuals at high risk of developing lung cancer. However, CT screening does not detect all lung cancers: some might be missed at screening, and others can develop in the interval between screens. The NELSON trial is a randomised trial to assess the effect of screening with increasing screening intervals on lung cancer mortality. In this prespecified analysis, we aimed to assess screening test performance, and the epidemiological, radiological, and clinical characteristics of interval cancers in NELSON trial participants assigned to the screening group. METHODS: Eligible participants in the NELSON trial were those aged 50-75 years, who had smoked 15 or more cigarettes per day for more than 25 years or ten or more cigarettes for more than 30 years, and were still smoking or had quit less than 10 years ago. We included all participants assigned to the screening group who had attended at least one round of screening. Screening test results were based on volumetry using a two-step approach. Initially, screening test results were classified as negative, indeterminate, or positive based on nodule presence and volume. Subsequently, participants with an initial indeterminate result underwent follow-up screening to classify their final screening test result as negative or positive, based on nodule volume doubling time. We obtained information about all lung cancer diagnoses made during the first three rounds of screening, plus an additional 2 years of follow-up from the national cancer registry. We determined epidemiological, radiological, participant, and tumour characteristics by reassessing medical files, screening CTs, and clinical CTs. The NELSON trial is registered at www.trialregister.nl, number ISRCTN63545820. FINDINGS: 15,822 participants were enrolled in the NELSON trial, of whom 7915 were assigned to low-dose CT screening with increasing interval between screens, and 7907 to no screening. We included 7155 participants in our study, with median follow-up of 8·16 years (IQR 7·56-8·56). 187 (3%) of 7155 screened participants were diagnosed with 196 screen-detected lung cancers, and another 34 (<1%; 19 [56%] in the first year after screening, and 15 [44%] in the second year after screening) were diagnosed with 35 interval cancers. For the three screening rounds combined, with a 2-year follow-up, sensitivity was 84·6% (95% CI 79·6-89·2), specificity was 98·6% (95% CI 98·5-98·8), positive predictive value was 40·4% (95% CI 35·9-44·7), and negative predictive value was 99·8% (95% CI 99·8-99·9). Retrospective assessment of the last screening CT and clinical CT in 34 patients with interval cancer showed that interval cancers were not visible in 12 (35%) cases. In the remaining cases, cancers were visible when retrospectively assessed, but were not diagnosed because of radiological detection and interpretation errors (17 [50%]), misclassification by the protocol (two [6%]), participant non-compliance (two [6%]), and non-adherence to protocol (one [3%]). Compared with screen-detected cancers, interval cancers were diagnosed at more advanced stages (29 [83%] of 35 interval cancers vs 44 [22%] of 196 screen-detected cancers diagnosed in stage III or IV; p<0·0001), were more often small-cell carcinomas (seven [20%] vs eight [4%]; p=0·003) and less often adenocarcinomas (nine [26%] vs 102 [52%]; p=0·005). INTERPRETATION: Lung cancer screening in the NELSON trial yielded high specificity and sensitivity, with only a small number of interval cancers. The results of this study could be used to improve screening algorithms, and reduce the number of missed cancers. FUNDING: Zorgonderzoek Nederland Medische Wetenschappen and Koningin Wilhelmina Fonds.

Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening.

BACKGROUND: The main challenge in CT screening for lung cancer is the high prevalence of pulmonary nodules and the relatively low incidence of lung cancer. Management protocols use thresholds for nodule size and growth rate to determine which nodules require additional diagnostic procedures, but these should be based on individuals' probabilities of developing lung cancer. In this prespecified analysis, using data from the NELSON CT screening trial, we aimed to quantify how nodule diameter, volume, and volume doubling time affect the probability of developing lung cancer within 2 years of a CT scan, and to propose and evaluate thresholds for management protocols. METHODS: Eligible participants in the NELSON trial were those aged 50-75 years, who have smoked 15 cigarettes or more per day for more than 25 years, or ten cigarettes or more for more than 30 years and were still smoking, or had stopped smoking less than 10 years ago. Participants were randomly assigned to low-dose CT screening at increasing intervals, or no screening. We included all participants assigned to the screening group who had attended at least one round of screening, and whose results were available from the national cancer registry database. We calculated lung cancer probabilities, stratified by nodule diameter, volume, and volume doubling time and did logistic regression analysis using diameter, volume, volume doubling time, and multinodularity as potential predictor variables. We assessed management strategies based on nodule threshold characteristics for specificity and sensitivity, and compared them to the American College of Chest Physicians (ACCP) guidelines. The NELSON trial is registered at www.trialregister.nl, number ISRCTN63545820. FINDINGS: Volume, volume doubling time, and volumetry-based diameter of 9681 non-calcified nodules detected by CT screening in 7155 participants in the screening group of NELSON were used to quantify lung cancer probability. Lung cancer probability was low in participants with a nodule volume of 100 mm(3) or smaller (0·6% [95% CI 0·4-0·8]) or maximum transverse diameter smaller than 5 mm (0·4% [0·2-0·7]), and not significantly different from participants without nodules (0·4% [0·3-0·6], p=0·17 and p=1·00, respectively). Lung cancer probability was intermediate (requiring follow-up CT) if nodules had a volume of 100-300 mm(3) (2·4% [95% CI 1·7-3·5]) or a diameter 5-10 mm (1·3% [1·0-1·8]). Volume doubling time further stratified the probabilities: 0·8% (95% CI 0·4-1·7) for volume doubling times 600 days or more, 4·0% (1·8-8·3) for volume doubling times 400-600 days, and 9·9% (6·9-14·1) for volume doubling times of 400 days or fewer. Lung cancer probability was high for participants with nodule volumes 300 mm(3) or bigger (16·9% [95% CI 14·1-20·0]) or diameters 10 mm or bigger (15·2% [12·7-18·1]). The simulated ACCP management protocol yielded a sensitivity and specificity of 90·9% (95% CI 81·2-96·1), and 87·2% (86·4-87·9), respectively. A diameter-based protocol with volumetry-based nodule diameter yielded a higher sensitivity (92·4% [95% CI 83·1-97·1]), and a higher specificity (90·0% [89·3-90·7). A volume-based protocol (with thresholds based on lung cancer probability) yielded the same sensitivity as the ACCP protocol (90·9% [95% CI 81·2-96·1]), and a higher specificity (94·9% [94·4-95·4]). INTERPRETATION: Small nodules (those with a volume <100 mm(3) or diameter <5 mm) are not predictive for lung cancer. Immediate diagnostic evaluation is necessary for large nodules (≥300 mm(3) or ≥10 mm). Volume doubling time assessment is advocated only for intermediate-sized nodules (with a volume ranging between 100-300 mm(3) or diameter of 5-10 mm). Nodule management protocols based on these thresholds performed better than the simulated ACCP nodule protocol. FUNDING: Zorgonderzoek Nederland Medische Wetenschappen and Koningin Wilhelmina Fonds.

Characteristics of lung cancers detected by computer tomography screening in the randomized NELSON trial.

RATIONALE: The NELSON (Nederlands Leuvens Longkanker Screenings Onderzoek) trial is, with 15,822 participants, the largest European lung cancer computer tomography screening trial. A volumetry-based screening strategy, stringent criteria for a positive screening, and an increasing length of screening interval are particular features of the NELSON trial. OBJECTIVES: To determine the effect of stringent referral criteria and increasing screening interval on the characteristics of screen-detected lung cancers, and to compare this across screening rounds, between sexes, and with other screening trials. METHODS: All NELSON participants with screen-detected lung cancer in the first three rounds were included. Lung cancer stage at diagnosis, histological subtype, and tumor localization were compared between the screening rounds, the sexes, and with other screening trials. MEASUREMENTS AND MAIN RESULTS: In the first three screening rounds, 200 participants were diagnosed with 209 lung cancers. Of these lung cancers, 70.8% were diagnosed at stage I and 8.1% at stage IIIB-IV, and 51.2% were adenocarcinomas. There was no significant difference in cancer stage, histology, or tumor localization across the screening rounds. Women were diagnosed at a significantly more favorable cancer stage than men. Compared with other trials, the screen-detected lung cancers of the NELSON trial were relatively more often diagnosed at stage I and less often at stage IIIB-IV. CONCLUSIONS: Despite stringent criteria for a positive screening, an increasing length of screening interval, and few female participants, the screening strategy of the NELSON trial resulted in a favorable cancer stage distribution at diagnosis, which is essential for the effectiveness of our screening strategy. Clinical trial registered with www.trialregister.nl (ISRCTN63545820).

Medical costs of lung cancer by stage, histology and first-line treatment modality in the Netherlands (2012-2021).

INTRODUCTION: Lung cancer is a leading cause of mortality worldwide, with lung cancer treatment presenting a significant financial burden. The treatment landscape has recently shifted, seeing an increase in targeted- and immunotherapies. Such treatments are expensive, but estimates of the medical costs of the lung cancer treatment pathway largely predate their introduction. METHODS: We link medical expenditures of individuals resident in the Netherlands (n = 19.2 m) for 2013-2021 to tumour-level (n = 137,129, incident 2012-2021) Netherlands Cancer Registry data. We estimate lung cancer-attributable costs by phase of care (initial, continuing and terminal), stratified by cancer stage and histology, and observe trends in medical costs over time. RESULTS: We estimate mean costs over the lung cancer treatment pathway to be €48,443 per patient. Total medical costs are highest in the initial phase, followed by the terminal and continuing phase. Monthly treatment for stage IV lung cancer is significantly more expensive than for early-stage disease (€8293 per month of initial care relative to €3228 for stage IA). Stage IV lung cancer has become significantly more expensive to treat 2018-2021 relative to 2013-2017, with monthly expenditures rising 55 % in initial care and 148 % in continuing care. Population-wide, we find €900.6 million spent on lung cancer care in 2021, €433 million more than in 2016, of which €307.3 million is attributed to per-patient expenditure trends. CONCLUSIONS: Treatment advances are quickly inflating medical costs for late-stage lung cancer. Policy makers should carefully evaluate the cost-effectiveness of novel treatments, and incorporate stage-specific treatment costs in evaluating interventions for early detection.

Projected effectiveness of lung cancer screening and concurrent smoking cessation support in the Netherlands.

Background: The NELSON trial demonstrated a 24% intention-to-screen reduction in lung cancer mortality from regular screening with low-dose computed tomography. Implementation efforts in Europe are ongoing, but still await country-specific and NELSON-adapted estimates of the benefits and harms of screening. Methods: We use the MISCAN-Lung microsimulation model, calibrated to individual-level outcomes from the NELSON trial, to estimate the effectiveness under 100% compliance of biennial lung cancer screening with concomitant smoking cessation support for Dutch cohorts 1942-1961. The model simulates smoking behaviour, lung cancer incidence and the effects of screening and smoking cessation on lung- and other-cause mortality. Findings: We find biennial screening with eligibility criteria equal to those of the 4-IN-THE-LUNG-RUN implementation trial to reduce lung cancer mortality by 16.9% among the eligible population, equivalent to 1076 LC deaths prevented per year in the next two decades. Eligible individuals constitute 21.5% of the cohorts studied, and stand to face 61% of the projected lung cancer mortality burden in the absence of screening. 10.3 life-years are gained per prevented LC death, for 14.9 screens per life year gained. Concomitant smoking cessation interventions may increase the expected gains in life years from screening by up to 20%. Interpretation: Policy makers should imminently consider the implementation of lung cancer screening in Europe, paired with effective smoking cessation interventions. Smoking cessation interventions on their own are not estimated to yield a gain in remaining life expectancy of the magnitude offered by even a single CT screen. Funding: European UnionHorizon 2020 grant 848294: 4-IN-THE-LUNG-RUN.

Volumetric computed tomography screening for lung cancer: three rounds of the NELSON trial.

Several medical associations recommended lung cancer screening by low-dose computed tomography scanning for high-risk groups. Counselling of the candidates on the potential harms and benefits and their lung cancer risk is a prerequisite for screening. In the NELSON trial, screenings are considered positive for (part) solid lung nodules with a volume >500 mm3 and for (part) solid or nonsolid nodules with a volume-doubling time <400 days. For this study, the performance of the NELSON strategy in three screening rounds was evaluated and risk calculations were made for a follow-up period of 5.5 years. 458 (6%) of the 7582 participants screened had a positive screen result and 200 (2.6%) were diagnosed with lung cancer. The positive screenings had a predictive value of 40.6% and only 1.2% of all scan results were false-positive. In a period of 5.5 years, the risk of screen-detected lung cancer strongly depends on the result of the first scan: 1.0% after a negative baseline result, 5.7% after an indeterminate baseline and 48.3% after a positive baseline. The screening strategy yielded few positive and false-positive scans with a reasonable positive predictive value. The 5.5-year lung cancer risk calculations aid clinicians in counselling candidates for lung cancer screening with low-dose computed tomography.

Diagnosis of chronic obstructive pulmonary disease in lung cancer screening Computed Tomography scans: independent contribution of emphysema, air trapping and bronchial wall thickening.

BACKGROUND: Beyond lung cancer, screening CT contains additional information on other smoking related diseases (e.g. chronic obstructive pulmonary disease, COPD). Since pulmonary function testing is not regularly incorporated in lung cancer screening, imaging biomarkers for COPD are likely to provide important surrogate measures for disease evaluation. Therefore, this study aims to determine the independent diagnostic value of CT emphysema, CT air trapping and CT bronchial wall thickness for COPD in low-dose screening CT scans. METHODS: Prebronchodilator spirometry and volumetric inspiratory and expiratory chest CT were obtained on the same day in 1140 male lung cancer screening participants. Emphysema, air trapping and bronchial wall thickness were automatically quantified in the CT scans. Logistic regression analysis was performed to derivate a model to diagnose COPD. The model was internally validated using bootstrapping techniques. RESULTS: Each of the three CT biomarkers independently contributed diagnostic value for COPD, additional to age, body mass index, smoking history and smoking status. The diagnostic model that included all three CT biomarkers had a sensitivity and specificity of 73.2% and 88.%, respectively. The positive and negative predictive value were 80.2% and 84.2%, respectively. Of all participants, 82.8% was assigned the correct status. The C-statistic was 0.87, and the Net Reclassification Index compared to a model without any CT biomarkers was 44.4%. However, the added value of the expiratory CT data was limited, with an increase in Net Reclassification Index of 4.5% compared to a model with only inspiratory CT data. CONCLUSION: Quantitatively assessed CT emphysema, air trapping and bronchial wall thickness each contain independent diagnostic information for COPD, and these imaging biomarkers might prove useful in the absence of lung function testing and may influence lung cancer screening strategy. Inspiratory CT biomarkers alone may be sufficient to identify patients with COPD in lung cancer screening setting.