Racial difference in BMI and lung cancer diagnosis: analysis of the National Lung Screening Trial.

BACKGROUND: The inverse relationship between BMI and lung cancer diagnosis is well defined. However, few studies have examined the racial differences in these relationships. The purpose of this paper is to explore the relationships amongst race, BMI, and lung cancer diagnosis using the National Lung Screening Trial (NLST) data. METHODS: Multivariate regression analysis was used to analyze the BMI, race, and lung cancer diagnosis relationships. RESULTS: Among 53,452 participants in the NLST cohort, 3.9% were diagnosed with lung cancer, 43% were overweight, and 28% were obese. BMI was inversely related to lung cancer diagnosis among Whites: those overweight (aOR = .83, 95%CI = .75-.93), obese (aOR = .64, 95%CI = .56-.73) were less likely to develop lung cancer, compared to those with normal weight. These relationships were not found among African-Americans. CONCLUSION: Our findings indicate that the inverse relationship of BMI and lung cancer risk among Whites is consistent, whereas this relationship is not significant for African-Americans. In consideration of higher lung cancer incidence among African Americans, we need to explore other unknown mechanisms explaining this racial difference.

Preserving NLST mortality benefits and acceptable morbidity for lung cancer surgery in a community hospital.

BACKGROUND AND OBJECTIVES: The aim of this study was to demonstrate whether academic thoracic surgeons could achieve morbidity and mortality rates in community hospitals equivalent to those seen in National Lung Screening Trial (NLST). METHODS: This was a retrospective review of community hospital lung cancer procedures for clinical Stage I-III non-small-cell lung cancers from 2007 through 2014. Variables include age, comorbidities, computed tomography (CT) characterization, and operative techniques. RESULTS: There were 177 patients who had lung cancers removed by a minimally invasive approach (79%), including lobectomy in 127 (72%), segmentectomy in 4 (2%), and wedge-resections in 46 (26%). The median patient age was 71 years (interquartile range [IQR], 63-76). The cohort was primarily female (58%), clinical Stage I (82%), with a median tumor size of 2.3 cm (IQR, 1.5-3.3). The median length of stay was 6 days (range: 1-35). Complications were experienced by 78 (44.1%) patients, most commonly atrial fibrillation in 20 (11.3%) followed by air-leak in 19 (10.7%). There were no in-hospital deaths. Tumor location and extent of resection were associated with complications, while larger tumor size, margin contour, and resection method were associated with air-leak (all p < 0.05). Higher clinical stage and larger tumor size were associated with occult Stage III disease (both p < 0.05). CONCLUSIONS: The low morbidity and mortality rates from the NLST were achievable in a community setting for early-stage lung cancer. Characterization of cancers using CT imaging identified factors most commonly associated with postoperative complications and the presence of occult Stage III disease.

Issues with implementing a high-quality lung cancer screening program.

After a comprehensive review of the evidence, the United States Preventive Services Task Force recently endorsed screening with low-dose computed tomography as an early detection approach that has the potential to significantly reduce deaths due to lung cancer. Prudent implementation of lung cancer screening as a high-quality preventive health service is a complex challenge. The clinical evaluation and management of high-risk cohorts in the absence of symptoms mandates an approach that differs significantly from that of symptom-detected lung cancer. As with other cancer screenings, it is essential to provide to informed at-risk individuals a safe, high-quality, cost-effective, and accessible service. In this review, the components of a successful screening program are discussed as we begin to disseminate lung cancer screening as a national resource to improve outcomes with this lethal cancer. This information about lung cancer screening will assist clinicians with communications about the potential benefits and harms of this service for high-risk individuals considering participation in the screening process.

Trade-off between benefits, harms and economic efficiency of low-dose CT lung cancer screening: a microsimulation analysis of nodule management strategies in a population-based setting.

BACKGROUND: In lung cancer screening, a nodule management protocol describes nodule assessment and thresholds for nodule size and growth rate to identify patients who require immediate diagnostic evaluation or additional imaging exams. The Netherlands-Leuvens Screening Trial and the National Lung Screening Trial used different selection criteria and nodule management protocols. Several modelling studies have reported variations in screening outcomes and cost-effectiveness across selection criteria and screening intervals; however, the effect of variations in the nodule management protocol remains uncertain. This study evaluated the effects of the eligibility criteria and nodule management protocols on the benefits, harms and cost-effectiveness of lung screening scenarios in a population-based setting in Germany. METHODS: We developed a modular microsimulation model: a biological module simulated individual histories of lung cancer development from carcinogenesis onset to death; a screening module simulated patient selection, screening-detection, nodule management protocols, diagnostic evaluation and screening outcomes. Benefits included mortality reduction, life years gained and averted lung cancer deaths. Harms were costs, false positives and overdiagnosis. The comparator was no screening. The evaluated 76 screening scenarios included variations in selection criteria and thresholds for nodule size and growth rate. RESULTS: Five years of annual screening resulted in a 9.7-12.8% lung cancer mortality reduction in the screened population. The efficient scenarios included volumetric assessment of nodule size, a threshold for a volume of 300 mm3 and a threshold for a volume doubling time of 400 days. Assessment of volume doubling time is essential for reducing overdiagnosis and false positives. Incremental cost-effectiveness ratios of the efficient scenarios were 16,754-23,847 euro per life year gained and 155,287-285,630 euro per averted lung cancer death. CONCLUSIONS: Lung cancer screening can be cost-effective in Germany. Along with the eligibility criteria, the nodule management protocol influences screening performance and cost-effectiveness. Definition of the thresholds for nodule size and nodule growth in the nodule management protocol should be considered in detail when defining optimal screening strategies.

Evaluating the impact of varied compliance to lung cancer screening recommendations using a microsimulation model.

BACKGROUND: The US preventive services task force (USPSTF) recently recommended that individuals aged 55-80 with heavy smoking history be annually screened by low-dose computed tomography (LDCT), thereby extending the stopping age from 74 to 80 compared to the national lung screening trial (NLST) entry criterion. This decision was made partly with model-based analyses from cancer intervention and surveillance modeling network (CISNET), which assumed perfect compliance to screening. METHODS: As part of CISNET, we developed a microsimulation model for lung cancer (LC) screening and calibrated and validated it using data from NLST and the prostate, lung, colorectal, and ovarian cancer screening trial (PLCO), respectively. We evaluated population-level outcomes of the lifetime screening program recommended by the USPSTF by varying screening compliance levels. RESULTS: Validation using PLCO shows that our model reproduces observed PLCO outcomes, predicting 884 LC cases [Expected(E)/Observed(O) = 0.99; CI 0.92-1.06] and 563 LC deaths (E/O = 0.94 CI 0.87-1.03) in the screening arm that has an average compliance rate of 87.9% over four annual screening rounds. We predict that perfect compliance to the USPSTF recommendation saves 501 LC deaths per 100,000 persons in the 1950 U.S. birth cohort; however, assuming that compliance behaviors extrapolated and varied from PLCO reduces the number of LC deaths avoided to 258, 230, and 175 as the average compliance rate over 26 annual screening rounds changes from 100 to 46, 39, and 29%, respectively. CONCLUSION: The implementation of the USPSTF recommendation is expected to contribute to a reduction in LC deaths, but the magnitude of the reduction will likely be heavily influenced by screening compliance.

[Prerequisites for a successful lung cancer screening program]. / Voraussetzungen für ein erfolgreiches Lungenkrebsscreeningprogramm.

The American national lung cancer screening trial (NLST) has provided the first confirmation of a reduction in lung cancer mortality by using low-dose multislice computed tomography (MSCT). Preliminary evaluations of smaller European trials could not confirm such a reduction. The final evaluation of the larger Dutch-Belgian NELSON trial and five other European trials are expected within the next 1-2 years. The results of the completed rounds of screening in all these studies indicate that the margin between a positive and a negative benefit-to-harm balance will be narrow. In such a scenario it will be crucial to optimize the definition of the target population for screening as a high-risk group for lung cancer, the quality of screening in terms of high sensitivity and specificity as well as high quality treatment and an effective ongoing control of program quality. Not all healthcare systems are suitable to fulfill these prerequisites.

Implementing low-dose computed tomography screening for lung cancer in Canada: implications of alternative at-risk populations, screening frequency, and duration.

BACKGROUND: Low-dose computed tomography (ldct) screening has been shown to reduce mortality from lung cancer; however, the optimal screening duration and "at risk" population are not known. METHODS: The Cancer Risk Management Model developed by Statistics Canada for the Canadian Partnership Against Cancer includes a lung screening module based on data from the U.S. National Lung Screening Trial (nlst). The base-case scenario reproduces nlst outcomes with high fidelity. The impact in Canada of annual screening on the number of incident cases and life-years gained, with a wider range of age and smoking history eligibility criteria and varied participation rates, was modelled to show the magnitude of clinical benefit nationally and by province. Life-years gained, costs (discounted and undiscounted), and resource requirements were also estimated. RESULTS: In 2014, 1.4 million Canadians were eligible for screening according to nlst criteria. Over 10 years, screening would detect 12,500 more lung cancers than the expected 268,300 and would gain 9200 life-years. The computed tomography imaging requirement of 24,000-30,000 at program initiation would rise to between 87,000 and 113,000 by the 5th year of an annual nlst-like screening program. Costs would increase from approximately $75 million to $128 million at 10 years, and the cumulative cost nationally over 10 years would approach $1 billion, partially offset by a reduction in the costs of managing advanced lung cancer. CONCLUSIONS: Modelling various ways in which ldct might be implemented provides decision-makers with estimates of the effect on clinical benefit and on resource needs that clinical trial results are unable to provide.

The National Lung Screening Trial Premise of Null and Chest Radiography Equivalence Is Open to Question.

OBJECTIVE: Lung cancer screening guidelines are based on the National Lung Screening Trial (NLST) that used chest radiographic control subjects on the premise of the reported mortality equivalence in chest radiography versus unscreened persons in the NLST-eligible subgroup of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. The purpose of this article is to discuss concerns regarding the validity of the NLST premise of chest radiography and null screening equivalence. CONCLUSION: Anomalous findings combined with the failure of CT trials using unscreened control subjects to replicate the benefits of the NLST open to question the validity of this premise.

Performance of the cancer risk management model lung cancer screening module.

BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that low-dose computed tomography (LDCT) screening reduces lung cancer mortality in a high-risk U.S. population. A microsimulation model of LDCT screening was developed to estimate the impact of introducing population-based screening in Canada. DATA AND METHODS: LDCT screening was simulated using the lung cancer module of the Cancer Risk Management Model (CRMM-LC), which generates large, representative samples of the Canadian population from which a cohort with characteristics similar to NLST participants was selected. Screening parameters were estimated for stage shift, LDCT sensitivity and specificity, lead time, and survival to fit to NLST incidence and mortality results. The estimation process was a step-wise directed search. RESULTS: Simulated mortality reduction from LDCT screening was 23% in the CRMM-LC, compared with 20% in the NLST. The difference in the number of lung cancer cases over six years varied by, at most, 2.3% in the screen arm. The difference in cumulative incidence at six years was less than 2% in both screen and control arms. The estimated percentage over-diagnosed was 24.8%, which was 6% higher than NLST results. INTERPRETATION: Simulated screening reproduces NLST results. The CRMM-LC can evaluate a variety of population-based screening strategies. Sensitivity analyses are recommended to provide a range of projections to reflect model uncertainty.

Pulmonary adenocarcinoma of low malignant potential defines indolent NSCLC associated with overdiagnosis in the national lung screening trial.

BACKGROUND: The national lung screening trial (NLST) demonstrated a reduction in lung cancer mortality with lowdose CT (LDCT) compared to chest x-ray (CXR) screening. Overdiagnosis was high (79%) among bronchoalveolar carcinoma (BAC) currently replaced by adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and adenocarcinoma of low malignant potential (LMP) exhibiting 100% disease specific survival (DSS). OBJECTIVE: Compare the outcomes and proportions of BAC, AIS, MIA, and LMP among NLST screendetected stage IA NSCLC with overdiagnosis rate. METHODS: Whole slide images were reviewed by a thoracic pathologist from 174 of 409 NLST screen-detected stage IA LUAD. Overdiagnosis rates were calculated from follow-up cancer incidence rates. RESULTS: Most BAC were reclassified as AIS/MIA/LMP (20/35 = 57%). The 7-year DSS was 100% for AIS/MIA/LMP and 94% for BAC. Excluding AIS/MIA/LMP, BAC behaved similarly to NSCLC (7-year DSS: 86% vs. 83%, p= 0.85) The overdiagnosis rate of LDCT stage IA NSCLC was 16.6% at 11.3-years, matching the proportion of AIS/MIA/LMP (16.2%) but not AIS/MIA (3.5%) or BAC (22.8%). CONCLUSIONS: AIS/MIA/LMP proportionally matches the overdiagnosis rate among stage IA NSCLC in the NLST, exhibiting 100% 7-year DSS. Biomarkers designed to recognize AIS/MIA/LMP preoperatively, would be useful to prevent overtreatment of indolent screen-detected cancers.

The HUNT lung-SNP model: genetic variants plus clinical variables improve lung cancer risk assessment over clinical models.

PURPOSE: The HUNT Lung Cancer Model (HUNT LCM) predicts individualized 6-year lung cancer (LC) risk among individuals who ever smoked cigarettes with high precision based on eight clinical variables. Can the performance be improved by adding genetic information? METHODS: A polygenic model was developed in the prospective Norwegian HUNT2 study with clinical and genotype data of individuals who ever smoked cigarettes (n = 30749, median follow up 15.26 years) where 160 LC were diagnosed within six years. It included the variables of the original HUNT LCM plus 22 single nucleotide polymorphisms (SNPs) highly associated with LC. External validation was performed in the prospective Norwegian Tromsø Study (n = 2663). RESULTS: The novel HUNT Lung-SNP model significantly improved risk ranking of individuals over the HUNT LCM in both HUNT2 (p < 0.001) and Tromsø (p < 0.05) cohorts. Furthermore, detection rate (number of participants selected to detect one LC case) was significantly better for the HUNT Lung-SNP vs. HUNT LCM in both cohorts (42 vs. 48, p = 0.003 and 11 vs. 14, p = 0.025, respectively) as well as versus the NLST, NELSON and 2021 USPSTF criteria. The area under the receiver operating characteristic curve (AUC) was higher for the HUNT Lung-SNP in both cohorts, but significant only in HUNT2 (AUC 0.875 vs. 0.844, p < 0.001). However, the integrated discrimination improvement index (IDI) indicates a significant improvement of LC risk stratification by the HUNT Lung-SNP in both cohorts (IDI 0.019, p < 0.001 (HUNT2) and 0.013, p < 0.001 (Tromsø)). CONCLUSION: The HUNT Lung-SNP model could have a clinical impact on LC screening and has the potential to replace the HUNT LCM as well as the NLST, NELSON and 2021 USPSTF criteria in a screening setting. However, the model should be further validated in other populations and evaluated in a prospective trial setting.

Early Detection of Lung Cancer in the NLST Dataset.

Lung Cancer is the leading cause of cancer mortality in the U.S. The effectiveness of standard treatments, including surgery, chemotherapy or radiotherapy, depends on several factors like type and stage of cancer, with the survival rate being much worse for later cancer stages. The National Lung Screening Trial (NLST) established that patients screened using low-dose Computed Tomography (CT) had a 15 to 20 percent lower risk of dying from lung cancer than patients screened using chest X-rays. While CT excelled at detecting small early stage malignant nodules, a large proportion of patients (> 25%) screened positive and only a small fraction (< 10%) of these positive screens actually had or developed cancer in the subsequent years. We developed a model to distinguish between high and low risk patients among the positive screens, predicting the likelihood of having or developing lung cancer at the current time point or in subsequent years non-invasively, based on current and previous CT imaging data. However, most of the nodules in NLST are very small, and nodule segmentations or even precise locations are unavailable. Our model comprises two stages: the first stage is a neural network model trained on the Lung Image Database Consortium (LIDC-IDRI) cohort which detects nodules and assigns them malignancy scores. The second part of our model is a boosted tree which outputs a cancer probability for a patient based on the nodule information (location and malignancy score) predicted by the first stage. Our model, built on a subset of the NLST cohort (n = 1138) shows excellent performance, achieving an area under the receiver operating characteristics curve (ROC AUC) of 0.85 when predicting based on CT images from all three time points available in the NLST dataset.

Volume doubling time and radiomic features predict tumor behavior of screen-detected lung cancers.

BACKGROUND: Image-based biomarkers could have translational implications by characterizing tumor behavior of lung cancers diagnosed during lung cancer screening. In this study, peritumoral and intratumoral radiomics and volume doubling time (VDT) were used to identify high-risk subsets of lung patients diagnosed in lung cancer screening that are associated with poor survival outcomes. METHODS: Data and images were acquired from the National Lung Screening Trial. VDT was calculated between two consequent screening intervals approximately 1 year apart; peritumoral and intratumoral radiomics were extracted from the baseline screen. Overall survival (OS) was the main endpoint. Classification and Regression Tree analyses identified the most predictive covariates to classify patient outcomes. RESULTS: Decision tree analysis stratified patients into three risk-groups (low, intermediate, and high) based on VDT and one radiomic feature (compactness). High-risk patients had extremely poor survival outcomes (hazard ratio [HR] = 8.15; 25% 5-year OS) versus low-risk patients (HR = 1.00; 83.3% 5-year OS). Among early-stage lung cancers, high-risk patients had poor survival outcomes (HR = 9.07; 44.4% 5-year OS) versus the low-risk group (HR = 1.00; 90.9% 5-year OS). For VDT, the decision tree analysis identified a novel cut-point of 279 days and using this cut-point VDT alone discriminated between aggressive (HR = 4.18; 45% 5-year OS) versus indolent/low-risk cancers (HR = 1.00; 82.8% 5-year OS). CONCLUSION: We utilized peritumoral and intratumoral radiomic features and VDT to generate a model that identify a high-risk group of screen-detected lung cancers associated with poor survival outcomes. These vulnerable subset of screen-detected lung cancers may be candidates for more aggressive surveillance/follow-up and treatment, such as adjuvant therapy.

Sublobar resection is comparable to lobectomy for screen-detected lung cancer.

OBJECTIVE: Sublobar resection is frequently offered to patients with small, peripheral lung cancers, despite the lack of outcome data from ongoing randomized clinical trials. Sublobar resection may be a particularly attractive surgical strategy for screen-detected lung cancers, which have been suggested to be less biologically aggressive than cancers detected by other means. Using prospective data collected from patients undergoing surgery in the National Lung Screening Trial, we sought to determine whether extent of resection affected survival for patients with screen-detected lung cancer. METHODS: The National Lung Screening Trial database was queried for patients who underwent surgical resection for confirmed lung cancer. Propensity score matching analysis (lobectomy vs sublobar resection) was done (nearest neighbor, 1:1, matching with no replacement, caliper 0.2). Demographics, clinicopathologic and perioperative outcomes, and long-term survival were compared in the entire cohort and in the propensity-matched groups. Multivariable logistic regression analysis was done to identify factors associated with increased postoperative morbidity or mortality. RESULTS: We identified 1029 patients who underwent resection for lung cancer in the National Lung Screening Trial, including 821 patients (80%) who had lobectomy and 166 patients (16%) who had sublobar resection, predominantly wedge resection (n = 114, 69% of sublobar resection). Patients who underwent sublobar resection were more likely to be female (53% vs 41%, P = .004) and had smaller tumors (1.5 cm vs 2 cm, P < .001). The sublobar resection group had fewer postoperative complications (22% vs 32%, P = .010) and fewer cardiac complications (4% vs 9%, P = .033). For stage I patients undergoing sublobar resection, there was no difference in 5-year overall survival (77% for both groups, P = .89) or cancer-specific survival (83% for both groups, P = .96) compared with patients undergoing lobectomy. On multivariable logistic regression analysis, sublobar resection was the only factor associated with lower postoperative morbidity/mortality (odds ratio, 0.63; 95% confidence interval, 0.40-0.98). To compare surgical strategies in balanced patient populations, we propensity matched 127 patients from each group undergoing sublobar resection and lobectomy. There were no differences in demographics or clinical and tumor characteristics among matched groups. There was again no difference in 5-year overall survival (71% vs 65%, P = .40) or cancer-specific survival (75% vs 73%, P = .89) for patients undergoing lobectomy and sublobar resection, respectively. CONCLUSIONS: For patients with screen-detected lung cancer, sublobar resection confers survival similar to lobectomy. By decreasing perioperative complications and potentially preserving lung function, sublobar resection may provide distinct advantages in a screened patient cohort.

The Journey for Lung Cancer Screening where we Stand Today.

Background: Lung cancer remains a leading cause of cancer mortality worldwide with many patients presenting with advanced disease. Objective: We reviewed the available literature for lung cancer screening using low dose computed tomography (LDCT). We reviewed the National Lung Screening Trial (NLST), Early Lung Cancer Action Program (ELCAP) and the (Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) trials. We also look at different lung cancer risk prediction models that may aid in identifying target populations and also discuss the cost-effectiveness of LDCT screening in different groups of smokers and ex-smokers. Lastly, we discuss recent guideline changes that have occurred in line with new and emerging evidence on lung cancer screening. Conclusion: LDCT has been shown reduce lung cancer mortality in certain groups of current and former smokers and should be considered to help in the early diagnosis of lung cancer.

Do competing causes of mortality contribute to overdiagnosis in lung cancer screening?

Overdiagnosed cancers are those that are screen-detected but never would have been symptomatic during patients' lifetimes. Indolent cancers are overdiagnosed cancers. Non-indolent cancers can be overdiagnosed when patients die of causes other than the screen-detected cancer and would have, in the absence of screening, been asymptomatic and undiagnosed at the time of death. This is termed competing cause of mortality (CCM) overdiagnosis. Deaths soon after screen detection may represent CCM overdiagnosis. We examined time from screen-detection to death among the 35 participants in the National Lung Screening Trial (NLST) low-dose computed tomography arm with screen-detected lung cancer and died of non-lung-cancer causes. Seven participants died within 6 months, and 20 died more than 24 months after diagnosis. Deaths due to non-lung cancer causes soon after screen detection were uncommon, arguing against widespread CCM overdiagnosis in the NLST. However, CCM overdiagnosis is likely more frequent in community-based screening given the higher prevalence of comorbidities.

Lung Cancer Risk among Patients with Asthma-Chronic Obstructive Pulmonary Disease Overlap.

Rationale: Chronic obstructive pulmonary disease (COPD) is a well-established independent risk factor for lung cancer; however, the literature on the association between asthma and lung cancer is mixed. Whether asthma-COPD overlap (ACO) is associated with lung cancer has not been studied. Objectives: We aimed to compare lung cancer risk among patients with ACO versus COPD and other conditions associated with airway obstruction. Methods: We studied 13,939 smokers from the National Lung Cancer Screening Trial who had baseline spirometry and used spirometric indices and history of childhood asthma to categorize participants into five specific airway disease subgroups. We used Poisson regression to compare unadjusted and adjusted lung cancer risk. Results: The incidence rate of lung cancer per 1,000 person-years was as follows: ACO, 13.2 (95% confidence interval [CI], 8.1-21.5); COPD, 11.7 (95% CI, 10.5-13.1); asthmatic smokers, 1.8 (95% CI, 0.6-5.4); Global Initiative for Chronic Obstructive Lung Disease-Unclassified, 7.7 (95% CI, 6.4-9.2); and normal spirometry smokers, 4.1 (95% CI, 3.5-4.8). Patients with ACO had increased adjusted risk of lung cancer compared with patients with asthma (incidence rate ratio [IRR], 4.5; 95% CI, 1.3-15.8) and normal spirometry smokers (IRR, 2.3; 95% CI, 1.3-4.2) in models adjusting for other risk factors. Adjusted lung cancer incidence in patients with ACO and COPD were not found to be different (IRR, 1.2; 95% CI, 0.7-2.1). Conclusions: The risk of lung cancer among patients with ACO is similar to those with COPD and higher than other groups of smokers. These results provide further evidence that COPD, with or without a history of childhood asthma, is an independent risk factor for lung cancer.

Impact of Low-Dose Computed Tomography Screening for Primary Lung Cancer on Subsequent Risk of Brain Metastasis.

INTRODUCTION: Brain metastasis (BM) is one of the most common metastases from primary lung cancer (PLC). Recently, the National Lung Screening Trial revealed the efficacy of low-dose computed tomography (LDCT) screening on LC mortality reduction. Nevertheless, it remains unknown if early detection of PLC through LDCT may be potentially beneficial in reducing the risk of subsequent metastases. Our study aimed to investigate the impact of LDCT screening for PLC on the risk of developing BM after PLC diagnosis. METHODS: We used the National Lung Screening Trial data to identify 1502 participants who were diagnosed with PLC in 2002 to 2009 and have follow-up data for BM. Cause-specific competing risk regression was applied to evaluate an association between BM risk and the mode of PLC detection-that is, LDCT screen-detected versus non-LDCT screen-detected. Subgroup analyses were conducted in patients with early stage PLC and those who underwent surgery for PLC. RESULTS: Of 1502 participants, 41.4% had PLC detected through LDCT screening versus 58.6% detected through other methods, for example, chest radiograph or incidental detection. Patients whose PLC was detected with LDCT screening had a significantly lower 3-year incidence of BM (6.5%) versus those without (11.9%), with a cause-specific hazard ratio (HR) of 0.53 (p = 0.001), adjusting for age at PLC diagnosis, PLC stage, PLC histology, and smoking status. This significant reduction in BM risk among PLCs detected through LDCT screening persisted in subgroups of participants with early stage PLC (HR = 0.47, p = 0.002) and those who underwent surgery (HR = 0.37, p = 0.001). CONCLUSIONS: Early detection of PLC using LDCT screening is associated with lower risk of BM after PLC diagnosis on the basis of a large population-based study.

Risk-based prediction model for selecting eligible population for lung cancer screening among ever smokers in Korea.

BACKGROUND: This study developed a new lung cancer risk prediction model for the Korean population and evaluated the performance, compared to the previously reported risk models developed in Western countries. METHODS: Among the 6,811,893 people who received health examinations from the Korean National Health Insurance Service, 969,351 ever-smokers (40-79 years) were included. Performance of Bach, Lung Cancer Risk Models for Screening, PLCOM2012, Pittsburgh, and Liverpool Lung Project models were evaluated. The ever-smokers were divided into the training and validation datasets by random sampling. The lung cancer risk model was developed and validated in the Korean population. The efficiency of model-based selection for lung cancer screening was compared with the eligible criteria of the National Lung Screening Trial (NLST). RESULTS: The Korean lung cancer risk model showed the area under the curve and expected/observed (E/O) ratio of 0.816 and 0.983 in the training dataset and 0.816 and 0.988 in the validation dataset. The Korean lung cancer risk model included age-mean of age, square of age-mean of age, sex, square root of pack-years of smoking, years since cessation, physical activity, alcohol consumption, body mass index, and medical history of chronic pulmonary obstructive disease, emphysema, pneumoconiosis, and interstitial pulmonary disease. Compared with the NLST criteria, the Korean lung cancer risk model's cut-off criteria (>2.1%) had more improved sensitivity (61.4% vs. 44.3%) and positive predictive value (4.1% vs. 2.9%). The Korean lung cancer risk model showed better discrimination and calibration than previously developed models in Western population. CONCLUSIONS: The Korean lung cancer risk model can select eligible population for low-dose computed tomography screening among the Asian population. The efficiency of risk model-based selection for lung cancer screening is superior to that of fixed criteria-based selection.

Computed tomography screening for lung cancer.

Cigarette smoking is the attributable cause for 90% of lung cancers. To complement preventative strategies, the advent of lung cancer screening programs targeted at prior and active smokers has been explored to reduce the mortality and morbidity of this lethal malignancy. In this article, we discuss the results of major computed tomography-based lung cancer screening trials, cost-effectiveness of screening, guidelines from major societies and future directions of the field.