Lung Cancer Screening Setting Research Articles

A Real-World Assessment of Stage I Lung Cancer Through Electronic Nose Technology

IntroductionElectronic nose (E-nose) technology has reported excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer. MethodsThis phase IIc trial (NCT04734145) included patients diagnosed with a single greater than or equal to 50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into three risk groups (low-risk, [<0.2]; moderate-risk, [≥0.2–0.7]; high-risk, [≥0.7]). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models. ResultsBased on the predefined cutoff (<0.20), E-nose agreed with histopathologic results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, two false negatives, and 12 false positives (n = 100). E-nose would refer fewer patients with malignant nodules to observation (low-risk: 2 versus 9 and 11, respectively; p = 0.028 and p = 0.011) than would the Swensen and Brock models and more patients with malignant nodules to treatment without biopsy (high-risk: 27 versus 19 and 6, respectively; p = 0.057 and p < 0.001). ConclusionsIn the setting of clinical stage I lung cancer, E-nose agrees well with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a “multiomics” platform.

Quantitative imaging workshop XIX: Utilizing quantitative thoracic imaging to optimize population health final summary.

Lung cancer screening involves the use of thoracic CT for both detection and measurements of suspicious lung nodules to guide the screening management. Since lung cancer screening eligibility typically requires age over 50 years along with >20 pack-year tobacco exposure, thoracic CT scans also frequently reveal evidence for pulmonary emphysema as well as coronary artery calcification. These three thoracic diseases are collectively three of the leading causes of premature death across the world. Screening for the major thoracic diseases in this heavily tobacco-exposed cohort is broadening the focus of lung cancer screening to a more comprehensive health evaluation including discussing the relevance of screen-detected findings of the heart and lung parenchyma. The status and implications of these emerging issues were reviewed in a multidisciplinary workshop focused on the process of quantitative imaging in the lung cancer screening setting to guide the evolution of this important new area of public health.

Fully automated calcium scoring predicts all-cause mortality at 12 years in the MILD lung cancer screening trial.

Coronary artery calcium (CAC) is a known risk factor for cardiovascular (CV) events and mortality but is not yet routinely evaluated in low-dose computed tomography (LDCT)-based lung cancer screening (LCS). The present analysis explored the capacity of a fully automated CAC scoring to predict 12-year mortality in the Multicentric Italian Lung Detection (MILD) LCS trial. The study included 2239 volunteers of the MILD trial who underwent a baseline LDCT from September 2005 to January 2011, with a median follow-up of 190 months. The CAC score was measured by a commercially available fully automated artificial intelligence (AI) software and stratified into five strata: 0, 1-10, 11-100, 101-400, and > 400. Twelve-year all-cause mortality was 8.5% (191/2239) overall, 3.2% with CAC = 0, 4.9% with CAC = 1-10, 8.0% with CAC = 11-100, 11.5% with CAC = 101-400, and 17% with CAC > 400. In Cox proportional hazards regression analysis, CAC > 400 was associated with a higher 12-year all-cause mortality both in a univariate model (hazard ratio, HR, 5.75 [95% confidence interval, CI, 2.08-15.92] compared to CAC = 0) and after adjustment for baseline confounders (HR, 3.80 [95%CI, 1.35-10.74] compared to CAC = 0). All-cause mortality significantly increased with increasing CAC (7% in CAC ≤ 400 vs. 17% in CAC > 400, Log-Rank p-value <0.001). Non-cancer at 12 years mortality was 3% (67/2239) overall, 0.8% with CAC = 0, 1.0% with CAC = 1-10, 2.9% with CAC = 11-100, 3.6% with CAC = 101-400, and 8.2% with CAC > 400 (Grey's test p < 0.001). In Fine and Gray's competing risk model, CAC > 400 predicted 12-year non-cancer mortality in a univariate model (sub-distribution hazard ratio, SHR, 10.62 [95% confidence interval, CI, 1.43-78.98] compared to CAC = 0), but the association was no longer significant after adjustment for baseline confounders. In conclusion, fully automated CAC scoring was effective in predicting all-cause mortality at 12 years in a LCS setting.

Using the Past to Understand the Future of U.S. and Global Smoking Disparities: A Birth Cohort Perspective

Using the Past to Understand the Future of U.S. and Global Smoking Disparities: A Birth Cohort Perspective

Automated Coronary Artery Calcium and Quantitative Emphysema in Lung Cancer Screening: Association With Mortality, Lung Cancer Incidence, and Airflow Obstruction.

To assess automated coronary artery calcium (CAC) and quantitative emphysema (percentage of low attenuation areas [%LAA]) for predicting mortality and lung cancer (LC) incidence in LC screening. To explore correlations between %LAA, CAC, and forced expiratory value in 1 second (FEV 1 ) and the discriminative ability of %LAA for airflow obstruction. Baseline low-dose computed tomography scans of the BioMILD trial were analyzed using an artificial intelligence software. Univariate and multivariate analyses were performed to estimate the predictive value of %LAA and CAC. Harrell C -statistic and time-dependent area under the curve (AUC) were reported for 3 nested models (Model survey : age, sex, pack-years; Model survey-LDCT : Model survey plus %LAA plus CAC; Model final : Model survey-LDCT plus selected confounders). The correlations between %LAA, CAC, and FEV 1 and the discriminative ability of %LAA for airflow obstruction were tested using the Pearson correlation coefficient and AUC-receiver operating characteristic curve, respectively. A total of 4098 volunteers were enrolled. %LAA and CAC independently predicted 6-year all-cause (Model final hazard ratio [HR], 1.14 per %LAA interquartile range [IQR] increase [95% CI, 1.05-1.23], 2.13 for CAC ≥400 [95% CI, 1.36-3.28]), noncancer (Model final HR, 1.25 per %LAA IQR increase [95% CI, 1.11-1.37], 3.22 for CAC ≥400 [95%CI, 1.62-6.39]), and cardiovascular (Model final HR, 1.25 per %LAA IQR increase [95% CI, 1.00-1.46], 4.66 for CAC ≥400, [95% CI, 1.80-12.58]) mortality, with an increase in concordance probability in Model survey-LDCT compared with Model survey ( P <0.05). No significant association with LC incidence was found after adjustments. Both biomarkers negatively correlated with FEV 1 ( P <0.01). %LAA identified airflow obstruction with a moderate discriminative ability (AUC, 0.738). Automated CAC and %LAA added prognostic information to age, sex, and pack-years for predicting mortality but not LC incidence in an LC screening setting. Both biomarkers negatively correlated with FEV 1 , with %LAA enabling the identification of airflow obstruction with moderate discriminative ability.

OA10.03 A Randomized Trial of Telephone-Based Smoking Cessation Treatment in the Lung Cancer Screening Setting

Lung cancer mortality is reduced via low-dose CT screening and treatment of early-stage disease. Evidence-based smoking cessation treatment delivered in the lung cancer screening setting can further reduce mortality. We report the quit rates, the short-term cost per quit, and long-term cost effectiveness of a trial of telephone counseling and nicotine replacement for individuals who smoke and were undergoing lung screening at 8 US screening facilities.

A Randomized Trial of Telephone-Based Smoking Cessation Treatment in the Lung Cancer Screening Setting.

Lung cancer mortality is reduced via low-dose computed tomography screening and treatment of early-stage disease. Evidence-based smoking cessation treatment in the lung screening setting can further reduce mortality. We report the results of a cessation trial from the National Cancer Institute's Smoking Cessation at Lung Examination collaboration. Eligible patients (n = 818) aged 50-80 years were randomly assigned (May 2017-January 2021) to the intensive vs minimal arms (8 vs 3 phone sessions plus 8 vs 2 weeks of nicotine patches, respectively). Bio-verified (primary) and self-reported 7-day abstinence rates were assessed at 3, 6, and 12 months post random assignment. Logistic regression analyses evaluated the effects of study arm. All statistical tests were 2-sided. Participants reported 48.0 (SD = 17.2) pack-years, and 51.6% were not ready to quit in less than 30 days. Self-reported 3-month quit rates were statistically significantly higher in the intensive vs minimal arm (14.3% vs 7.9%; odds ratio [OR] = 2.00, 95% confidence interval [CI] = 1.26 to 3.18). Bio-verified abstinence was lower but with similar relative differences between arms (9.1% vs 3.9%; OR = 2.70, 95% CI = 1.44 to 5.08). Compared with the minimal arm, the intensive arm was more effective among those with greater nicotine dependence (OR = 3.47, 95% CI = 1.55 to 7.76), normal screening results (OR = 2.58, 95% CI = 1.32 to 5.03), high engagement in counseling (OR = 3.03, 95% CI = 1.50 to 6.14), and patch use (OR = 2.81, 95% CI = 1.39 to 5.68). Abstinence rates did not differ statistically significantly between arms at 6 months (OR = 1.2, 95% CI = 0.68 to 2.11) or 12 months (OR = 1.4, 95% CI = 0.82 to 2.42). Delivering intensive telephone counseling and nicotine replacement with lung screening is an effective strategy to increase short-term smoking cessation. Methods to maintain short-term effects are needed. Even with modest quit rates, integrating cessation treatment into lung screening programs may have a large impact on tobacco-related mortality.

Cost-Effectiveness of a Telephone-Based Smoking Cessation Randomized Trial in the Lung Cancer Screening Setting.

BackgroundThere are limited data on the cost-effectiveness of smoking cessation interventions in lung cancer screening settings. We conducted an economic analysis embedded in a national randomized trial of 2 telephone counseling cessation interventions.MethodsWe used a societal perspective to compare the short-term cost per 6-month bio-verified quit and long-term cost-effectiveness of the interventions. Trial data were used to micro-cost intervention delivery, and the data were extended to a lifetime horizon using an established Cancer Intervention Surveillance and Modeling Network lung cancer model. We modeled the impact of screening accompanied by 8 weeks vs 3 weeks of telephone counseling (plus nicotine replacement) vs screening alone based on 2021 screening eligibility. Lifetime downstream costs (2021 dollars) and effects (life-years gained, quality-adjusted life-years [QALYs]) saved were discounted at 3%. Sensitivity analyses tested the effects of varying quit rates and costs; all analyses assumed nonrelapse after quitting.ResultsThe costs for delivery of the 8-week vs 3-week protocol were $380.23 vs $144.93 per person, and quit rates were 7.14% vs 5.96%, respectively. The least costly strategy was a 3-week counseling approach. An 8-week (vs 3-week) counseling approach increased costs but gained QALYs for an incremental cost-effectiveness ratio of $4029 per QALY. Screening alone cost more and saved fewer QALYs than either counseling strategy. Conclusions were robust in sensitivity analyses.ConclusionsTelephone-based cessation interventions with nicotine replacement are considered cost-effective in the lung screening setting. Integrating smoking cessation interventions with lung screening programs has the potential to maximize long-term health benefits at reasonable costs.

The reporting of pulmonary nodule results by letter in a lung cancer screening setting

ObjectivesPulmonary nodules are commonly found in Lung Cancer Screening (LCS), with results typically communicated by face-to-face or telephone consultation. Providing LCS on a population basis requires resource efficient and scalabe communication methods. Written communication provides one such method. Here, we assess participant satisfaction with this approach in a LCS setting and investigate characteristics associated with dissatisfaction. Materials and methodsThe SUMMIT Study is a prospective observational cohort study which aims to assess the implementation of Low-Dose Computed Tomography (LDCT) scanning for LCS in a high-risk population and validate a multi-cancer early detection blood test (NCT03934866). Participants with indeterminate pulmonary nodules requiring a three-month interval LDCT were informed of their result by postal letter and given a face-to-face appointment with a study practitioner at their interval LDCT appointment. At this appointment, having previously received their results letter, participants were verbally asked questions to assess their satisfaction with, and preferences for, methods of results communication. Results1,900 participants were included in the analysis. 82.8% (n = 1573) were satisfied with receiving their results by letter, with 2.9% (n = 55) reporting dissatisfaction. 86.3% (n = 1640) stated it was their preferred communication method and 77.3% (n = 1469) reported that their letter contained the right amount of information. Participants from less deprived socioeconomic quintiles were more likely to report that the letter contained insufficient information and individuals aged ≥ 70 years were less likely to do so.Although 13.7% (n = 261) participants had discussed their results with their General Practitioner (GP) prior to the study visit, 83.9% (n = 219) of these participants were satisfied with receiving results by letter, with the same proportion preferring this communication method. ConclusionWe report high participant satisfaction with the reporting of pulmonary nodule results by letter in a LCS setting. We believe this provides a feasible route forward for large-scale screening programmes.

Engaging Patients in Smoking Cessation Treatment within the Lung Cancer Screening Setting: Lessons Learned from an NCI SCALE Trial.

Offering smoking cessation treatment at lung cancer screening (LCS) will maximize mortality reduction associated with screening, but predictors of treatment engagement are not well understood. We examined participant characteristics of engagement in an NCI SCALE cessation trial. Eligible LCS patients (N = 818) were randomized to the Intensive arm (8 phone counseling sessions +8 weeks of nicotine replacement therapy (NRT)) vs. Minimal arm (3 sessions + 2 weeks of NRT). Engagement was measured by number of sessions completed (none, some, or all) and NRT mailed (none vs. any) in each arm. In the Intensive arm, those with ≥some college (OR = 2.1, 95% CI = 1.1, 4.0) and undergoing an annual scan (OR = 2.1, 95% CI = 1.1, 4.2) engaged in some counseling vs. none. Individuals with higher nicotine dependence were more likely (OR = 2.8, 95% CI = 1.3, 6.2) to request NRT. In the Minimal arm, those with higher education (OR = 2.1, 95% CI = 1.1, 3.9) and undergoing an annual scan (OR = 2.0, 95% CI = 1.04, 3.8) completed some sessions vs. none. Requesting NRT was associated with more pack-years (OR = 1.9, 95% CI = 1.1, 3.5). Regardless of treatment intensity, additional strategies are needed to engage those with lower education, less intensive smoking histories, and undergoing a first scan. These efforts will be important given the broader 2021 LCS guidelines.

Serum RNAs can predict lung cancer up to 10 years prior to diagnosis.

Lung cancer (LC) prognosis is closely linked to the stage of disease when diagnosed. We investigated the biomarker potential of serum RNAs for the early detection of LC in smokers at different prediagnostic time intervals and histological subtypes. In total, 1061 samples from 925 individuals were analyzed. RNA sequencing with an average of 18 million reads per sample was performed. We generated machine learning models using normalized serum RNA levels and found that smokers later diagnosed with LC in 10 years can be robustly separated from healthy controls regardless of histology with an average area under the ROC curve (AUC) of 0.76 (95% CI, 0.68-0.83). Furthermore, the strongest models that took both time to diagnosis and histology into account successfully predicted non-small cell LC (NSCLC) between 6 and 8 years, with an AUC of 0.82 (95% CI, 0.76-0.88), and SCLC between 2 and 5 years, with an AUC of 0.89 (95% CI, 0.77-1.0), before diagnosis. The most important separators were microRNAs, miscellaneous RNAs, isomiRs, and tRNA-derived fragments. We have shown that LC can be detected years before diagnosis and manifestation of disease symptoms independently of histological subtype. However, the highest AUCs were achieved for specific subtypes and time intervals before diagnosis. The collection of models may therefore also predict the severity of cancer development and its histology. Our study demonstrates that serum RNAs can be promising prediagnostic biomarkers in an LC screening setting, from early detection to risk assessment.

Computer tomography guided thoracoscopic resection of small pulmonary nodules in the hybrid theatre.

Thoracic surgeons are currently asked to resect smaller and deeper lesions which are difficult to detect thoracoscopically. The growing number of those lesions arises both from lung cancer screening programs and from follow-up of extrathoracic malignancies. This study analyzed the routine use of a CT-aided thoracoscopic approach to small pulmonary nodules in the hybrid theatre and the resulting changes in the treatment pathway. 50 patients were retrospectively included. The clinical indication for histological diagnosis was suspected metastasis in 46 patients. Technically, the radiological distance between the periphery of the lesion and the visceral pleura had to exceed the maximum diameter of the lesion for the patient to be included. A spiral wire was placed using intraoperative CT-based laser navigation to guide the thoracoscopic resection. The mean diameter of the lesions was 8.4 mm (SD 4.27 mm). 29.4 minutes (SD 28.5) were required on average for the wire placement and 42.3 minutes (SD 20.1) for the resection of the lesion. Histopathology confirmed the expected diagnosis in 30 of 52 lesions. In the remaining 22 lesions, 9 cases of primary lung cancer were detected while 12 patients showed a benign disease. Computer tomography assisted thoracoscopic surgery (CATS) enabled successful resection in all cases with minimal morbidity. The histological diagnosis led to a treatment change in 42% of the patients. The hybrid-CATS technique provides good access to deeply located small pulmonary nodules and could be particularly valuable in the emerging setting of lung cancer screening.

Predictors of Enrollment of Older Smokers in Six Smoking Cessation Trials in the Lung Cancer Screening Setting: The Smoking Cessation at Lung Examination (SCALE) Collaboration.

Increased rates of smoking cessation will be essential to maximize the population benefit of low-dose CT screening for lung cancer. The NCI's Smoking Cessation at Lung Examination (SCALE) Collaboration includes eight randomized trials, each assessing evidence-based interventions among smokers undergoing lung cancer screening (LCS). We examined predictors of trial enrollment to improve future outreach efforts for cessation interventions offered to older smokers in this and other clinical settings. We included the six SCALE trials that randomized individual participants. We assessed demographics, intervention modalities, LCS site and trial administration characteristics, and reasons for declining. Of 6285 trial- and LCS-eligible individuals, 3897 (62%) declined and 2388 (38%) enrolled. In multivariable logistic regression analyses, Blacks had higher enrollment rates (OR 1.5, 95% CI 1.2,1.8) compared to Whites. Compared to "NRT Only" trials, those approached for "NRT + prescription medication" trials had higher odds of enrollment (OR 6.1, 95% CI 4.7,7.9). Regarding enrollment methods, trials using "Phone + In Person" methods had higher odds of enrollment (OR 1.6, 95% CI 1.2,1.9) compared to trials using "Phone Only" methods. Some of the reasons for declining enrollment included "too busy" (36.6%), "not ready to quit" (8.2%), "not interested in research" (7.7%), and "not interested in the intervention offered" (6.2%). Enrolling smokers in cessation interventions in the LCS setting is a major priority that requires multiple enrollment and intervention modalities. Barriers to enrollment provide insights that can be addressed and applied to future cessation interventions to improve implementation in LCS and other clinical settings with older smokers. We explored enrollment rates and reasons for declining across six smoking cessation trials in the lung cancer screening setting. Offering multiple accrual methods and pharmacotherapy options predicted increased enrollment across trials. Enrollment rates were also greater among Blacks compared to Whites. The findings offer practical information for the implementation of cessation trials and interventions in the lung cancer screening context and other clinical settings, regarding intervention modalities that may be most appealing to older, long-term smokers.

Pairing smoking cessation with lung cancer screening may save lives

Pairing smoking cessation with lung cancer screening may save lives

Predictors of attrition in a smoking cessation trial conducted in the lung cancer screening setting

SignificanceAlthough it is a requirement that tobacco treatment is offered to cigarette smokers undergoing low-dose computed tomographic lung cancer screening (LCS), not all smokers engage in treatment. To understand the barriers to tobacco treatment in this setting, we evaluated predictors of attrition in a smoking cessation trial among individuals undergoing LCS. MethodsPrior to LCS, 926 participants, 50–80 years old, completed the baseline (T0) phone assessment, including demographic, clinical, tobacco, and psychological characteristics.Following LCS and receipt of the results, participants completed the pre-randomization (T1) assessment. ResultsAt the T1 assessment, 735 (79%) participants were retained and 191 (21%) dropped out. In multivariable analyses, attrition was higher among those who: smoked >1 pack per day (OR = 1.44, CI 1.01, 2.06) or had undergone their first (vs. annual) LCS scan (OR = 1.70, CI 1.20, 2.42). Attrition was lower among those with: more education (associates (OR = 0.67, CI = 0.46, 0.98) or bachelor's degree (OR = 0.56, CI 0.35, 0.91) vs. high school/GED), some (vs. none/a little) worry about lung cancer (OR = 0.60, CI 0.39, 0.92), or a screening result that was benign (OR = 0.57, CI 0.39, 0.82) or probably benign (OR = 0.38, CI 0.16, 0.90) vs. negative. ConclusionsThis study illuminated several LCS-related factors that contributed to trial attrition. Increasing tobacco treatment in this setting will require targeted strategies for those who report little lung cancer worry, are undergoing their first LCS exam, and/or who have a negative LCS result. Addressing attrition and reducing barriers to tobacco treatment will increase the likelihood of cessation, thereby reducing the risk of developing lung cancer.

A qualitative study exploring older smokers' attitudes and motivation toward quitting during the COVID-19 pandemic.

Older individuals who smoke are at increased risk of having severe outcomes from COVID-19, due to their long-term smoking and underlying health conditions. In this qualitative study, we explored the impact of COVID-19 on attitudes toward smoking and motivation to quit. Participants (N = 30) were enrolled in a larger ongoing randomized controlled smoking cessation trial conducted in the lung cancer screening setting. From March to May 2020, we assessed quantitative and qualitative responses to participants’ overall concern about COVID-19, changes in amount smoked, and motivation to reduce/quit smoking. Responses to the quantitative questions indicated that 64.3% of participants were extremely concerned with COVID-19, 20.7% reported reductions in amount smoked, and 37.9% reported increased motivation to quit. The qualitative responses, which were transcribed and coded using Consensual Qualitative Research guidelines, expanded upon these findings by providing the content of participants’ concerns, which included perceived risk of contracting COVID-19, the added stressors caused by COVID-19, and a variable impact on the amount smoked and motivation to quit. Although half of participants expressed extreme concern regarding COVID-19, fewer indicated increased motivation or reduced smoking. Qualitative themes suggested that the initial two months of the pandemic prompted some smokers to reduce or quit, but it exacerbated smoking triggers for others. Understanding how the pandemic continues to affect this vulnerable group will aid in adapting methods to support their efforts to stop smoking and remain abstinent.

ES13.03 Managing the Psychological Needs of Patients in a Screening Service

Psychological considerations within the realm of lung cancer screening are broad and span a number of areas. The aim of this talk is to give a brief overview of some of these areas. Firstly, an understanding of psychosocial factors can help program leaders develop campaigns to promote services and better target specific populations that demonstrate risk (Irwin et al., 2019; Montano et al., 1997). There are specific psychosocial factors including anxiety, fatalism, and concerns regarding stigma that impact the willingness of individuals and specific populations to accept screening (Quaife et al., 2017). Strategies for targeting these concerns include directly addressing these areas with patients, and coaching providers and medical team members to intervene. Secondly, tobacco/smoking cessation is vital to decreasing risk of lung cancer as well as a host of other illnesses and all cause mortality (Li et al., 2020). Psychology has an important role in engaging patients with quitting services and providing support and programming during quitting (Iaccarino et al., 2019). Motivational interviewing strategies have been shown to be particularly important in generating treatment engagement around addiction services in general, and tobacco cessation in particular (Miller & Rollnick, 2013). Efforts to convince patients to engage often backfire, while approaching individuals with curiosity and allowing space for patients to explore their own motivation to quit generate increased motivation. It is optimal that all program staff are aware of motivational interviewing principles and work together to create an atmosphere of partnership, acceptance, and compassion. Once tobacco/smoking cessation treatment has been accepted, matching individuals with modalities that fit their preferences, and are also most likely to generate successful outcomes, becomes important (Carter-Harris et al., 2018). Having recommendations for diverse modalities including in-person services, telephone services, text support, and apps allows patients to engage in ways that can minimize drop out from treatment. Providing a combination of medication and support resources as well as services that can provide support throughout the timeframe of quitting have also been shown to generate the greatest success in quitting. Finally, as with screening for any potentially serious diagnosis, patients can respond with significant distress at any point in the process (Byrne et al., 2008). In particular, waiting for results, receiving significant findings, or receiving inconclusive results are particularly risky times (Dunn et al., 2017). It is important for program staff to be aware of psychological signs indicating a need for additional services, and what types of services are best suited to address these concerns. Cognitive behavioral and mindfulness-based interventions have demonstrated significant positive outcomes for lessening distress in cancer patients following diagnosis and during treatment (Carlson, 2017). These treatments lessen distress by assisting patients in changing behaviors, thoughts, and their relationship to both cognitive and affective responses to stress. Byrne, M. M., Weissfeld, J., & Roberts, M. S. (2008). Anxiety, fear of cancer, and perceived risk of cancer following lung cancer screening. Medical Decision Making 28(Nov-Dec), 917-925. https://doi.org/10.1177/0272989X08322013 Carlson, M. (2017). CBT for psychological well-being in cancer: A skills training manual integrating DBT, ACT, behavioral activation and motivational interviewing (1st ed.). John Wiley & Sons Ltd. https://doi.org/10.1002/9781119161370 Carter-Harris, L., Shwindt, R., Bakoyannis, G., Ceppa, D. P. (2018). Current smokers’ preferences for receiving cessation information in a lung cancer screening setting. Journal of Cancer Education 33(5), 1120-1125. https://doi.org/10.1007/s13187-017-1222-7 Dunn, C. E., Edwards, A., Carter, B., Field, J. K., Brain, K., & Lifford, K. J. (2017). The role of screening expectations in modifying short-term psychological responses to low-dose computed tomography lung cancer screening among high risk individuals. Patient Education and Counseling 100, 1572-1579. https://dx.doi.org/10.1016.j.pec.2017.02.024 Iaccarino, J. M., Duran, C., Slatore, C. G., Weiner, R. S., & Kathuria, H. (2019). Combining smoking cessation intervention with LDCT lung cancer screening: A systematic review. Preventive Medicine 121, 24-32. https://doi.org/10.1016/j.ypmed.2019.02.016 Irwin, K. E., Stefens, E. B., Yoon, Y., Flores, E., J., Knight, H. P., Pirl, W. F., Freudenreich, O., Henderson, D. C., & Park, E. R. (2019). Lung cancer screening eligibility, risk perceptions, and clinician delivery of tobacco cessation among patients with schizophrenia. Psychiatric Services 70, 927-934. https://doi.org/10.1176/appi.ps.201900044 Li, J., Chung, S., Martinez, M. C., & Luft, H. S. (2020). Smoking-cessation interventions after lung cancer screening guidelines change. American Journal of Preventive Medicine 59(1), 88-97. https://doi.org/10.1016/j.amepre.2020.01.031 Miller, W. R., & Rollnick, S. (2013). Motivational interviewing (3rd ed.). The Guilford Press. Montano, D. E., Kasprzyk, D., Taplin, S. H. (1997). The theory of reasoned action and the theory of planned behavior. In K. Glanz, F. M. Lewis, & B. K. Rimer (Eds.), Health behavior and health education: Theory, research, and practice (pp. 85-112). Jossey-Bass Inc. Quaife, S. L., Marlow, L. A. V., McEwen, A., Janes, S. M., & Wardle, J. (2017). Attitudes towards lung cancer screening in socioeconomically deprived and heavy smoking communities: informing screening communication. Health Expectations 20, 563-573. https://doi.org/10.1111/hex.12481

Cost-Effectiveness of Smoking Cessation Interventions in the Lung Cancer Screening Setting: A Simulation Study.

Guidelines recommend offering cessation interventions to smokers eligible for lung cancer screening, but there is little data comparing specific cessation approaches in this setting. We compared the benefits and costs of different smoking cessation interventions to help screening programs select specific cessation approaches. We conducted a societal-perspective cost-effectiveness analysis using a Cancer Intervention and Surveillance Modeling Network model simulating individuals born in 1960 over their lifetimes. Model inputs were derived from Medicare, national cancer registries, published studies, and micro-costing of cessation interventions.We modeled annual lung cancer screening following 2014 US Preventive Services Task Force guidelines plus cessation interventions offered to current smokers at first screen, including pharmacotherapy only or pharmacotherapy with electronic and/or web-based, telephone, individual, or group counseling.Outcomes included lung cancer cases and deaths, life-years saved, quality-adjusted life-years (QALYs) saved, costs, and incremental cost-effectiveness ratios. Compared with screening alone, all cessation interventions decreased cases of and deaths from lung cancer. Compared incrementally, efficient cessation strategies included pharmacotherapy with either web-based cessation ($555 per QALY), telephone counseling ($7562 per QALY), or individual counseling ($35531 per QALY). Cessation interventions continued to have costs per QALY well below accepted willingness to pay thresholds even with the lowest intervention effects and was more cost-effective in cohorts with higher smoking prevalence. All smoking cessation interventions delivered with lung cancer screening are likely to provide benefits at reasonable costs. Because the differences between approaches were small, the choice of intervention should be guided by practical concerns such as staff training and availability.

Management and Outcomes of Suspected Infectious and Inflammatory Lung Abnormalities Identified on Lung Cancer Screening CT.

BACKGROUND. Incidental findings are frequently encountered during lung cancer screening (LCS). Limited data describe the prevalence of suspected acute infectious and inflammatory lung processes on LCS and how they should be managed. OBJECTIVE. The purpose of this study was to determine the prevalence, radiologic reporting and management, and outcome of suspected infectious and inflammatory lung processes identified incidentally during LCS and to propose a management algorithm. METHODS. This retrospective study included 6314 low-dose CT (LDCT) examinations performed between June 2014 and April 2019 in 3800 patients as part of an established LCS program. Radiology reports were reviewed, and patients with potentially infectious or inflammatory lung abnormalities were identified and analyzed for descriptors of imaging findings, Lung-RADS designation, recommendations, and clinical outcomes. Using the descriptors, outcomes, and a greater than 2% threshold risk of malignancy, a follow-up algorithm was developed to decrease additional imaging without affecting cancer detection. RESULTS. A total of 331/3800 (8.7%) patients (178 men, 153 women; mean age [range], 66 [53-87] years) undergoing LCS had lung findings that were attributed to infection or inflammation. These abnormalities were reported as potentially significant findings using the S modifier in 149/331 (45.0%) and as the dominant nodule used to determine the Lung-RADS category in 96/331 (29.0%). Abnormalities were multiple or multifocal in 260/331 (78.5%). Common descriptors were ground-glass (155/331; 46.8%), tree-in-bud (56/331; 16.9%), consolidation (41/331; 12.4%), and clustered (67/331; 20.2%) opacities. A follow-up chest CT outside of screening was performed within 12 months or less in 264/331 (79.8%) and within 6 months or less in 186/331 (56.2%). A total of 260/331 (78.5%) opacities resolved on follow-up imaging. Two malignancies (2/331; 0.6%) were associated with these abnormalities and both had consolidations. Theoretic adoption of a proposed management algorithm for suspected infectious and inflammatory findings reduced unnecessary follow-up imaging by 82.6% without missing a single malignancy. CONCLUSION. Presumed acute infectious or inflammatory lung abnormalities are frequently encountered in the setting of LCS. These opacities are commonly multifocal and resolve on follow-up. Less than 1% are associated with malignancy. CLINICAL IMPACT. Adoption of a conservative management algorithm can standardize recommendations and reduce unnecessary imaging without increasing the risk of missing a malignancy.

Artificial Intelligence Tools for Refining Lung Cancer Screening.

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