Virtual Library

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    ES01 - Advances in Lung Cancer Screening Through Imaging (ID 769)

    • Event: WCLC 2018
    • Type: Educational Session
    • Track: Screening and Early Detection
    • Presentations: 4
    • Moderators:
    • Coordinates: 9/24/2018, 13:30 - 15:00, Room 206 F
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      ES01.01 - Image Quality Characteristics and Nodule Growth Measurement, Medical Physics and Machine Parameters (ID 11351)

      13:30 - 13:50  |  Presenting Author(s): Ricardo S Avila

      • Abstract

      Abstract not provided

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      ES01.02 - Image Interpretation and Advances from the Perspective of the Radiologist (ID 11352)

      13:50 - 14:10  |  Presenting Author(s): David F Yankelevitz

      • Abstract

      Abstract not provided

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      ES01.03 - Deep Machine Learning for Screening LDCT (ID 11353)

      14:10 - 14:30  |  Presenting Author(s): Bram Van Ginneken

      • Abstract

      Abstract not provided

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      ES01.04 - Multi-Phasic Screening - Can We Address Competing Causes of Morbidity * Mortality Such as Coronary Artery Disease and COPD (ID 11355)

      14:30 - 14:50  |  Presenting Author(s): Rozemarijn Vliegenthart

      • Abstract

      Abstract not provided

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    GR01 - Thymic Malignancies Tumor Board (ID 777)

    • Event: WCLC 2018
    • Type: Grand Rounds Session
    • Track: Thymoma/Other Thoracic Malignancies
    • Presentations: 5
    • Moderators:
    • Coordinates: 9/25/2018, 10:30 - 12:00, Room 206 F
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      GR01.01 - Pathology (ID 11386)

      10:30 - 10:45  |  Presenting Author(s): Anja C Roden

      • Abstract

      Abstract not provided

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      GR01.02 - Surgical Oncology (ID 11387)

      10:45 - 11:00  |  Presenting Author(s): Pier Luigi Filosso  |  Author(s): Enrico Ruffini, Francesco Guerrera, Paolo Olivo Lausi, Paraskevas Lyberis, Alberto Oliaro

      • Abstract

      Abstract not provided

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      GR01.03 - Surgical Oncology (ID 11388)

      11:00 - 11:15  |  Presenting Author(s): David Waller

      • Abstract

      Abstract not provided

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      GR01.04 - Medical Oncology (ID 11389)

      11:15 - 11:30  |  Presenting Author(s): Nicolas Girard

      • Abstract

      Abstract not provided

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      GR01.05 - Radiation Oncology (ID 11390)

      11:30 - 11:45  |  Presenting Author(s): Anthony Brade

      • Abstract

      Abstract not provided

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    MA20 - Implementation of Lung Cancer Screening (ID 923)

    • Event: WCLC 2018
    • Type: Mini Oral Abstract Session
    • Track: Screening and Early Detection
    • Presentations: 11
    • Moderators:
    • Coordinates: 9/25/2018, 15:15 - 16:45, Room 206 F
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      MA20.01 - Lung Cancer Screenee Selection by USPSTF versus PLCOm2012 Criteria – Preliminary ILST Findings (ID 14331)

      15:15 - 15:20  |  Presenting Author(s): Martin Tammemägi  |  Author(s): Renelle L Myers, Mamta Ruparel, Niloofar Taghizadeh, Sukhinder Atkar-Khattra, Jennifer Dickson, Samantha Quaife, Angshu Bhowmik, Paul Burrowes, Paul Maceachern, Eric Bedard, John Yee, John Mayo, Jing Liu, Kwun M Fong, Alain Tremblay, Sam M Janes, Stephen Lam

      • Abstract
      • Presentation
      • Slides

      Background

      Background

      The National Lung Screening Trial showed that lung cancer screening of high-risk individuals with low dose computed tomography can reduce lung cancer mortality by 20%. Critically important is enrolling high-risk individuals. Most current guidelines including the United States Preventive Services Task Force (USPSTF) and Center for Medicare and Medicaid Services (CMS) recommend screening using variants of the NLST eligibility criteria: smoking ≥30 pack-years, smoking within 15 years, and age 55-80 and 55-77 years. Many studies indicate that using accurate risk prediction models is superior for selecting individuals for screening, but these findings are based on retrospective analyses. The International Lung Screen Trial(ILST) was implemented to prospectively identify which approach is superior.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Methods

      ILST is a multi-centred trial enrolling 4000 participants. Individuals will be offered screening if they are USPSTF criteria positive or have PLCOm2012 model 6-year risk ≥1.5%. Participants will receive two annual screens and will be followed for six years for lung cancer outcomes. Individuals not qualifying by either criteria will not be offered screening, but samples of them will be followed for lung cancer outcomes. Outcomes in discordant groups, USPSTF+ve/PLCOm2012-ve and USPSTF-ve/PLCOm2012+ve, are informative. Numbers of lung cancers, abnormal suspicious for lung cancer scans (a marker of future lung cancers) and individuals enrolled, and sensitivity and specificity and positive predictive values of the two criteria will be compared.

      4c3880bb027f159e801041b1021e88e8 Result

      Results

      As of March 2018, ILST centers in Canada (British Columbia and Alberta), Australia, and the United Kingdom had enrolled and scanned 1938 individuals. Study results are summarized in Figure 1.

      fig1.jpg

      8eea62084ca7e541d918e823422bd82e Conclusion

      Conclusion

      Interim analysis of ILST data, suggests that classification accuracy of lung cancer screening outcomes support the PLCOm2012 criteria over the USPSTF criteria. Individuals who are USPSTF+ve and PLCOm2012-ve appear to be at such low baseline risk (0.46%) that they may be unlikely to benefit from screening.

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      MA20.02 - “Reduced” HUNT Lung Cancer Model for Predicting Lung Cancer in the Prospective Danish Lung Cancer Screening Study - Comparison with the NLST. (ID 12802)

      15:20 - 15:25  |  Presenting Author(s): Oluf Dimitri Røe  |  Author(s): Maria Markaki, Ioannis Tsmardinos, Vincenzo Lagani, Jesper Holst Pedersen, Zaigham Saghir, Haseem Ashraf

      • Abstract
      • Presentation
      • Slides

      Background

      Risk prediction is important for selection of individuals for lung cancer screening programs. We have recently published a validated calculator, the HUNT Lung Cancer Risk Model (https://www.ebiomedicine.com/article/S2352-3964(18)30114-2/fulltext) for all ages and smoking patterns.

      The Danish Lung Cancer Screening Trial (DLCST) was a randomized prospective study that included 4104 heavy smokers with a median age of 57.6, 33.8 pack-years and maximum 9 years quit time and 10 years follow-up. We tested the value of the HUNT model in this prospective Danish lung cancer study and compared with the NLST.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      The DLCST study only had 5 of the 7 variables in the original HUNT Model, so we trained a “reduced” HUNT Model in the Norwegian HUNT2 cohort of 12 091 ever-smokers ages between 49-71 years (as the age span in the Danish cohort) based on age, pack-years, smoking intensity, quit time and BMI where sex was added for adjustment. The model was applied blindly in the 4051 individuals of the Danish cohort that had all 5 variables.

      4c3880bb027f159e801041b1021e88e8 Result

      In the population selected by the "reduced" HUNT Model, 148/149 (99.33%) lung cancer cases were predicted (sensitivity 99.33%, negative predictive value 99.23%), thus only one individual that developed lung cancer was lost among those 52 not selected for screening. If the the NLST criteria were used (age 55-74, >30 pack-years and <15 years quit time), less than half of the Danish cohort (n=1870 (46.2%)) would have been considered eligible for screening, and 104/149 (69.80%) lung cancer cases would have been predicted. With these criteria, one would lose 45 (32.7%) lung cancer cases, and the sensitivity would be lower (69.80%).

      8eea62084ca7e541d918e823422bd82e Conclusion

      We were able to predict 99.33% of those that were diagnosed with lung cancer in 10 years, only one future lung cancer case was not included. Therefore, even the “reduced” HUNT model was highly sensitive in selecting persons at high risk for lung cancer in a screening cohort. The objection one could have for preferring the NLST criteria is that one screened about half of this population but at the same time lost 1/3 of the future lung cancers. In a health system that can afford to screen more people than those included by the NLST criteria, the HUNT model may be useful, preferably the validated HUNT Lung Cancer Model, for the selection of high risk individuals to a screening programme.

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      MA20.03 - Surprising Implications of Proposed Risk-Thresholds for Selecting US Ever-Smokers into CT Lung-Cancer Screening (ID 13834)

      15:25 - 15:30  |  Presenting Author(s): Hormuzd Katki  |  Author(s): Christine Berg, Anil Chaturvedi, Rebecca Landy, Hilary Robbins, Li C Cheung

      • Abstract
      • Presentation
      • Slides

      Background

      Many studies show that using risk-models to select ever-smokers for screening may be more effective and efficient than current US Preventive Service Task Force (USPSTF) guidelines. Current National Comprehensive Cancer Network (NCCN) guidelines permit screening ever-smokers with at least 1.3% 6-year lung-cancer risk. Here we re-evaluate assertions, originally based on pre-2015 or non-representative data, that currently proposed risk-thresholds would screen no more ever-smokers than current USPSTF guidelines and at higher effectiveness and efficiency.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Using the 2015 US National Health Interview Survey (NHIS), we estimate the number of ever-smokers eligible for lung-cancer screening according to 3 lung-cancer risk-thresholds: 1.3% (NCCN) and 1.51% 6-year risks by the PLCOM2012 risk-model and 1.9% 5-year risk by the Lung Cancer Risk Assessment Tool (LCRAT). The NCCN and 1.51% thresholds were based on data from the Prostate Lung Colorectal and Ovarian (PLCO) cancer screening trial, a non-representative sample of US ever-smokers 1993-2001. The 1.9% threshold was based on pre-2015 but representative data (NHIS 2010-2012). Using previously published methodology to estimate 5-year outcomes following 3 annual CT lung-screens, we calculate screening effectiveness (the number needed to screen (NNS) to prevent 1 lung-cancer death) and efficiency (the number of false-positive CT screens per prevented lung-cancer death).

      4c3880bb027f159e801041b1021e88e8 Result

      8.0M US ever-smokers were eligible for lung-screening by USPSTF guidelines in 2015. Surprisingly, millions more were eligible according to risk-thresholds: 12.6M, 11.3M, and 9.2M ever-smokers were eligible at the 1.3% (NCCN), 1.51%, and 1.9% thresholds, respectively. We estimated effectiveness by USPSTF guidelines as NNS=194, which worsened to 222 and 207 for the 1.3% (NCCN) and 1.51% thresholds respectively, but improved to 172 for the 1.9% threshold. We estimated screening efficiency by USPSTF guidelines as 133 false-positives per prevented death, which worsened to 150 and 141 for the 1.3% (NCCN) and 1.51% thresholds respectively, but improved to 122 for the 1.9% threshold. The PLCOm2012 risk threshold that would select 8.0M 2015 ever-smokers is substantially higher than NCCN guidelines (2.28% vs. 1.3% 6-year risk).

      8eea62084ca7e541d918e823422bd82e Conclusion

      Compared to current USPSTF guidelines, the 1.3% (NCCN) and 1.51% risk thresholds (6-year risks by PLCOm2012) would screen many millions more US ever-smokers and likely at lower effectiveness and efficiency. Although the 1.9% threshold (5-year risk by LCRAT) also chose more ever-smokers than USPSTF guidelines, it may screen them more effectively and efficiently. Our findings demonstrate that risk-thresholds developed using older or non-representative data should be re-evaluated using current and representative data.

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      MA20.04 - Discussant - MA 20.01, MA 20.02, MA 20.03 (ID 14633)

      15:30 - 15:45  |  Presenting Author(s): Amanda Tufman

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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      MA20.05 - Who Gets Screened for Lung Cancer? A Simple Adjustment to Current Guidelines to Reduce Racial Disparities (ID 13992)

      15:45 - 15:50  |  Presenting Author(s): Melinda Aldrich  |  Author(s): Sarah Mercaldo, Kim L. Sandler, William J Blot, Eric Grogan, Jeffrey Blume

      • Abstract
      • Presentation
      • Slides

      Background

      Background. The United States Preventive Services Task Force (USPSTF) recommends low-dose computed tomography screening for lung cancer in current or former smokers age 55-80 years with a minimum 30 pack-year history and having quit no more than 15 years ago. However, these guidelines were developed in the predominantly white population of the National Lung Screening Trial and therefore may not be generalizable to African Americans who have different smoking patterns. We evaluated USPSTF lung cancer screening guidelines in a predominantly African American prospective cohort with an elevated incidence of lung cancer.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Methods. The Southern Community Cohort Study (SCCS) is a prospective observational cohort of approximately 86,000 adults (two-thirds African American) aged 40-79 years enrolled primarily at community health centers from 2002-2009 across 12 Southern U.S. states. Former and current smokers were included in the present study and were followed for up to 9 years. We examined the impact of race and smoking history on eligibility for lung cancer screening using USPSTF guidelines.

      4c3880bb027f159e801041b1021e88e8 Result

      Results. Among N=50,524 adult (67% African American, 33% white) ever smokers at baseline (64% current smokers, median age 50 years at enrollment) in the SCCS, we identified 1,359 incident lung cancers. Among lung cancer patients, 32% of African Americans were eligible for screening following USPTSF criteria compared with 55% of whites (p<0.001). The lower percentage of eligible African Americans was primarily due to African Americans having smoked fewer pack-years than whites (14 vs 27 median pack-years, respectively, p<0.001). Lowering the smoking pack-year eligibility criteria to a minimum 20-29 pack-year history, increased the number of African Americans eligible for screening by 38%. With a lower smoking pack-year criterion for African Americans, sensitivity increased from 32% to 50% and specificity decreased from 87% to 78% yielding sensitivity and specificity values that were similar to whites (55% sensitivity, 75% specificity) using the USPSTF guidelines.

      8eea62084ca7e541d918e823422bd82e Conclusion

      Conclusion. Current lung cancer screening guidelines are too conservative for African Americans. A greater percentage of African Americans are excluded from screening opportunities primarily due to lower smoking histories. Adjustment of pack-years in lung cancer screening guidelines by race will result in more equitable screening for smokers at high risk for lung cancer.

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      MA20.06 - Lung Cancer Screening Pilot for People at High Risk: Early Results on Cancer Detection and Staging (ID 13890)

      15:50 - 15:55  |  Presenting Author(s): Martin Tammemägi  |  Author(s): Gail Elizabeth Darling, Heidi Schmidt, Monica Yu, Marianne Luettschwager, Bogdan Pylypenko, Tanvi Patel, Veronica Rivera, Katharine Pearson, Katie Larson

      • Abstract
      • Presentation
      • Slides

      Background

      In June 2017, Cancer Care Ontario initiated organized lung cancer screening for people at high risk of developing lung cancer, using annual low-dose computed tomography (LDCT), at three pilot sites in Ontario. A key indicator of pilot success is detection of lung cancers at early stages. Ontario Cancer Registry (OCR) is used to track lung cancer diagnosis, stage and histology.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Patient abstracts were created using Registry Plus CDC abstracting software for pilot participants and patient-level data were collected from hospital data submissions, hospital electronic medical records via remote access, OCR pathology database (eMaRC) and OCR clinical source records (Resolink). Confirmed lung cancer cases were reviewed by a team of cancer staging analysts to achieve consensus on stage group using AJCC TNM 8th edition. A post-staging review was conducted for all staged cases to ensure accuracy and completeness.

      4c3880bb027f159e801041b1021e88e8 Result

      As of February 2018, 1086 participants received a baseline LDCT scan. 37% (n=404) of participants had Lung-RADS™ scores of 1; 45% (n=487) had Lung-RADS™ scores of 2; 10% (n=112) had Lung-RADS™ scores of 3; and 8% (n=83) had Lung-RADS™ scores of 4A, 4B or 4X, which triggered additional follow-up or diagnostic workup. 18 lung cancers were confirmed and 11 were fully staged.

      Of the 11 staged cases: 45% (n=5) was stage I; 9% (n=1) stage II; 9% (n=1) stage III; and 36% (n=4) stage IV. This represents a statistically significant increase in the proportion of early stage lung cancers (stage I and II) compared to historical proportions (p<0.05). 73% (n=8) were adenocarcinoma. The median risk score (i.e., PLCOm2012 risk prediction model probability of developing lung cancer in 6 years) was 8.1%, considerably higher than the median risk score of the overall pilot cohort (2.9%). 82% (n=9) had baseline Lung-RADS™ scores of 4X and 18% (n=2) had 4B. The average age at diagnosis was 67. 45% (n=5) were male; 55% (n=6) were current smokers; and 55% (n=6) had high school education or less. In addition, the screening pilot facilitated the successful transition by the OCR from AJCC TNM 7th to TNM 8th edition in lung cancer staging. Results will be updated in the conference presentation.

      8eea62084ca7e541d918e823422bd82e Conclusion

      Early pilot results demonstrate success in detecting early stage lung cancers and a statistically significant stage shift to earlier cancer stages. We anticipate a greater proportion of early stage lung cancers on annual recall LDCT scans. The OCR efficiently enabled capturing important incidence, staging and histological pilot data.

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      MA20.07 - Lung Cancer Screening for Limited-Resource Patients: Preliminary Findings from a Low-dose CT Pilot Program (ID 13910)

      15:55 - 16:00  |  Presenting Author(s): Lesley Watson  |  Author(s): Megan May Cotter, Robert A. Smith, Katherine Sharpe

      • Abstract
      • Presentation
      • Slides

      Background

      Low-dose CT (LDCT) screening for lung cancer in adults at high-risk is associated with a reduction in lung cancer mortality in high-risk adults, yet screening rates remain low. Increasing access to high-quality lung cancer screening is critical to further reducing deaths from the disease. In 2015 the American Cancer Society implemented a pilot program to identify successful strategies for improving access to LDCT in Memphis, Tennessee and Charleston, West Virginia through partnerships with Federally Qualified Health Centers (FQHCs) that serve limited resource patients. The program focused on developing systems within FQHCs to identify and refer patients for LDCT, and helping FQHCs build relationships with local accredited screening facilities to deliver lung cancer screening and navigate patients through the screening process and any necessary follow-up. This program is novel because it brings emerging technology in lung cancer screening and early detection to low-resource FQHCs that typically do not have access to state-of-the-art interventions. As such, the pilot affords important opportunities to identify facilitators and barriers to conducting LDCT in under-resourced areas. This presentation focuses on evaluation results for the program to-date, emphasizing barriers to implementation experienced by FQHCs and their screening partners.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Participating FQHCs submitted quarterly monitoring reports tracking the number of: patients assessed for LDCT eligibility, shared decision-making (SDM) visits, patients screened, and screening results. Evaluators conducted site visits and stakeholder interviews with staff from FQHCs and their screening partners in summer 2017 and 2018 to capture nuanced information about program implementation.

      4c3880bb027f159e801041b1021e88e8 Result

      Participating FQHCs conducted 387 SDM discussions and have screened 252 patients to date. Participants expressed uncertainty about the definition and process of SDM, and difficulty with tracking and billing for these patient-provider encounters. During the project period, both sites established processes for follow-up screening and referrals based on initial screening results (LRADs 1-4). Interview data provided insight into the major challenges and successes to piloting and implementing a new protocol. Both sites struggled to agree on the correct follow-up for LRADS 3 and 4 patients. Through piloting and discussion with clinic leadership, one site successfully implemented clear, logical follow-up procedures based on staff capacity and clinical guidelines.

      8eea62084ca7e541d918e823422bd82e Conclusion

      Our evaluation findings, including key lessons learned and recommendations, add to the growing knowledge base of effective lung cancer screening practices and may be used to inform and guide health systems looking to initiate similar programs, particularly those in low-resource settings.

      6f8b794f3246b0c1e1780bb4d4d5dc53

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      MA20.08 - Discussant - MA 20.05, MA 20.06, MA 20.07 (ID 14634)

      16:00 - 16:15  |  Presenting Author(s): Annette Maree McWilliams

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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      MA20.09 - Improved Lung Cancer and Mortality Prediction Accuracy Using Survival Models Based on Semi-Automatic CT Image Measurements (ID 12074)

      16:15 - 16:20  |  Presenting Author(s): Anton Schreuder  |  Author(s): Colin Jacobs, Nikolas Lessmann, Ernst Scholten, Ivana Isgum, Mathias Prokop, Cornelia Schaefer-Prokop, Bram Van Ginneken

      • Abstract
      • Presentation
      • Slides

      Background

      In a lung cancer CT screening setting, imaging biomarkers are typically extracted by experienced human readers. We found that adding semi-automatic computer-aided detection (CAD) measurements to a base model significantly improved lung cancer and mortality risk prediction accuracy.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      Participants’ baseline CT scans, characteristics, and 7-year follow-up outcomes were obtained from the National Lung Screening Trial. The selection included all 1810 deceased and a random selection of 4190 surviving participants from the CT screening arm with an image available; the latter subcohort was sampled with replacement up to 24432 to approximate the full CT arm. Seventeen patient characteristics variables endorsed by literature were considered for each model. CAD was used to automatically measure normalized emphysema score, coronary calcium volume, and thoracic aorta calcium volume. Pulmonary nodule consistency, volume, solid core volume (if part-solid), and upper lobe location were annotated by an experienced radiologist with CAD support. Only the largest noncalcified nodule was considered for the model; having no nodules was the reference.

      Cox proportional hazard regression was performed on patient characteristics variables only (base model) and combined with CAD variables (new model). This was done for three outcomes: lung cancer diagnosis, lung cancer mortality, and overall mortality. The average continuous net reclassification improvements (NRI) between the base and new models were calculated for each year following the baseline scan. To calculate NRI, the net percentages of subjects with and without the event of interest correctly reclassified as high and low risk, respectively, are summed (maximum range: -2 to 2); positive scores indicate that the new model is more accurate.

      4c3880bb027f159e801041b1021e88e8 Result

      CAD measures were successfully computed for 5575 baseline scans. After sampling, the test cohort consisted of 24370 participants. 3.9% were diagnosed with lung cancer (940/24370) and 6.9% died (1681/24370), of which 24.9% due to lung cancer (418/1681). For all outcomes, the new models were significantly superior to the base model. With lung cancer diagnosis as the outcome, the NRI at 1, 4, and 7 years follow-up were 0.628 (95% confidence interval: 0.373–0.700), 0.331 (0.261–0.390), and 0.349 (0.293–0.389), respectively. The respective NRIs were 0.501 (0.290–0.642), 0.288 (0.221–0.374), and 0.255 (0.218–0.339) when predicting lung cancer mortality and 0.496 (0.295–0.610), 0.301 (0.239–0.376), and 0.270 (0.201–0.320) when predicting overall mortality.

      8eea62084ca7e541d918e823422bd82e Conclusion

      CAD measures of emphysema and atherosclerosis and CAD-supported pulmonary nodule annotations are of added value for predicting lung cancer and mortality. These new models may be used to further personalize lung cancer CT screening follow-up protocols.

      6f8b794f3246b0c1e1780bb4d4d5dc53

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      • Abstract
      • Presentation
      • Slides

      Background

      Artificial Intelligence software has shown promise in predicting malignancy in indeterminate CT detected pulmonary nodules. This study aimed to assess the accuracy of a convolutional neural network (CNN) based lung cancer prediction software on an independent dataset of indeterminate incidentally detected nodules in a retrospective European multicentre trial.

      a9ded1e5ce5d75814730bb4caaf49419 Method

      The software was trained using the US National Lung Screening Trial (NLST) dataset which was manually curated, such that each reported nodule and cancer was located, contoured and diagnostically characterised (9310 benign nodule patients; 1058 cancer patients). From this complete dataset, a training set was built by selecting all patients with solid and part-solid lesions of 6mm and above, where benign nodules and cancers could be confidently identified by clinicians (5972 patients, of which 575 were cancer patients). A CNN classifier was trained using Deep Learning on this data to produce a malignancy score per nodule. We defined a benign nodule rule-out test by calculating thresholds on the malignancy score that achieve 100% and 99.5% sensitivity on the NLST data.

      The study was set up so that a malignancy score for each nodule was generated. Overall performance was evaluated using Area-Under-the-ROC-Curve analysis (AUC) and rule-out performance measured the specificity at the two thresholds, i.e. the proportion of benign nodules correctly stratified at each threshold.

      There were 2201 nodules, measuring between 5-15mm from 1719 patients from three tertiary referral centres in the UK, Germany and Netherlands. The CT data included heterogeneous scan parameters, scanner manufacturers and clinical indications. Diagnostic ground-truth was established according to Fleischner or British Thoracic Society guidelines. The dataset contained 222 unique cancers from 215 patients.

      4c3880bb027f159e801041b1021e88e8 Result

      AUC on all-site data was 0.92 (95%CI = 0.89-0.93) and broken down per-site the AUC was 0.97 (Netherlands, n=883, 26 cancers), 0.93 (UK, n= 698, 51 cancers), and 0.84 (Germany, 620, 145 cancers).

      The score thresholds used for the target sensitivity of 100% and 99.5% were the same and achieved an overall sensitivity on the data of 99.1% with a specificity of 25.0%. Per-site results were 25.6% (Netherlands), 27.8% (UK) and 20.6% (Germany) specificity with 100%, 100% and 98.6% sensitivity respectively.

      8eea62084ca7e541d918e823422bd82e Conclusion

      Performance of the AI software on independent European multicentre data was comparable to that achieved on the NLST training data, although there was some variability in the performance of the system across the three centres, potentially providing an opportunity for further optimisation.

      6f8b794f3246b0c1e1780bb4d4d5dc53

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      MA20.12 - Discussant - MA 20.09, MA 20.10 (ID 14635)

      16:25 - 16:40  |  Presenting Author(s): Heidi Schmidt

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    MS01 - Cancer Pathways, Targeted Therapy and Resistance (ID 780)

    • Event: WCLC 2018
    • Type: Mini Symposium
    • Track: Biology
    • Presentations: 4
    • Moderators:
    • Coordinates: 9/24/2018, 10:30 - 12:00, Room 206 F
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      MS01.01 - Defects of the SWI/SNF OR MYC/MAX Pathways: Effects in Cell Differentiation and Therapeutic Opportunities (ID 11401)

      10:30 - 10:50  |  Presenting Author(s): Montse Sanchez-Cespedes

      • Abstract
      • Presentation
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      Abstract

      The SWI/SNF complexes are ATP-dependent remodelers of the chromatin structure, by disrupting of DNA–histone interactions to activate or repress gene expression (Wilson et al. 2011). In healthy adults and during embryonic development, the complex is involved in the control of cell differentiation and in the specification of different tissues. Components of the SWI/SNF complex bind to various nuclear receptors, such as those of estrogen, progesterone, androgen, glucocorticoids and retinoic acid, thereby adapting the gene expression programs to the demands of the cell environmental requirements. The effect of the SWI/SNF complex on some of these processes is, at least in part, related to its involvement in regulating hormone-responsive promoters (reviewed Romero et al. 2014).

      A few years ago, we discovered that, in lung cancer, the SWI/SNF component, SMARCA4 (also called BRG1), is genetically inactivated in about thirty per cent of non-small cell lung cancers (NSCLC), and that its inactivation occurs in a background of wild type MYC (Medina et al. 2008). Nowadays, it is well established that other components of the complex are also commonly inactivated in most cancer types, including lung cancer (reviewed in Romero et al. 2014). Gene alterations of the SWI/SNF complex are significantly more common in NSCLC, as compared to small cell lung cancers (SCLC), and tend to associated with smoking habit. In addition, we reported the presence of tumor-specific inactivation of the MYC-associated factor X gene, MAX, in about ten percent of SCLC (Romero et al. 2014). The two events are mutually exclusive among them and with alterations at the MYC-family of genes. We also demonstrated that SMARCA4 regulates the expression of MAX and that depletion of SMARCA4 specifically in MAX-deficient cells strongly decreased cell growth, heralding a synthetic lethal interaction with potential therapeutic implications. Furthermore, MAX required of SMARCA4 to activate neuroendocrine transcriptional programs and to up-regulate MYC-targets, such as glycolytic-related genes. Finally, we observed genetic inactivation of the MAX dimerization protein, MGA, in lung cancers with wild type components of the SWI/SNF or MYC pathways.

      The widespread occurrence of alterations at genes encoding different components of the SWI/SNF complex reveals an important new feature that sustains cancer development. Retinoic acid (RA) and glucorticoids (GC) are well known modulators of cell differentiation, embryonic development and morphogenesis. GCs and RA are part of the curative treatment of some malignancies, mostly leukemias (Collins et al. 2002; Rutz et al. 2002; Pottier et al. 2008). However, most solid tumors, including lung cancers, are refractory to GC- and RA-based therapies. Underlying some cases of refractoriness to GC and RA is a dysfunctional SWI/SNF complex, for example due to alterations at SMARCA4 (Romero et al. 2002). On the other hand, compounds that modulate the structure of the chromatin are currently used to treat cancer. These include histone deacetylase (HDAC) inhibitors, in hematological malignancies and cutaneous T-cell lymphomas, and inhibitors of DNA methylation such as azacytidine for myelodysplasic syndrome (Liu et al. 2013). HDACs and DNA methylation inhibitors promote gene transcription by increasing DNA accessibility through the inhibition of histone deacetylation and DNA methylation, respectively. In a preliminary study, these drugs, in combination, have shown promising results in the treatment of lung cancer patients. In lung cancer cell lines, we observed that GC plus RA (GC/RA) in combination with the epigenetic drugs azacytidine and SAHA (A/S) reduced growth, triggered pro-differentiation gene expression signatures and downregulated MYC, in MYC-amplified but not in most SMARCA4-mutant cells (Romero et al. 2017). In vivo, treatments with GC/RA improved overall survival of mice implanted with MYC-amplified cells and reduced tumor-cell viability and cell proliferation. We also found some effect of the SAHA treatment, alone in reducing the cell growth of MYC-amplified lung cancer cells but not those that are SMARCA4-deficient. Thus, we propose that the combination of retinoids, corticoids and epigenetic treatments of lung tumors with MYC amplification constitute a strategy for therapeutic intervention in this otherwise incurable disease.

      Altogether, the genetic observations coupled with the functional evidence demonstrate that an aberrant SWI/SNF-MYC network is essential for lung cancer development and open novel therapeutic possibilities for the treatment of lung cancer patients.

      REFERENCES

      Collins SJ. The role of retinoids and retinoic acid receptors in normal hematopoiesis. Leukemia 2002; 16, 1896–905.

      Liu SV, Fabbri M, Gitlitz BJ, Laird-Offringa IA. Epigenetic therapy in lung cancer. Front Oncol 2013; 3, 135.

      Medina PP et al. Frequent BRG1/SMARCA4-inactivating mutations in human lung cancer cell lines. Hum Mut 2008; 29, 617-22a.

      Pottier N et al. The SWI/SNF chromatin-remodeling complex and glucocorticoid resistance in acute lymphoblastic leukemia. J Natl Cancer Inst 2008; 100, 1792-803.

      Romero OA et al. The tumour suppressor and chromatin-remodelling factor BRG1 antagonizes Myc activity and promotes cell differentiation in human cancer. EMBO Mol Med 2012; 4, 603-16.

      Romero OA et al. MAX inactivation in small cell lung cancer disrupts MYC-SWI/SNF programs and is synthetic lethal with BRG1. Cancer Discov 2014; 4, 292-303.

      Romero OA, Sanchez-Cespedes M. The SWI/SNF genetic blockade: effects in cell differentiation, cancer and developmental diseases. Oncogene 2014; 33, 2681-9.

      Romero OA et al. Sensitization of retinoids and corticoids to epigenetic drugs in MYC-activated lung cancers by antitumor reprogramming. Oncogene 2017; 36, 1287-96.

      Rutz HP. Effects of corticosteroid use on treatment of solid tumours. Lancet 2002; 360, 1969–70.

      Wilson GB, Roberts CWM. SWI/SNF nucleosome remodellers and cancer. Nat Rev Cancer 2011; 11, 481-92.

      e353dbe42c8654f33588d4da0b517469

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      MS01.02 - Targeting Negative Feedback Regulators to Hyperactivate Oncogenic Signaling (ID 11402)

      10:50 - 11:10  |  Presenting Author(s): William Lockwood

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      MS01.03 - Stimulating Anti-Tumor Immunity Through Enhancing T-Cell Activation (ID 11403)

      11:10 - 11:30  |  Presenting Author(s): Kwok-Kin Wong

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      MS01.04 - Addressing Drug Resistance Beyond Kinase Domain Mutations (ID 11404)

      11:30 - 11:50  |  Presenting Author(s): Robert C. Doebele

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    MS10 - Part Solid Nodules, GGN and STAS (ID 789)

    • Event: WCLC 2018
    • Type: Mini Symposium
    • Track: Treatment of Early Stage/Localized Disease
    • Presentations: 5
    • Moderators:
    • Coordinates: 9/24/2018, 15:15 - 16:45, Room 206 F
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      MS10.01 - Radiographic Differences Between Presumed AIS and MIA (ID 11440)

      15:15 - 15:30  |  Presenting Author(s): Mini Pakkal

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      Abstract not provided

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      MS10.02 - Importance of CT in the Pathologic Assessment of Tumor Sized in Subsolid and Part-Solid Adenocarcinoma (ID 11441)

      15:30 - 15:45  |  Presenting Author(s): Erik Thunnissen

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      MS10.03 - CT Versus Needle Biopsy Assessment Before Resection of Part Solid Nodules (ID 11442)

      15:45 - 16:00  |  Presenting Author(s): Young Tae Kim

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      MS10.04 - Therapeutic Implications of Spread Through Air Spaces (STAS) (ID 11443)

      16:00 - 16:15  |  Presenting Author(s): William D Travis  |  Author(s): Rania Gaber, Shaohua Lu, Takashi Eguchi, Natasha Rekhtman, Prasad S. Adusumilli

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      Abstract not provided

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      MS10.05 - Should We Resect GGNs (ID 11444)

      16:15 - 16:30  |  Presenting Author(s): Kenji Suzuki

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    MS16 - Implementation of Lung Cancer Screening (ID 795)

    • Event: WCLC 2018
    • Type: Mini Symposium
    • Track: Screening and Early Detection
    • Presentations: 5
    • Moderators:
    • Coordinates: 9/25/2018, 13:30 - 15:00, Room 206 F
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      MS16.01 - CMS Approved ACR Lung Cancer Screening Registry in the United States (ID 11468)

      13:30 - 13:45  |  Presenting Author(s): Ella Kazerooni

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      Abstract not provided

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      MS16.02 - NELCIN B3 Screening Program in China (ID 11469)

      13:45 - 14:00  |  Presenting Author(s): Qinghua Zhou

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      Abstract not provided

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      MS16.03 - Recruitment Strategies for the Lung Cancer Screening (ID 11470)

      14:00 - 14:15  |  Presenting Author(s): Gail Elizabeth Darling

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      MS16.04 - National Lung Screening Program in Taiwan (ID 11471)

      14:15 - 14:30  |  Presenting Author(s): Pan-Chyr Yang

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      MS16.05 - Optimal Approach to Integrate Smoking Cessation into Screening Program (ID 11472)

      14:30 - 14:45  |  Presenting Author(s): Matthew Eric Callister

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    MS22 - Biology of the Lung and Lung Cancer (ID 800)

    • Event: WCLC 2018
    • Type: Mini Symposium
    • Track: Biology
    • Presentations: 6
    • Moderators:
    • Coordinates: 9/26/2018, 10:30 - 12:00, Room 206 F
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      MS22.01 - Lung Development and Stem Cells (ID 11490)

      10:30 - 10:45  |  Presenting Author(s): Samuel Rowbotham  |  Author(s): Joo-Hyeon Lee, Carla Kim

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      MS22.02 - Epigenetic Alterations in Lung Cancer Development (ID 11491)

      10:45 - 11:00  |  Presenting Author(s): Wan Lam

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      MS22.03 - Non-Coding RNA in Lung Cancer (ID 11492)

      11:00 - 11:15  |  Presenting Author(s): Sven Diederichs

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      MS22.04 - Genomics of Resistance and Response in Lung Cancer (ID 11493)

      11:15 - 11:30  |  Presenting Author(s): Marc Ladanyi

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      MS22.05 - Inflammation in Lung Cancer (ID 11494)

      11:30 - 11:45  |  Presenting Author(s): Katerina Politi

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      MS22.06 - Transcriptomic-Metabolomic Reprograming as Resistant Mechanism (ID 11495)

      11:45 - 12:00  |  Presenting Author(s): Patrick C Ma  |  Author(s): XIaoliang Wu, Zuan-Fu Lim, Satoshi Komo

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    MS29 - Selection into Screening Programs: Interplay of Risk Algorithms, Genetic Markers and Biomarkers (ID 807)

    • Event: WCLC 2018
    • Type: Mini Symposium
    • Track: Screening and Early Detection
    • Presentations: 6
    • Moderators:
    • Coordinates: 9/26/2018, 13:30 - 15:00, Room 206 F
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      MS29.00 - Introduction with Poll Slides (ID 14933)

      13:30 - 13:35  |  Presenting Author(s): Betty Tong, John R Goffin

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      Abstract not provided

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      MS29.01 - Assessment of Risk Prediction Algorithms for Entry into Screening Programs (ID 11525)

      13:35 - 13:50  |  Presenting Author(s): Martin Tammemägi

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      MS29.02 - Defining Screening Frequency &amp; Duration Using Risk Prediction Algorithms and CT Image Findings (ID 11526)

      13:50 - 14:05  |  Presenting Author(s): Kevin ten Haaf

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      MS29.03 - Polygenic Risk Score for Risk Assessment (ID 11527)

      14:05 - 14:20  |  Presenting Author(s): Rayjean J. Hung  |  Author(s): Yonathan Brhane, Nilanjan Chatterjie, David C Christiani, Neil Caporaso, Maria Teresa Landi, Loic Le Marchand, Geoffrey Liu, Stephen Lam, John Kirkpatrick Field, Paul Brennan, Christopher Ian Amos

      • Abstract
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      MS29.04 - LuCID Exhaled Breath Analysis (ID 11528)

      14:20 - 14:35  |  Presenting Author(s): Marc Phillipe Van Der Schee  |  Author(s): Edoardo Gaude, Jasper Boschmans, Billy Boyle, Robert Campbell Rintoul, Robert Smith, Anna Battista

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      MS29.05 - Early Detection Biomarker Development: Is Success on the Horizon? (ID 11529)

      14:35 - 14:50  |  Presenting Author(s): Peter Mazzone

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    MTE01 - Preclinical Models of Lung Cancer (Ticketed Session) (ID 811)

    • Event: WCLC 2018
    • Type: Meet the Expert Session
    • Track: Biology
    • Presentations: 2
    • Moderators:
    • Coordinates: 9/24/2018, 07:00 - 08:00, Room 206 F
  • +

    MTE14 - Nodule Management (Pro Con Debate and Case Presentations) (Ticketed Session) (ID 824)

    • Event: WCLC 2018
    • Type: Meet the Expert Session
    • Track: Screening and Early Detection
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/25/2018, 07:00 - 08:00, Room 206 F
    • +

      MTE14.01 - Nodule Management (Pro Con Debate and Case Presentations) (ID 11570)

      07:00 - 08:00  |  Presenting Author(s): Stephen Lam, Matthijs Oudkerk

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