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James L Mulshine



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    MTE04 - Comparison of Various Risk Models (Ticketed Session) (ID 814)

    • Event: WCLC 2018
    • Type: Meet the Expert Session
    • Track: Screening and Early Detection
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/24/2018, 07:00 - 08:00, Room 205 AC
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      MTE04.02 - Where Should Health Programs Set Threshold for Tailored Screening? (Now Available) (ID 11553)

      07:30 - 08:00  |  Presenting Author(s): James L Mulshine

      • Abstract
      • Presentation
      • Slides

      Abstract

      Since the publication of the U.S. Preventive Services Task Force recommendation statement on lung cancer screening much discussion has focused on what is the critical information required to make an informed decision regarding the benefit of undergoing thoracic CT screening (1). Ever more sophisticated modeling approaches are being developed to better characterize the risk: benefit consequences of screening. This session will explore the current state of this complex issue. Yet as screening implementation builds momentum, more information is emerging about the information gleaned from thoracic CT obtained in a population of heavily tobacco-exposed individuals that may profoundly effect the screening health benefit discussion.

      A comprehensive analysis of diseases, injuries and risk factors across the United States from 1990 to 2016 was recently reported by a jointly sponsored consortium from the National Institutes of Health and The Bill and Melinda Gates Foundation, as a guide to investment for research, care and public health policy in the United States (2). According to that report, lung cancer including both the trachea and the bronchi was and remains the second leading cause of years of life lost across the 26 year time interval of that study due to an increase by 26.8% in the number of lung cancer deaths. In that analysis, the most lethal disease process was ischemic heart disease (IHD) which accounted for over 544,000 deaths in 2016. Even though, there was a 15% reduction in IHD mortality since 1990, ischemic heart disease still results in over 2.84 times more deaths than lung cancer. However, for both of these diseases, the age-standardized death rate is fortunately declining.

      In contrast for the third leading cause of death, chronic obstructive pulmonary disease (COPD), over that same 26 year interval, the total number of deaths has increased by 86.9%. Collectively, these three diseases, IHD, lung cancer and COPD account for over 44% of the mortality from the top 25 causes of years of life lost in 2016.

      As we consider risk developing risk models for lung cancer screening, it is useful to step back and consider the information being shared with the individual considering their screening benefit. Currently, in the United States that person being screened is most likely an over 55 years old, current or former smoker with over 30 pack year exposure to tobacco combustion products. As we have just reviewed, the most likely determinants of that individual’s life expectancy are the three most lethal diseases, IHD, lung cancer and COPD.

      Even as we are beginning to screening tobacco-exposed populations, we know that there large numbers of individuals found in the course of their lung cancer screening CT, who will also be found that have asymptomatic but objective evidence of COPD or coronary calcification (3-7). For both IHD and COPD, NIH is encouraging measures to improve the early detection of these two major diseases so that pre-emptive strategies can be employed, before the development of symptoms and avoid the disabling burden of largely incurable advanced disease. Guidelines have already been published for managing the extent of coronary calcium found on thoracic CT scans as promulgated by cardiac professional societies (8). In parallel developments, the pulmonary community is also finding compelling evidence for cardiovascular disease when evaluating for COPD (9). Finding from both of these thoracic CT-detected diseases are frequently being reported on the radiologists’ report for lung cancer screening.

      Considerable progress has been made in developing predictive risk models for lung cancer in the screening setting (10, 11). However, from a screening subjects’ perspective, a lung cancer-only risk analysis does not include the vast majority of risk-for-death information that is relevant to a heavy smoker that could be available on their screening CT in regard to the first and third leading cause of death (IHD or COPD) (2-9). Therefore when considering developing future risk outcomes tools for an individual deciding on whether or not to undergo CT screening for lung cancer, we perhaps need a more inclusive evaluation of health outcomes that consider the major knowable consequences of extensive tobacco exposure. The most recent Surgeon General's Report released in 2014 and summarizing 50 years of studying tobacco health consequences, reaffirmed the causal inference of tobacco smoke to a lengthy list of diseases including most prominently, cancers, cardiovascular disease and chronic obstructive pulmonary disease (12). In discussions about other major chronic diseases such as diabetes or hypertension, people are educated about the multi-organ involvement of these diseases, so they have the information to better protect their health.

      The three leading causes of loss of life (IHD, lung cancer and COPD) in the United States cumulatively account for over 13,500 years of loss of life per year. However, from a heavily tobacco-exposed individual’s perspective, lung cancer only accounts for 26% of this mortality burden. A thoracic CT scan can provide actionable risk information for all three leading tobacco-related causes of death. The most recent draft research plan for the United States Preventive Services Task Force is explicitly evaluating lung cancer screening outcomes for impact on all-cause mortality. It is a critical time to consider more comprehensive tools to transparently inform about the relevant health information available with the use of thoracic CT imaging in heavily tobacco-exposed individuals.

      References:

      1) Moyer VA; U.S. Preventive Services Task Force. Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2014 Mar 4;160(5):330-8. doi: 10.7326/M13-2771.

      2) PMID: 24378917The Burden of Disease Collaborators; Mokdad AH, Murray CJL, Khan AR, et al. The state of US health, 1990-2016: burden of diseases, injuries, and risk factors among US states. JAMA. doi:10.1001/jama.2018.0158.

      3)Seijo LM and Zulueta JJ. Understanding the links between lung cancer, COPD and emphysema: A key to more effective treatment and screening. Oncology 2017; 31: 93-100.

      4) Shemesh J, Henschke CI, Shaham D, et al. Ordinal scoring of coronary artery calcifications on low-dose CT scans of the chest is predictive of death from cardiovascular disease. Radiology. 2010;257(2):541-548.

      5) Chiles C, Duan F, Gladish GW, et al. Association of Coronary Artery Calcification and Mortality in the National Lung Screening Trial: A Comparison of Three Scoring Methods. Radiology. 2015;276(1):82-90.

      6) Takx RA, de Jong PA, Leiner T, et al. Automated coronary artery calcification scoring in non-gated chest CT: agreement and reliability. PLoS One. 2014 Mar 13;9(3):e91239. doi: 10.1371/journal.pone.0091239. eCollection 2014.

      7) Malcolm KB, Dinwoodey DL, Cundiff MC et al. Qualitative coronary artery calcium assessment on CT lung screening exam helps predict first cardiac events. J Thorac Dis. 2018. 10: 2740-2751 doi: 10.21037/jtd.2018.04.76.

      8) Harvey S. Hecht, Paul Cronin, et al.SCCT/STR guidelines for coronary artery calcium scoring of noncontrast noncardiac chest CT scans: A report of the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology. Journal of Cardiovascular Computed Tomography, Volume 11: 74-84, 2016.

      9) Bhatt SP, Kazerooni EA, Newell JD Jr et al. Visual estimate of coronary artery calcium predicts cardiovascular disease in COPD, CHEST (2018), doi: 10.1016/j.chest.2018.05.037.

      10) ten Haaf K, Jeon J, Tammemägi MC et al. Risk prediction models for selection of lung cancer screening candidates: a retrospective validation study., PLoS Med, 2017, vol. 14 pg. e1002277.

      11) Katki HA, Kovalchik SA, Petito LC, et al. Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening. Ann Intern Med. 2018 May 15. doi: 10.7326/M17-2701. [Epub ahead of print].

      12) US Department of Health and Human Services, The Health Consequences of Smoking: 50 Years of Progress: a Report of the Surgeon General, 2014 Atlanta, GAUS Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.

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    S01 - IASLC CT Screening Symposium: Forefront Advances in Lung Cancer Screening (Ticketed Session) (ID 853)

    • Event: WCLC 2018
    • Type: Symposium
    • Track: Screening and Early Detection
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/23/2018, 07:00 - 12:00, Room 203 BD
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      S01.18 - IASLC Leads the International Collaboration on Data Sharing (IASLC- ELIC-CCTRR) (Now Available) (ID 11899)

      11:30 - 11:50  |  Presenting Author(s): James L Mulshine

      • Abstract
      • Presentation
      • Slides

      Abstract

      The IASLC ELIC-CCTR vision is to create a globally-accessible, privacy-secured environment to enable the analysis and study of extremely large collections of quality-controlled internationally assembled CT lung cancer images and associated biomedical data for research and healthcare delivery. This initiative will rapidly accelerate improvements to the multi-disciplinary management of early curable, lung cancer and other major thoracic diseases. This new research environment will be deployed and used to conduct global studies within the first two years of this project and is designed to one day scale to enabling coherent analysis across millions of cases.

      The current problem is that the implementation and advancement of lung cancer low dose CT screening (LDCT) screening requires large and high-quality collections of data obtained from global populations with currently deployed scanning equipment 1-5. Furthermore, there are new opportunities to develop deep learning methods for lung cancer imaging, which requires large quality-controlled datasets. As a community we have to very aware of the privacy challenges around data sharing. Lack of high quality data has been a barrier to LDCT screening progress.

      The way forward has been developed at the recent IASLC Confederation of CT Screened Patients Registry & Resource (CCTRR) Roundtable Workshop, as outlined in figure 1.

      figure 1.jpg

      IASLC will develop and run a new international collaborative (the ELIC framework) building on the processes established in the successful TNM Staging project. An internationally-federated Hub and Spoke system will be deployed to permit analysis of CT images and associated data in a secure environment, without any requirement to reveal data itself (i.e. privacy-protecting). No identifiable data ever leaves sources under local governance (PI) control. Existing imaging collections remain in the geographic regions where they were collected, so the resulting environment remains consistent with local regulations without privacy or data disclosure risk. In addition to connecting the world’s largest lung cancer screening registries, which is necessary for exploiting advanced computing capabilities with trustworthy security, enabling the rapid ramp up and participation of new global screening groups.

      The structure will provide the ability to interrogate large, high-quality, and internationally sourced image data sets will allow the lung cancer screening community to identify key insights, publish studies, and make lung cancer recommendations based on potentially millions of screening participants. By validating and distributing common data standards for CT imaging as well as for additional clinical follow-up information, the framework can be applied to the collaborative study of related intrathoracic disease processes.

      1. Henschke CI, McCauley DI, Yankelevitz DF, et al. Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 1999; 354(9173): 99-105.

      2. National Lung Screening Trial Research T, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011; 365(5): 395-409.

      3. van Klaveren RJ, Oudkerk M, Prokop M, et al. Management of lung nodules detected by volume CT scanning. N Engl J Med 2009; 361(23): 2221-9.

      4. Tammemagi MC, Schmidt H, Martel S, et al. Participant selection for lung cancer screening by risk modelling (the Pan-Canadian Early Detection of Lung Cancer [PanCan] study): a single-arm, prospective study. Lancet Oncol 2017; 18(11): 1523-31.

      5. Field JK, Duffy SW, Baldwin DR, et al. The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer. Health Technol Assess 2016; 20(40): 1-146.

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