Screening Reduces Lung Cancer Mortality Research Articles

When to reinvite initially ineligible populations for targeted lung cancer screening?

IntroductionTargeted low-dose CT lung cancer screening reduces lung cancer mortality. England’s Targeted Lung Health Check programme uses risk prediction tools to determine eligibility for biennial screening among people with a...

Facilitators and Barriers to Lung Cancer Screening during Long COVID: A Global Systematic Review and Meta-Study Synthesis of Qualitative Research.

Background: Participation in targeted screening reduces lung cancer mortality by 30-60%, but screening is not universally available. Therefore, the study aimed to synthesize the evidence and identify facilitators and barriers to lung cancer screening participation globally. Methods: Two reviewers screened primary studies using qualitative methods published up to February 2023. We used two-phase synthesis consistent with a meta-study methodology to create an interpretation of lung cancer screening decisions grounded in primary studies, carried out a thematic analysis of group themes as specific facilitators and barriers, systematically compared investigations for similarities and differences, and performed meta-synthesis to generate an expanded theory of lung cancer screening participation. We used the Social Ecological Model to organize and interpret the themes: individual, interpersonal, social/cultural, and organizational/structural levels. Results: Fifty-two articles met the final inclusion criteria. Themes identified as facilitating lung cancer screening included prioritizing patient education, quality of communication, and quality of provider-initiated encounter/coordination of care (individual patient and provider level), quality of the patient-provider relationship (interpersonal group), perception of a life's value and purpose (cultural status), quality of tools designed, and care coordination (and organizational level). Themes coded as barriers included low awareness, fear of cancer diagnosis, low perceived benefit, high perceived risk of low-dose computerized tomography, concern about cancer itself, practical obstacle, futility, stigma, lack of family support, COVID-19 fear, disruptions in cancer care due to COVID-19, inadequate knowledge of care providers, shared decision, and inadequate time (individual level), patient misunderstanding, poor rapport, provider recommendation, lack of established relationship, and confusing decision aid tools (interpersonal group), distrust in the service, fatalistic beliefs, and perception of aging (cultural level), and lack of institutional policy, lack of care coordinators, inadequate infrastructure, absence of insurance coverage, and costs (and organizational status). Conclusions: This study identified critical barriers, facilitators, and implications to lung cancer screening participation. Therefore, we employed strategies for a new digital medicine (artificial intelligence) screening method to balance the cost-benefit, "workdays" lost in case of disease, and family hardship, which is essential to improve lung cancer screening uptake.

Recalibration of a Deep Learning Model for Low-Dose Computed Tomographic Images to Inform Lung Cancer Screening Intervals

Annual low-dose computed tomographic (LDCT) screening reduces lung cancer mortality, but harms could be reduced and cost-effectiveness improved by reusing the LDCT image in conjunction with deep learning or statistical models to identify low-risk individuals for biennial screening. To identify low-risk individuals in the National Lung Screening Trial (NLST) and estimate, had they been assigned a biennial screening, how many lung cancers would have been delayed 1 year in diagnosis. This diagnostic study included participants with a presumed nonmalignant lung nodule in the NLST between January 1, 2002, and December 31, 2004, with follow-up completed on December 31, 2009. Data were analyzed for this study from September 11, 2019, to March 15, 2022. An externally validated deep learning algorithm that predicts malignancy in current lung nodules using LDCT images (Lung Cancer Prediction Convolutional Neural Network [LCP-CNN]; Optellum Ltd) was recalibrated to predict 1-year lung cancer detection by LDCT for presumed nonmalignant nodules. Individuals with presumed nonmalignant lung nodules were hypothetically assigned annual vs biennial screening based on the recalibrated LCP-CNN model, Lung Cancer Risk Assessment Tool (LCRAT + CT [a statistical model combining individual risk factors and LDCT image features]), and the American College of Radiology recommendations for lung nodules, version 1.1 (Lung-RADS). Primary outcomes included model prediction performance, the absolute risk of a 1-year delay in cancer diagnosis, and the proportion of people without lung cancer assigned a biennial screening interval vs the proportion of cancer diagnoses delayed. The study included 10 831 LDCT images from patients with presumed nonmalignant lung nodules (58.7% men; mean [SD] age, 61.9 [5.0] years), of whom 195 were diagnosed with lung cancer from the subsequent screen. The recalibrated LCP-CNN had substantially higher area under the curve (0.87) than LCRAT + CT (0.79) or Lung-RADS (0.69) to predict 1-year lung cancer risk (P < .001). If 66% of screens with nodules were assigned to biennial screening, the absolute risk of a 1-year delay in cancer diagnosis would have been lower for recalibrated LCP-CNN (0.28%) than LCRAT + CT (0.60%; P = .001) or Lung-RADS (0.97%; P < .001). To delay only 10% of cancer diagnoses at 1 year, more people would have been safely assigned biennial screening under LCP-CNN than LCRAT + CT (66.4% vs 40.3%; P < .001). In this diagnostic study evaluating models of lung cancer risk, a recalibrated deep learning algorithm was most predictive of 1-year lung cancer risk and had least risk of 1-year delay in cancer diagnosis among people assigned biennial screening. Deep learning algorithms could prioritize people for workup of suspicious nodules and decrease screening intensity for people with low-risk nodules, which may be vital for implementation in health care systems.

Potential Impact of Criteria Modifications on Race and Sex Disparities in Eligibility for Lung Cancer Screening

IntroductionLow-dose computed tomography (LDCT) screening reduces lung cancer mortality, but current eligibility criteria underestimate risk in women and racial minorities. We evaluated the impact of screening criteria modifications on LDCT eligibility and lung cancer detection. MethodsUsing data from a Lung Nodule Program, we compared persons eligible for LDCT by the following: U.S. Preventive Services Task Force (USPSTF) 2013 criteria (55–80 y, ≥30 pack-years of smoking, and ≤15 y since cessation); USPSTF2021 criteria (50–80 y, ≥20 pack-years of smoking, and ≤15 y since cessation); quit duration expanded to less than or equal to 25 years (USPSTF2021-QD25); reducing the pack-years of smoking to more than or equal to 10 years (USPSTF2021-PY10); and both (USPSTF2021-QD25-PY10). We compare across groups using the chi-square test or analysis of variance. ResultsThe 17,421 individuals analyzed were of 56% female sex, 69% white, 28% black; 13% met USPSTF2013 criteria; 17% USPSTF2021; 18% USPSTF2021-QD25; 19% USPSTF2021-PY10; and 21% USPSTF2021-QD25-PY10. Additional eligible individuals by USPSTF2021 (n = 682) and USPSTF2021-QD25-PY10 (n = 1402) were 27% and 29% black, both significantly higher than USPSTF2013 (17%, p < 0.0001). These additional eligible individuals were 55% (USPSTF2021) and 55% (USPSTF2021-QD25-PY10) of female sex, compared with 48% by USPSTF2013 (p < 0.05). Of 1243 persons (7.1%) with lung cancer, 22% were screening eligible by USPSTF13. USPSTF2021-QD25-PY10 increased the total number of persons with lung cancer by 37%. These additional individuals with lung cancer were of 57% female sex (versus 48% with USPSTF2013, p = 0.0476) and 24% black (versus 20% with USPSTF2013, p = 0.3367). ConclusionsExpansion of LDCT screening eligibility criteria to allow longer quit duration and fewer pack-years of exposure enriches the screening-eligible population for women and black persons.

Lung Cancer Screening in Asbestos-Exposed Populations.

Asbestos exposure is the most important cause of occupational lung cancer mortality. Two large randomized clinical trials in the U.S. and Europe conclusively demonstrate that annual low-dose chest CT (LDCT) scan screening reduces lung cancer mortality. Age and smoking are the chief risk factors tested in LDCT studies, but numerous risk prediction models that incorporate additional lung cancer risk factors have shown excellent performance. The studies of LDCT in asbestos-exposed populations shows favorable results but are variable in design and limited in size and generalizability. Outstanding questions include how to: (1) identify workers appropriate for screening, (2) organize screening programs, (3) inform and motivate people to screen, and (4) incorporate asbestos exposure into LDCT decision-making in clinical practice. Conclusion: Screening workers aged ≥50 years with a history of ≥5 years asbestos exposure (or fewer years given intense exposure) in combination with either (a) a history of smoking at least 10 pack-years with no limit on time since quitting, or (b) a history of asbestos-related fibrosis, chronic lung disease, family history of lung cancer, personal history of cancer, or exposure to multiple workplace lung carcinogens is a reasonable approach to LDCT eligibility, given current knowledge. The promotion of LDCT-based screening among asbestos-exposed workers is an urgent priority.

AHRR (cg05575921) Methylation Safely Improves Specificity of Lung Cancer Screening Eligibility Criteria: A Cohort Study.

Screening reduces lung cancer mortality, but specificities of eligibility criteria are low. We tested if leukocyte AHRR(cg05575921) methylation improves specificity of lung cancer screening eligibility criteria. A total of 9,206 and 5,370 individuals of the 1991 to 1994 and 2001 to 2003 examinations of the Copenhagen City Heart Study, Denmark, were followed for lung cancer within 5 years after examination and mortality. Screening eligibility criteria (DANTE, DLCST, ITALUNG, LUSI, NELSON, NLST, and PLCOM2012) were evaluated, and AHRR (cg05575921) methylation extent at different methylation cut points was added. The model with the lowest number of eligible individuals per 5-year lung cancer was validated within the 2001 to 2003 examination. Eligibility criteria identified risk-groups ranging from 3,182 (DANTE) to 1,641 (ITALUNG) individuals. The positive predictive value was highest for PLCOM2012 (3.2%), while DANTE showed the highest negative predictive value (99.7%). Adding AHRR (cg05575921) methylation led to higher specificities for all criteria. Number of eligible individuals per 5-year lung cancer varied from 38 (NELSON) to 27 (NLST) with AHRR (cg05575921) methylation <55%. This last model led to a 21.9% lower screening burden and increased (P < 0.05) specificity of 84.0%. Findings were reproduced among the 5,334 individuals of the 2001 to 2003 examination. Adding AHRR (cg05575921) methylation on top of current eligibility criteria for lung cancer screening improves specificity by excluding those individuals with the lowest risk. The results point toward a potential clinical use of AHRR (cg05575921) methylation, which is a cost-effective measurement compared with lung CT scanning, to provide additional predictive risk information to identify eligible smokers for lung cancer screening. See related commentary by Hung, p. 698.

A risk prediction model for selecting high-risk population for computed tomography lung cancer screening in China

ObjectiveTwo large randomized controlled trials (RCTs) have demonstrated that low dose computed tomography (LDCT) screening reduces lung cancer mortality. Risk-prediction models have been proved to select individuals for lung cancer screening effectively. With the focus on established risk factors for lung cancer routinely available in general cancer screening settings, we aimed to develop and internally validated a risk prediction model for lung cancer. Materials and methodsUsing data from the Cancer Screening Program in Urban China (CanSPUC) in Henan province, China between 2013 and 2019, we conducted a prospective cohort study consisting of 282,254 participants including 126,445 males and 155,809 females. Detailed questionnaire, physical assessment and follow-up were completed for all participants. Using Cox proportional risk regression analysis, we developed the Henan Lung Cancer Risk Models based on simplified questionnaire. Model discrimination was evaluated by concordance statistics (C-statistics), and model calibration was evaluated by the bootstrap sampling, respectively. ResultsBy 2020, a total of 589 lung cancer cases occurred in the follow-up yielding an incident density of 64.91/100,000 person-years (pyrs). Age, gender, smoking, history of tuberculosis and history of emphysema were included into the model. The C-index of the model for 1-year lung cancer risk was 0.766 and 0.741 in the training set and validation set, respectively. In stratified analysis, the model showed better predictive power in males, younger participants, and former or current smoking participants. The model calibrated well across the deciles of predicted risk in both the overall population and all subgroups. ConclusionsWe developed and internally validated a simple risk prediction model for lung cancer, which may be useful to identify high-risk individuals for more intensive screening for cancer prevention.

In high-risk persons, lung cancer screening with CT vs. no or CXR screening reduces lung cancer mortality.

Passiglia F, Cinquini M, Bertolaccini L, et al. Benefits and harms of lung cancer screening by chest computed tomography: a systematic review and meta-analysis. J Clin Oncol. 2021;39:2574-85. 34236916.

Data Shows Low-Dose CT Screening Reduces Lung Cancer Mortality

Data Shows Low-Dose CT Screening Reduces Lung Cancer Mortality

Health and economic impact at a population level of both primary and secondary preventive lung cancer interventions: A model-based cost-effectiveness analysis

ObjectivesRobust economic evaluations are needed to identify efficient strategies for lung cancer prevention that combine brief and intensive smoking cessation intervention programmes with screening using low-dose computed tomography (LDCT) at different ages, frequencies, and coverages. We aimed to assess the cost-effectiveness of smoking cessation approaches combined with lung cancer screening in the European context at a population level from a societal perspective. Materials and MethodsA microsimulation model that describes the natural history of lung cancer and incorporates several prevention strategies was developed. Discounted lifetime QALYs and costs at a rate of 3% were used to calculate incremental cost-effectiveness ratios, defined as additional costs in 2017 Euros per QALY gained. ResultsSmoking cessation interventions reduce the incidence of lung cancer by 8%-46% and are consistently more effective and cost-effective when starting at younger ages. Screening reduces lung cancer mortality by 1%-24% and is generally less effective and more costly than smoking cessation interventions. The most cost-effective strategy would be to implement intensive smoking cessation interventions at ages 35, 40 and 45, combined with screening every three years between the ages of 55 and 65. ConclusionsCombining smoking cessation interventions with LDCT screening is a very attractive prevention strategy that substantially diminishes the burden of lung cancer. These combined prevention strategies, especially when providing several intensive interventions for smoking cessation at early ages, are more cost-effective than both approaches separately and allow for a more intensified LDCT without losing efficiency.

Lung cancer screening: who pays? who receives?-the Chinese perspective.

The National Lung Screening Trial (NLST) revealed that low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20.0%. In China, LDCT is very cheap and easy to access. As a result, LDCT screening is not limited to “high-risk” population defined by the NLST trial. The results of LDCT screening in China are also quite different from that in Western countries. LDCT detected lung cancer in a significant proportion of young, female and non-smokers in China. There is also a higher proportion of adenocarcinoma (ADC), a lower proportion of squamous cell carcinoma, and a higher proportion of early-stage 0/I disease among LDCT-detected lung cancer in China. The issue of overdiagnosis and overtreatment is discussed. Finally, we call the global attention to clarify the etiology of lung cancer in young female non-smokers.

Impact of the COVID-19 Pandemic on Lung Cancer Screening Program and Subsequent Lung Cancer

BackgroundLow-dose CT (LDCT) screening reduces lung cancer mortality by at least 20%. The COVID-19 pandemic required an unprecedented shutdown in our institutional LDCT program. The purpose of this study was to examine the impact of COVID-19 on lung cancer screening and subsequent cancer diagnosis.Study DesignWe analyzed our prospective institutional LDCT screening database, which began in 2012. In all, 2,153 patients have participated. Monthly mean number of LDCTs were compared between baseline (January 2017 to February 2020) and COVID-19 periods (March 2020 to July 2020).ResultsLDCT was suspended on March 13, 2020 and 818 screening visits were cancelled. Phased reopening began on May 5, 2020 and full opening on June 1, 2020. Total monthly mean ± SD LDCTs (146 ± 31 vs 39 ± 40; p < 0.01) and new patient monthly LDCTs (56 ± 14 vs 15 ± 17; p < 0.01) were significantly decreased during the COVID-19 period. New patient monthly LDCTs have remained low despite resuming full operations. Three- and 6-month interval follow-up LDCTs were prioritized and were significantly increased compared with baseline (11 ± 4 vs 30 ± 4; p < 0.01). The “no-show” rate was significantly increased from baseline (15% vs 40%; p < 0.04). Most concerning, the percentage of patients with lung nodules suspicious for malignancy (Lung-RADS 4) were significantly increased after screenings resumed (8% vs 29%; p < 0.01).ConclusionsCOVID-19 caused significant disruption in lung cancer screening, leading to a decrease in new patients screened and an increased proportion of nodules suspicious for malignancy once screening resumed. Using lung cancer and the LDCT screening program as a model, this early analysis showed the unrecognized consequences related to the pandemic for screening programs and cancer care.

Abstract PO-256: Factors determining adherence to lung cancer screening in a Hispanic urban population

Abstract Background: The National Lung Screening Trial (NLST) demonstrated that lung cancer screening reduces lung cancer mortality by 20% in high risk individuals. The rate of adherence to screening was more than 90% in the NSLT in a predominant non- Hispanic White (NHW) population, with only 1.8% Hispanics. Concerns regarding adherence in lung cancer screening have been widely reported. The goal of our study was to investigate the attributes of a Lung Cancer (LC) screening program and factors associated with screening adherence in a largely Hispanic urban population and compare with the NLST population. Methods: We performed a retrospective analysis of 421 consecutive cases who underwent LDCT screening from 2016-2019 at the University of Miami (UM), with similar inclusion criteria as the NLST. Annual adherence was defined as returning for imaging within 1 year and 90 days after an initial negative scan. Screening results, LC detection and screening adherence were examined and compared with the NLST cohort using summary statistics and X2 test for categorical variables. Association between adherence and baseline factors including age, gender, race/ethnicity, insurance, smoking history, and COPD was analyzed. Results: A total of 421 patients underwent screening from 2016-2019. UM cohort had a different racial and ethnic profile, with a higher percentage of Hispanics (47.3% vs 1.8%) and African Americans (15% vs 4.5%) in the UM than the NLST cohort respectively. Compared with NLST Low-Dose Computed Tomography (LDCT) arm, the UM cohort had fewer active smokers and a lighter smoking history. The proportion of positive LDCT screens (Lung-RADS Class 3/4) in the UM cohort (14.1%) was comparable to the NLST cohort (13.7%). Eighty-five percent of initial scans (359 of 421) were benign (Lung-RADS Class 1/2). The no-show rate for the LDCT screening shared-decision visit was 26% (228 of 891 visits). Early adherence rate to repeat annual imaging was 31.4% (81/258) Factors associated with early adherence included gender smoking, and race/ethnicity, with greater adherence in men than women, former smokers, and patients of NHW ethnicity. Despite, lower adherence to screening, the UM cohort had higher LC detection rate (3.3%) than the NLST cohort (1.1%) (p&amp;lt;0.001). Conclusion: Nonadherence to LDCT screening recommendations and non-compliance to shared decision making visits is common in a urban-based LDCT screening program. More data is needed to understand obstacles to compliance with screening in minority populations nationwide. Citation Format: Estelamari Rodriguez, Marie Jeanette Charles, Sophie Torrents, Richa Dawar, Nestor Villamizar, Dao Minh Nguyen, Kunal Gawri. Factors determining adherence to lung cancer screening in a Hispanic urban population [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-256.

CO-DESIGNING CANCER SCREENING INTERVENTIONS WITH PEOPLE OVER 55 YEARS OLD AT RISK FOR LUNG CANCER

In 2014, the US Preventive Task Force recommended annual lung cancer screening with low dose CT (LDCT) for adults aged 55 to 80 years old with significant smoking history. Although screening reduces lung cancer mortality, the leading cause of cancer mortality in the US, adherence to screening follow-up remains low. In a human-centered design qualitative study, health services researchers and eight adults over 55 years old from Kaiser Permanente Washington who had recently had an LDCT participated in two co-design sessions. We elicited barriers, facilitators and design principles to develop multilevel interventions that aim to improve adherence to ongoing LDCT. In the initial discussion, participants identified four key areas for improvements to adherence: a) reminders for scheduling and appointments, b) knowledge about tests and follow-up, c) convenience in location and scheduling, and d) financial and non-financial incentives. In a second session, participants referenced patient personas and sketched storyboards, a comic strip-like format showing steps in a journey, to describe different ways to help patients return for LDCTs. Through qualitative analysis, we identified ten elements to consider incorporating in multilevel interventions: versatility (e.g., multiple reminder options), social support (e.g., families, peers), individualization (e.g., tailoring to patient needs), feelings (e.g., fear, relief), knowledge (e.g., harms/benefits, expectations), responsibility (e.g., who is accountable for reminders), continuity (e.g., clear pathway to adherence), consistency (e.g., same messages), cadence (e.g., rhythm of messages), and acknowledgment (e.g., recognition of screening completion). Next steps are to incorporate feedback from clinical stakeholders and develop multilevel interventions for further testing.

Occurrence of Discussion about Lung Cancer Screening Between Patients and Healthcare Providers in the USA, 2017.

Computed tomography lung cancer screening reduces lung cancer mortality. However, screening is underutilized. This study assesses the extent to which providers discuss lung cancer screening with their patients, as a lack of discussion and counseling may serve as a potential cause of low utilization rates. Data from 1667 adults aged 55-80years sampled in the 2017 Health Information National Trends Survey was utilized. A weighted multivariable logistic regression model was fit with past-year discussion about lung cancer screening with a provider as the outcome. The adjusted odds of discussion were higher for current cigarette smokers compared to non-cigarette smokers (adjusted odds ratio = 3.91; 95% confidence interval [CI], 1.75 to 8.74). Despite higher odds, the absolute prevalence was low with only 18% (95% CI, 11.8 to 24.2%) of current adult smokers reporting a past-year discussion. Knowledge of screening from trusted sources of medical information, such as doctors, can increase screening rates and may ultimately reduce lung cancer mortality.

Understanding Lung-RADS 1.0: A Case-Based Review

Lung cancer is the leading cause of cancer death in both men and women in the United States. The National Lung Screening Trial (NLST) demonstrated that low-dose computed tomography (CT) screening reduces lung cancer mortality by 20% compared to screening with chest radiography. Currently, many institutions in the US are implementing lung cancer screening programs. The use of lung-RADS as a quality assurance tool allows standardization of lung cancer screening CT lexicon, reporting and management recommendations, and reduces confusion in lung cancer screening CT interpretations. Lung-RADS will also facilitate outcome monitoring and future auditing of lung cancer screening programs, assist research, and consequently refine and improve lung cancer screening practices. Familiarity with lung-RADS version 1.0 is essential not only for radiologists interpreting low-dose computed tomography screening studies, but all medical personnel involved in multidisciplinary lung cancer screening programs. This article reviews the Lung-RADS categories and management recommendations using a case-based approach.

Tumor-Associated Autoantibodies: Re-Optimization of EarlyCDT-Lung Diagnostic Performance and Its Application to Indeterminate Pulmonary Nodules

Background: Low-dose computed tomography (CT) screening reduces lung cancer mortality but costs are prohibitive for most healthcare budgets due to high false positive rates. An adjunctive test able to distinguish malignant from benign pulmonary nodules would be hugely beneficial. EarlyCDT-Lung measures serum autoantibodies to tumor-associated antigens and has found clinical acceptance to aid early detection of lung cancer for high risk patients. However performance was optimized for screening. The construction of a receiver-operating characteristic (ROC) curve would enable optimization of performance for alternative settings, including nodule malignancy. Methods: A Monte-Carlo search method was used to construct a ROC curve using a case-control cohort, enabling high and low specificity versions of EarlyCDT-Lung to be determined. These were used for a theoretical evaluation of a nodule cohort, and positive predictive value (PPV) was calculated under the assumption of independence of risk source. Patients or their nodules are typically classified into three risk groups: low (0% - 10%), intermediate (10% - 65%) and high (>65%) risk of malignancy. The predicted shift in risk group by application of the high and low specificity versions, along with the current commercial EarlyCDT-Lung, was then estimated. Results: The ROC curve, with an area under the curve of 0.743, was constructed. The high specificity (98%), low specificity (49%) and current commercial (91% specificity) versions of EarlyCDT-Lung re-classified 27%, 23% and 26% of intermediate nodules, respectively, to either a higher (10%, 8% and 10%) or lower (17%, 15% and 16%) risk group. Conclusion: A ROC curve was constructed to allow performance prediction of EarlyCDT-Lung at different specificities in the indeterminate nodule setting. This enabled risk re-classification of intermediate risk nodules, and could therefore facilitate alternative more appropriate intervention. We have shown how a multivariate biomarker test can add to the interpretation of pulmonary nodules and therefore aid patient management.

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

BackgroundIn the USA annual lung cancer screening is recommended. However, the optimal screening strategy (eg, screening interval, screening rounds) is unknown. This study provides results of the fourth screening round...

Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium.

BackgroundSupport for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures. Circulating biomarkers may serve as a valuable adjunctive tool to imaging.ResultsWe developed a broad-based proteomics discovery program, integrating liquid chromatography/mass spectrometry (LC/MS) analyses of freshly resected lung tumor specimens (n = 13), lung cancer cell lines (n = 17), and conditioned media collected from tumor cell lines (n = 7). To enrich for biomarkers likely to be found at elevated levels in the peripheral circulation of lung cancer patients, proteins were prioritized based on predicted subcellular localization (secreted, cell-membrane associated) and differential expression in disease samples. 179 candidate biomarkers were identified. Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189). An 8-marker model was developed (TFPI, MDK, OPN, MMP2, TIMP1, CEA, CYFRA 21–1, SCC) which accurately distinguished subjects with lung cancer (n = 50) from high risk smokers (n = 50) in an independent validation study (AUC = 0.775).ConclusionsIntegrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers. This unique collection of biomarkers may have clinical utility in lung cancer detection and diagnoses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12014-015-9090-9) contains supplementary material, which is available to authorized users.

Prevalence of incidental pulmonary nodules on computed tomography of the thorax in trauma patients.

Lung cancer is the third leading cause of death in high-income countries. Early detection leads to improved clinical outcomes, with evidence showing that lung cancer screening reduces lung cancer mortality. Knowledge of the population prevalence of pulmonary nodules affects the efficacy and cost-effectiveness of a local screening programme. We performed a retrospective review of our trauma database looking for the prevalence of incidental pulmonary nodules on computed tomography of the thorax. Prevalence of nodules and follow up according to Fleischner Guidelines were reviewed. Two hundred and forty-eight patients underwent a computed tomography thorax as part of their trauma assessment. 8.5% (21/248) had incidental pulmonary nodules. Eighty-one per cent of these (17/21) required follow up according to the Fleischner Society Guidelines. One was subsequently diagnosed with primary lung cancer, one with metastatic sigmoid cancer and one with invasive aspergillus. Incidental pulmonary nodules are common in the general population. This has implications for possible lung cancer screening recommendations in the Australian population. Referral and/or review systems are essential to ensure adequate follow up of incidental findings, as it is likely some patients are not receiving adequate follow up at present.