Computed Tomography Screening Research Articles

Recalibrating Risk Prediction Models by Synthesizing Data Sources: Adapting the Lung Cancer PLCO Model for Taiwan.

Methods synthesizing multiple data sources without prospective datasets have been proposed for absolute risk model development. This study proposed methods for adapting risk models for another population without prospective cohorts, which would help alleviate the health disparities caused by advances in absolute risk models. To exemplify, we adapted the lung cancer risk model PLCOM2012, well studied in the west, for Taiwan. Using Taiwanese multiple data sources, we formed an age-matched case-control study of ever-smokers (AMCCSE), estimated the number of ever-smoking lung cancer patients in 2011-2016 (NESLP2011), and synthesized a dataset resembling the population of cancer-free ever-smokers in 2010 regarding the PLCOM2012 risk factors (SPES2010). The AMCCSE was used to estimate the overall calibration slope, and the requirement that NESLP2011 equals the estimated total risk of individuals in SPES2010 was used to handle the calibration-in-the-large problem. The adapted model PLCOT-1 (PLCOT-2) had an AUC of 0.78 (0.75). They had high performance in calibration and clinical usefulness on subgroups of SPES2010 defined by age and smoking experience. Selecting the same number of individuals for low-dose computed tomography screening using PLCOT-1 (PLCOT-2) would have identified approximately 6% (8%) more lung cancers than the US Preventive Services Task Forces 2021 criteria. Smokers having 40+ pack-years had an average PLCOT-1 (PLCOT-2) risk of 3.8% (2.6%). The adapted PLCOT models had high predictive performance. The PLCOT models could be used to design lung cancer screening programs in Taiwan. The methods could be applicable to other cancer models.

Stage Migration and Lung Cancer Incidence After Initiation of Low-Dose Computed Tomography Screening

IntroductionDespite evidence from clinical trials of favorable shifts in cancer stage and improvements in lung cancer-specific mortality, the effectiveness of lung cancer screening (LCS) in clinical practice has not been clearly revealed. MethodsWe performed a multicenter cohort study of patients diagnosed with a primary lung cancer between January 1, 2014, and September 30, 2019, at one of four U.S. health care systems. The primary outcome variables were cancer stage distribution and annual age-adjusted lung cancer incidence. The primary exposure variable was receipt of at least one low-dose computed tomography for LCS before cancer diagnosis. ResultsA total of 3678 individuals were diagnosed with an incident lung cancer during the study period; 404 (11%) of these patients were diagnosed after initiation of LCS. As screening volume increased, the proportion of patients diagnosed with lung cancer after LCS initiation also rose from 0% in the first quartile of 2014 to 20% in the third quartile of 2019. LCS did not result in a significant change in the overall incidence of lung cancer (average annual percentage change [AAPC]: −0.8 [95% confidence interval (CI): −4.7 to 3.2]) between 2014 and 2018. Stage-specific incidence rates increased for stage I cancer (AAPC = 8.0 [95% CI: 0.8–15.7]) and declined for stage IV disease (AAPC = −6.0 [95% CI: −11.2 to −0.5]). ConclusionsImplementation of LCS at four diverse health care systems has resulted in a favorable shift to a higher incidence of stage I cancer with an associated decline in stage IV disease. Overall lung cancer incidence did not increase, suggesting a limited impact of overdiagnosis.

EP01.02-005 Exploring Individuals' Views on Invitation to Lung Cancer Screening: Developing a Tailored Approach

Lung cancer outcomes in the UK are poor with 70% of patients first presenting to specialist care with advanced disease and treatment at this stage having little effect on mortality. To improve outcomes, earlier diagnosis is essential, and a promising approach is Low Dose Computer Tomography screening (LS). Despite the efficacy of LS, there is evidence that those most at risk of lung cancer are the least likely to attend screening. Effective methods to encourage high-risk people into screening programmes are needed.

Treatment of Stage I Lung Cancer Detected by Computed Tomography Screening

IntroductionReducing lung cancer deaths through early detection by computed tomography (CT) screening requires delivery of effective treatment. We performed this retrospective study to determine the types of treatment used for screen-detected stage I lung cancer at our academic center and to compare the demographic and clinical characteristics of patients by type of treatment. MethodsAll persons screened in the lung cancer screening program at our institution through June 16, 2021, were included. Those with screening CT findings needing follow-up were managed through a thoracic surgery clinic. Demographic and clinical characteristics of patients diagnosed with having stage I lung cancer through June 16, 2021, were compared by type of treatment, with follow-up through December 31, 2021. ResultsStage I NSCLC was diagnosed in 54 of 2203 persons screened (2.5%), on the basis of biopsy in 37 and on imaging findings in 17 patients in whom a tissue diagnosis could not be obtained. Treatment was by lobectomy in 18, sublobar resection in 14, and stereotactic body radiation therapy (SBRT) in 22. Patients treated with SBRT had lower forced expiratory volume in 1 second (p < 0.001) and diffusing capacity of the lung for carbon monoxide (p < 0.001) and more comorbidities (p = 0.003) than those treated with surgery. New or recurrent cancer developed in nine patients (three lobectomy, three sublobar resection, three SBRT). ConclusionsMany patients with screen-detected stage I lung cancer are medically unfit for lobectomy, and a variety of treatments are being used. Assessment of treatment-based outcomes will be critical for ensuring an optimal balance of the risks and benefits of CT screening in a medically diverse population.

Deformation of Transcatheter Aortic Valve Prostheses: Implications for Hypoattenuating Leaflet Thickening and Clinical Outcomes.

Although transcatheter aortic valve replacement (TAVR) therapy continues to grow, there have been concerns about the occurrence of hypoattenuating leaflet thickening (HALT), which may affect prosthesis function or durability. This study aimed to examine prosthesis frame factors and correlate their extent to the frequency of HALT and clinical outcomes. We prospectively examined 565 patients with cardiac computed tomography screening for HALT at 30 days after balloon-expandable SAPIEN3 and self-expanding EVOLUT TAVR. Deformation of the TAVR prostheses, asymmetric prosthesis leaflet expansion, prosthesis sinus volumes, and commissural alignment were analyzed on the postprocedural computed tomography. For descriptive purposes, an index of prosthesis deformation was calculated, with values >1.00 representing relative midsegment underexpansion. A time-to-event model was performed to evaluate the association of HALT with the clinical outcome. Overall, HALT was present in 21% of SAPIEN3 patients and in 16% of EVOLUT patients at 30 days after TAVR. The occurrence of HALT was directly associated with greater prosthesis frame deformation (P<0.001), worse asymmetry of the leaflets (P<0.001), and smaller TAVR neosinus volumes (P<0.001). These relations were present in both prosthetic types and in all of their size ranges (all P<0.05). In multivariable analyses that include clinical variables previously associated with HALT (eg, anticoagulant therapy), variables of TAVR prosthesis deformation remained predictive of HALT. Although HALT was not associated with changes in prosthetic hemodynamics, its presence was associated with the risk of mortality at 1 year, with respect to greater incidences of all-cause mortality (hazard ratio, 2.98 [95% CI, 1.57-5.63]; P=0.001), cardiac death (hazard ratio, 4.58 [95% CI, 1.81-11.6]; P=0.001), and a composite outcome of all-cause mortality and heart failure hospitalization (hazard ratio, 1.94 [95% CI, 1.14-3.30]; P=0.02) with adjustment for age, sex, and comorbidities. Nonuniform expansion of TAVR prostheses resulting in frame deformation, asymmetric leaflet, and smaller neosinus volume is related to occurrence of HALT in patients who undergo TAVR. These data may have implications for both prosthesis valve design and deployment techniques to improve clinical outcomes for these patients.

Early natural menopause is associated with poor lung health and increased mortality among female smokers

Early natural menopause has been regarded as a biomarker of reproductive and somatic aging. Cigarette smoking is the most harmful factor for lung health and also an established risk factor for early menopause. Understanding the effect of early menopause on health outcomes in middle-aged and older female smokers is important to develop preventive strategies. This study aimed to examine the associations of early menopause with multiple lung health and aging biomarkers, lung cancer risk, and all-cause and cause-specific mortality in postmenopausal women who were moderate or heavy smokers. This study was conducted on postmenopausal women with natural (n=1038) or surgical (n=628) menopause from the Pittsburgh Lung Screening Study. The Pittsburgh Lung Screening Study is a community-based research cohort of current and former smokers, screened with low-dose computed tomography and followed up for lung cancer. Early menopause was defined as occurring before 45 years of age. The analyses were stratified by menopause types because of the different biological and medical causes of natural and surgical menopause. Statistical methods included linear model, generalized linear model, linear mixed-effects model, and time-to-event analysis. The average age of the 1666 female smokers was 59.4±6.7 years, with 1519 (91.2%) of the population as non-Hispanic Whites and 1064 (63.9%) of the population as current smokers at baseline. Overall, 646 (39%) women reported early menopause, including 198 (19.1%) women with natural menopause and 448 (71.3%) women with surgical menopause (P<.001). Demographic variables did not differ between early and nonearly menopause groups, regardless of menopause type. Significant associations were identified between early natural menopause and higher risk of wheezing (odds ratio, 1.65; P<.01), chronic bronchitis (odds ratio, 1.73; P<.01), and radiographic emphysema (odds ratio, 1.70; P<.001) and lower baseline lung spirometry in an obstructive pattern (-104.8 mL/s for forced expiratory volume in the first second with P<.01,-78.6 mL for forced vital capacity with P=.04, and-2.1% for forced expiratory volume in the first second-to-forced vital capacity ratio with P=.01). In addition, early natural menopause was associated with a more rapid decline of forced expiratory volume in the first second-to-forced vital capacity ratio (-0.16% per year; P=.01) and incident airway obstruction (odds ratio, 2.02; P=.04). Furthermore, women early natural menopause had a 40% increased risk of death (P=.023), which was mainly driven by respiratory diseases (hazard ratio, 2.32; P<.001). Mediation analyses further identified that more than 33.3% of the magnitude of the associations between early natural menopause and all-cause and respiratory mortality were explained by baseline forced expiratory volume in the first second. Additional analyses in women with natural menopause identified that the associations between continuous smoking and subsequent lung cancer risk and cancer mortality were moderated by early menopause status, and females with early natural menopause who continued smoking had the worst outcomes (hazard ratio, >4.6; P<.001). This study did not find associations reported above in female smokers with surgical menopause. Early natural menopause was found to be a risk factor for malignant and nonmalignant lung diseases and mortality in middle-aged and older female smokers. These findings have strong public health relevance as preventive strategies, including smoking cessation and chest computed tomography screening, should target this population (ie, female smokers with early natural menopause) to improve their postmenopausal health and well-being.

Cytisine Therapy Improved Smoking Cessation in the Randomized Screening and Multiple Intervention on Lung Epidemics Lung Cancer Screening Trial

IntroductionCytisine, a partial agonist-binding nicotine acetylcholine receptor, is a promising cessation intervention. We conducted a single-center, randomized, controlled trial (RCT) in Italy to assess the efficacy and tolerability of cytisine as a smoking cessation therapy among lung cancer screening participants. MethodsFrom July 2019 to March 2020, the Screening and Multiple Intervention on Lung Epidemics RCT enrolled 869 current heavy tobacco users in a low-dose computed tomography screening program, with a randomized comparison of pharmacologic intervention with cytisine plus counseling (N = 470) versus counseling alone (N = 399). The primary outcome was continuous smoking abstinence at 12 months, biochemically verified through carbon monoxide measurement. ResultsAt the 12-month follow-up, the quit rate was 32.1% (151 participants) in the intervention arm and 7.3% (29 participants) in the control arm. The adjusted OR of continuous abstinence was 7.2 (95% confidence interval: 4.6–11.2). Self-reported adverse events occurred more frequently in the intervention arm (399 events among 196 participants) than in the control arm (230 events among 133 participants, p < 0.01). The most common adverse events were gastrointestinal symptoms, comprising abdominal swelling, gastritis, and constipation. ConclusionsThe efficacy and safety observed in the Screening and Multiple Intervention on Lung Epidemics RCT indicate that cytisine, a very low-cost medication, is a useful treatment option for smoking cessation and a feasible strategy to improve low-dose computed tomography screening outcomes with a potential benefit for all-cause mortality.

Improving the Pulmonary Nodule Classification Based on KPCA-CNN Model

Lung cancer mortality, the main cause of cancer-associated death all over the world, can be reduced by screening risky patients with low-dose computed tomography (CT) scans for lung cancer. In CT screening, radiologists will have to examine millions of CT pictures, putting a great load on them. Convolutional neural networks (CNNs) with deep convolutions have the potential to improve screening efficiency. In the examination of lung cancer screening CT images, estimating the chance of a malignant nodule in a specific location on a CT scan is a critical step. Low-dimensional convolutional neural networks and other methods are unable to provide sufficient estimation for this task, even though the most advanced 3-dimensional CNN (3D-CNN) has extremely high computing requirements. This article presents a novel strategy for reducing false positives in automatic pulmonary nodule diagnosis from 3-dimensional CT imaging by merging a kernel Principal Component Analysis (kPCA) approach with a 2-dimensional CNN (2D-CNN). To recreate 3-dimensional CT images, the kPCA method is utilized, with the goal of reducing the dimension of data, minimizing noise from raw sensory data while maintaining neoplastic information. The CNN can diagnose new CT scans with an accuracy of up to 90% when trained with the regenerated data, which is better than existing 2D-CNNs and on par with the best 3D-CNNs. The short duration of training, and certain accuracy shows the potential of the kPCA-CNN to adapt to CT scans with different parameters in practice. The study shows that the kPCA-CNN modeling technique can improve the efficiency of lung cancer diagnosis.

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 lung cancer screening combined with nurse-led smoking cessation intervention: A population-based microsimulation study

BackgroundThe appropriate screening inclusion criteria of low-dose computed tomography screening for lung cancer in Chinese population remains unclear and the effect of combining screening with nurse-led smoking cessation intervention is poorly understood as well. ObjectiveWe compared the benefits and costs of lung cancer screening with and without nurse-led smoking cessation intervention in different inclusion criteria to help select optimal screening strategies. MethodsDifferent screening strategies were set based on diverse starting ages, smoking pack-year and whether nurse-led smoking cessation intervention was applied. We use nationally representative data published by the China Health and Retirement Longitudinal Survey, based on a microsimulation model, to predict incremental cost-effectiveness ratio and net health benefits under different strategies. ResultsThe incremental cost-effectiveness ratios for all lung cancer screening strategies were less than three times GDP per capita, and screening combined with smoking cessation intervention had lower incremental cost-effectiveness ratios. The largest net health benefits and probability of cost-effectiveness were both obtained in the strategy which conducted screening and nurse-led smoking cessation intervention for people over 45 years with at least 20 pack-year smoking history. In strategies screening alone, it was obtained in screening for people over 50 years and with at 20 pack-year smoking history. ConclusionsNurse-led smoking cessation intervention is recommended provided in conjunction with lung cancer screening. The optimal strategy is conducted screening with cessation intervention for current smokers or smoking quitters in the past 15 years who are over 45 years with at least 20 pack-year smoking history. For strategies screening alone, the target population should be over 50 years old with at least 20 pack year smoking history, when willingness to pay less than three times GPD per capita.

Abstract 23: Will novel systemic treatments alter the benefit of lung cancer screening?: A microsimulation study

Abstract Background: The U.S. Preventive Services Task Force has recently updated its 2013 lung cancer screening guidelines with low-dose computed tomography. In the last decade, population level mortality for advanced non-small cell lung cancer fell significantly due to the novel targeted and immunotherapy-based treatments. Moreover, with detection of new molecular targets, these therapies are expected to become the ultimate curative options. However, how these treatments might impact the benefits of lung cancer screening is unknown. Methods: We utilize a computer microsimulation modeling framework to screen the U.S. population aged 50 to 80 who had a 20 pack-year smoking history and currently smoked or had quit within the past 15 years under both standard treatments (chemotherapy and radiotherapy) and novel treatments (immunotherapy and targeted therapy) settings. The corresponding mortality reductions associated with the stage shift via low-dose computed screening are projected for each setting. Results: Over 25 years, risk-targeted screening saves 243 lives per 20,000 under standard therapies (12% mortality reduction) and 99 per 20,000 under fully adopted novel therapies (6% mortality reduction). Under standard treatment, 1.28 cancers are over-diagnosed per life saved; under fully adopted novel therapies, this increases to 3.46. Over 25 years the number needed to screen to avert one death is 82 under standard treatment and 202 under fully adopted novel therapies. Conclusions: Ongoing transition from chemotherapy and radiotherapy to novel immunotherapies and targeted therapies may reduce the expected lives saved by low-dose computed tomography screening. Screening recommendations might need to be reconsidered as novel treatments become widespread. Citation Format: Kemal Caglar Gogebakan, Jane Lange, Christopher Slatore, Ruth Etzioni. Will novel systemic treatments alter the benefit of lung cancer screening?: A microsimulation study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 23.

Abstract 2242: Impact of low-dose computed tomography screening for lung cancer at a community oncology clinic on stage of lung cancer diagnosis in the catchment area

Abstract Introduction: Arkansas has the second-highest incidence of lung cancer in the U.S., with a largely rural and medically underserved population. Low-dose computed tomography (LDCT) is a well-established procedure for lung cancer screening in academic medical centers, but few local community oncology centers utilize this technology. Highlands Oncology Group (HOG), located in Northwest Arkansas (NWA), took the initiative to bring LDCT screening to a non-academic medical center and provide routine LDCT screening to a rural population. The objective of this study is to evaluate the benefits of free LDCT screening at a community oncology clinic. Methods: The study compared for-fee and free periods of LDCT screening at HOG and their impact on identifying cancer in NWA. The study population was patients in HOG’s catchment area who fell into the risk categories set by the National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology to be eligible for screening between March 2013 and February 2020. Results: A total of 5,402 eligible participants enrolled in the study. During ten months of for-fee screening (n=60), 3.3% of patients diagnosed had Stage I lung cancer, and 1.7% were diagnosed with Stages II-IV. During the first ten months of free screening (n=729), 3% of patients were diagnosed with Stage I lung cancer, 1.8% were diagnosed with Stages II-IV, and 1.1% were diagnosed with other cancers. Over the entire program until February 2020 (n=5,402), a total of 76 patients were diagnosed with Stage I lung cancer, 52 were diagnosed with Stage II-IV, and 35 were diagnosed with other cancers. Conclusion: The result of this study suggests that eligible patients are more receptive to free lung cancer screening, even though most insurance coverage does not have a required co-pay for eligible patients. We also observed an increased diagnosis rate for early-stage lung cancers due to increased patient influx with free LDCT screening. The state central registry data showed a decline in distant lung cancer after the free LDCT screening offered in the northwestern counties in the HOG catchment area. At the same time, no such trend is visible for the entire state, suggesting a stage shift in lung cancer due to free LDCT screening. Citation Format: Edgar T. Ellis, Michael A. Bauer, Thaddeus Beck, Daniel S. Bradford, Joanna Thompson, Margarete C. Kulik, Joseph L. Su. Impact of low-dose computed tomography screening for lung cancer at a community oncology clinic on stage of lung cancer diagnosis in the catchment area [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2242.

Acceptability of a standalone written leaflet for the National Health Service for England Targeted Lung Health Check Programme: A concurrent, think-aloud study.

BackgroundMany countries are introducing low‐dose computed tomography screening programmes for people at high risk of lung cancer. Effective communication strategies that convey risks and benefits, including unfamiliar concepts and outcome probabilities based on population risk, are critical to achieving informed choice and mitigating inequalities in uptake.MethodsThis study investigated the acceptability of an aspect of NHS England's communication strategy in the form of a leaflet that was used to invite and inform eligible adults about the Targeted Lung Health Check (TLHC) programme. Acceptability was assessed in terms of how individuals engaged with, comprehended and responded to the leaflet. Semi‐structured, ‘think aloud’ interviews were conducted remotely with 40 UK screening‐naïve current and former smokers (aged 55–73). The verbatim transcripts were analysed thematically using a coding framework based on the Dual Process Theory of cognition.ResultsThe leaflet helped participants understand the principles and procedures of screening and fostered cautiously favourable intentions. Three themes captured the main results of the data analysis: (1) Response—participants experienced anxiety about screening results and further investigations, but the involvement of specialist healthcare professionals was reassuring; (2) Engagement—participants were rapidly drawn to information about lung cancer prevalence, and benefits of screening, but deliberated slowly about early diagnosis, risks of screening and less familiar symptoms of lung cancer; (3) Comprehension—participants understood the main principles of the TLHC programme, but some were confused by its rationale and eligibility criteria. Radiation risks, abnormal screening results and numerical probabilities of screening outcomes were hard to understand.ConclusionThe TLHC information leaflet appeared to be acceptable to the target population. There is scope to improve aspects of comprehension and engagement in ways that would support informed choice as a distributed process in lung cancer screening.Patient or Public ContributionThe insight and perspectives of patient representatives directly informed and improved the design and conduct of this study.

DELFI-L101: Development of a blood-based assay that evaluates cell-free DNA fragmentation patterns to detect lung cancer.

TPS3164 Background: Despite longstanding national recommendations, uptake of lung cancer screening in the US remains low. Barriers include access to lung cancer screening, costs, and concerns over potential harms like false-positives and radiation exposure. The DELFI technology evaluates fragmentation patterns of cfDNA using supervised machine learning to distinguish cancer from non-cancer [PMID30943338; 34417454; 31142840]. Methods: The DELFI-L101 is a case-control observational study (NCT04825834) prospectively enrolling at academic and community sites. Eligible participants (≥50 years of age) are individuals who currently smoke or previously smoked, with smoking histories of ≥20 pack-years. Individuals are ineligible if they had cancer treatment in the prior year or a history of hematologic malignancies or myelodysplasia. Cases are individuals with pathologically confirmed cancers (group A – lung, group C – non-lung). Controls are those without cancer (group B) as determined by low-dose computed tomography screening completed within 6 weeks of enrollment. Cases and controls are identified among enrollees from all participating sites. Total enrollment is estimated to be ̃2500 participants across all groups. Blood samples are collected at enrollment for DELFI analyses, which involves cfDNA isolation from plasma, low-coverage, whole-genome, next-generation sequencing, and machine learning methods. Clinical data (medical history, demographics, and diagnostic, surgery, imaging, and pathology reports, and/or other diagnostic information) are collected at enrollment and at 12 months post-enrollment. The primary objective is to train and test a classifier for the detection of lung cancer using the DELFI technology with other biomarkers and clinical features. Secondary objectives include the evaluation of classifiers to distinguish lung cancer from other cancers, modeling benefits and harms using performance estimates of these classifiers, and description of the analytical performance (eg, repeatability and reproducibility) of the DELFI technology and classifiers. The primary endpoint is the accuracy of lung cancer detection as measured by sensitivity, specificity, and the area under the receiver operating characteristic curve. Secondary endpoints include accuracy of tissue of origin classification, and adverse events associated with blood sample collection. The training and performance characterization of a DELFI classifier will further the development of an affordable, accessible, blood-based cancer detection tool with potential to overcome barriers to lung cancer screening. Clinical trial information: NCT04825834.

Redlining, structural racism, and lung cancer screening disparities.

The objective of this study was to understand the effect of historical redlining (preclusion from home loans and wealth-building for Black Americans) and its downstream factors on the completion of lung cancer screening in Boston. Patients within our institution were identified as eligible for lung cancer screening on the basis of the United State Preventive Service Task Force criteria and patient charts were reviewed to determine if patients completed low-dose computed tomography screening. Individual addresses were geocoded and overlayed with original 1930 Home Owner Loan Corporation redlining vector files. Structural equation models were used to estimate the odds of screening for Black and White patients, interacted with sex, in redlined and nonredlined areas. Black patients had a 44% lower odds of screening compared with White (odds ratio [OR], 0.66; 95% CI, 0.52-0.85). With race as a mediator, Black patients in redlined areas were 61% less likely to undergo screening than White patients (OR, 0.39; 95% CI, 0.24-0.64). Similarly, in redlined areas Black women had 61% (OR, 0.39; 95% CI, 0.21-0.73) and Black men 47% (OR, 0.53; 95% CI, 0.29-0.98) lower odds of screening compared with White men in redlined areas. Despite higher rates of lung cancer screening in redlined areas, Black race mediated worse screening rates in these areas, suggesting racist structural factors contributing to the disparities in lung cancer screening completion among Black and White patients. Furthermore, these disparities were more apparent in Black women, suggesting that racial and gender intersectional discrimination are important in lung cancer screening completion.

A narrative review of deep learning applications in lung cancer research: from screening to prognostication.

Background and ObjectiveDeep learning (DL) algorithms have been developed for various tasks, including lung nodule detection on chest radiographs or lung cancer computed tomography screening, potential candidate selection in lung cancer screening, malignancy prediction for indeterminate pulmonary nodules, lung cancer staging, treatment response prediction, prognostication, and prediction of genetic mutations in lung cancer. Furthermore, these DL algorithms have been applied in various clinical settings in order for them to be generalized in real-world clinical practice. Multiple DL algorithms have been corroborated to be on par with experts or current clinical prediction models for several specific tasks. However, no article has yet comprehensively reviewed DL algorithms dedicated to lung cancer research. This narrative review presents an overview of the literature dealing with DL techniques applied in lung cancer research and briefly summarizes the results according to the DL algorithms’ clinical use cases.Methodswe performed a narrative review by searching the Embase and OVID-MEDLINE databases for articles published in English from October, 2016 until September, 2021 and reviewing the bibliographies of key references to identify important literature related to DL in lung cancer research. The background, development, results, and clinical implications of each DL algorithm are briefly discussed. Lastly, we end this review article by highlighting future directions in lung cancer research using DL techniques.Key Content and FindingsDL algorithms have been introduced to show comparable or higher performance than human experts in various clinical settings. Specifically, they have been actively applied to detect lung nodules in chest radiographs or computed tomography (CT) examinations, optimize candidate selection for lung cancer screening (LCS), predict the malignancy of lung nodules, stage lung cancer, and predict treatment response, patients’ prognoses, and genetic mutations in lung cancers.ConclusionsDL algorithms have corroborated their potential value for various tasks, ranging from lung cancer screening to prognostication of lung cancer patients. Future research is warranted for the clinical application of these algorithms in daily clinical practice and verification of their real-world clinical usefulness.

Evaluation of Methylation Panel in the Promoter Region of p16INK4a , RASSF1A, and MGMT as a Biomarker in Sputum for Lung Cancer.

Lung cancer is the most common cause of cancer death in the world. Effective early detection and appropriate medications can help treat this deadly cancer. Therefore, early detection of lung cancer is of utmost importance, especially in screening high-risk populations (such as smokers) with an urgent need to identify new biomarkers. The present study aimed to demonstrate the potential of using the panel of DNA methylation as a biomarker for the early diagnosis of lung cancer from sputum samples. The methylated promoter of p16INK4a , RASSF1A, and MGMT genes was estimated by the methylation-specific polymerase chain reaction in a sample of 84 lung cancer patients (65 smokers and 19 non-smokers). Based on the results, p16INK4a promoter methylation was significantly associated with smoking habit and lung cancer progression in terms of histological grading and patient staging. The sensitivity and specificity of the p16INK4a gene as a biomarker for lung cancer were 71% and 90%, respectively. The methylated promoter of RASSF1A was less sensitive (48%) as a biomarker for lung cancer with 83%. The results demonstrated a strong association between promoter methylation of RASSF1A and late stages of lung cancer (P=0.0007). The sensitivity of the MGMT gene as a biomarker for lung cancer was 61% with high specificity (92%), compared to other candidate genes in this study. The epigenetic alteration in the promoter region of p16INK4a , RASSF1A, and MGMT genes is highly associated with cancer cell development. It is suggested that the use of these candidate biomarkers can be used as an adjunct to computed tomography screening to diagnose patients at high risk for lung cancer after validation.

Potential of Inflammatory Protein Signatures for Enhanced Selection of People for Lung Cancer Screening.

Simple SummarySelection of appropriate high-risk smokers is one of the major challenges for implementing low-dose computed tomography screening for lung cancer. Many lung cancer risk prediction models have been proposed to supplement lung cancer screening. This study evaluated the potential of inflammatory protein markers to enhance lung cancer risk stratification beyond lung cancer risk models. The addition of inflammatory protein markers to existing lung cancer risk models improved risk prediction. The inflammatory protein markers may enhance current risk stratification and may be useful to identify high-risk populations for lung cancer screening.Randomized trials have demonstrated a substantial reduction in lung cancer (LC) mortality by screening heavy smokers with low-dose computed tomography (LDCT). The aim of this study was to assess if and to what extent blood-based inflammatory protein biomarkers might enhance selection of those at highest risk for LC screening. Ever smoking participants were chosen from 9940 participants, aged 50–75 years, who were followed up with respect to LC incidence for 17 years in a prospective population-based cohort study conducted in Saarland, Germany. Using proximity extension assay, 92 inflammation protein biomarkers were measured in baseline plasma samples of ever smoking participants, including 172 incident LC cases and 285 randomly selected participants free of LC. Smoothly clipped absolute deviation (SCAD) penalized regression with 0.632+ bootstrap for correction of overoptimism was applied to derive an inflammation protein biomarker score (INS) and a combined INS-pack-years score in a training set, and algorithms were further evaluated in an independent validation set. Furthermore, the performances of nine LC risk prediction models individually and in combination with inflammatory plasma protein biomarkers for predicting LC incidence were comparatively evaluated. The combined INS-pack-years score predicted LC incidence with area under the curves (AUCs) of 0.811 and 0.782 in the training and the validation sets, respectively. The addition of inflammatory plasma protein biomarkers to established nine LC risk models increased the AUCs up to 0.121 and 0.070 among ever smoking participants from training and validation sets, respectively. Our results suggest that inflammatory protein biomarkers may have potential to improve the selection of people for LC screening and thereby enhance screening efficiency.

Bone mineral density alteration in obstructive sleep apnea by derived computed tomography screening

The association between obstructive sleep apnea (OSA) and bone mineral density (BMD) is poorly elucidated and has contradictory findings. Abdominal computed tomography (CT) for other indications can provide a valuable opportunity for osteoporosis screening. Thus, we retrospectively explored the association between OSA and BMD by examining abdominal CT vertebrae images for a multitude of conditions and indications. We included 315 subjects (174 with OSA and 141 without OSA) who performed at least two CT scans (under similar settings). Both groups had a similar duration between the first and second CT scans of 3.6 years. BMD decreased in those with OSA and increased age. A multivariate linear regression indicated that OSA is associated with BMD alterations after controlling for age, gender, and cardiovascular diseases. Here, we report that OSA is associated with BMD alterations. Further studies are required to untangle the complex affect of OSA on BMD and the possible clinical implications of vertebra-depressed or femoral neck fractures.

Relationship Between Reception of Low-Dose Computed Tomography Screening, Tobacco Cessation Attempt, and Reception of Pneumococcal Vaccine.

The stage at diagnosis is the single most important predictor of lung cancer outcome. Therefore, detecting lung cancer early is of utmost importance. Low-dose computed tomography (LDCT) has proven beneficial in the early detection and mortality reduction of lung cancer. Despite this, very few of the high-risk population get annual LDCT done. Patients' attitudes towards tobacco usage and preventive care can be a factor in getting LDCT. We analyzed the relationship between the willingness to undergo LDCT and a person's readiness to try tobacco cessation medication or get the pneumococcal vaccine. We also analyzed the relationship between patients who had tobacco cessation counseling and their willingness to get LDCT and pneumococcal vaccine. Medical records of high-risk patients seen in the East Tennessee State University (ETSU) clinics between January 1, 2016, and November 30, 2020, were analyzed retrospectively. In the data obtained, a total of 2,834 patients were current smokers and were included in the research. The study subjects were assessed in two ways, which from here on will be referred to as method one and method two. In the first method, patients who underwent LDCT were assessed, and the outcome investigated was tobacco cessation counseling, tobacco cessation medication prescription, and pneumococcal vaccination. In the second method, patients who had tobacco cessation counseling were assessed, and the outcome evaluated was LDCT, tobacco cessation medication prescription, and pneumococcal vaccination. In the first method, out of 2,834 total population, 570 had undergone at least one LDCT screening during the study period. Of the 570 patients who underwent LDCT, 22.8% tried one of the tobacco cessation medications at least once during the study period (vs. 9.8% in patients who did not get the LDCT). Also, 71.5% of patients who had LDCT received at least one dose of pneumonia vaccine (vs. 35.5% in patients who did not get the LDCT). In the second method, 1,673 out of 2,834 patients received at least one tobacco cessation counseling, and out of those, 27.5% had LDCT screening (vs. 9.5% among those who never received counseling). Also, 54.9% received a pneumococcal vaccine (vs. 45.1% among those who did not receive counseling). The study demonstrates a relationship between getting LDCT and getting a pneumococcal vaccine or tobacco cessation medications. It also reveals that tobacco cessation counseling increases the odds of getting LDCT, tobacco cessation medications, and pneumococcal vaccine.