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Ugo Pastorino
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ES08 - Critical Concerns in Screening (ID 11)
- Event: WCLC 2019
- Type: Educational Session
- Track: Screening and Early Detection
- Presentations: 7
- Now Available
- Moderators:Ugo Pastorino, John Kirkpatrick Field
- Coordinates: 9/08/2019, 13:30 - 15:00, Copenhagen (1980)
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ES08.01 - Participation of the Target Population in Lung Cancer Screening (Now Available) (ID 3191)
13:30 - 15:00 | Presenting Author(s): Robin Cornelissen
- Abstract
- Presentation
Abstract
Participation of the Target Population in Lung Cancer Screening
Robin Cornelissen, MD, PhD.
Erasmus MC cancer institute
Rotterdam, The Netherlands
The two largest randomized controlled trials performed, The National Lung Screening Trial (NLST) and the Nederlands-Leuvens Longkanker ScreeningsONderzoek (NELSON) 1,2, proved that lung cancer screening using low dose CT scan, resulted in a significant reduction in lung cancer mortality. Following the results of the NLST trial, lung cancer screening was initiated in the United States and Canada. However, the uptake of lung cancer screening is poor, with only 3% to 4% of all eligible persons participating in the implemented screening program 3. Given more recent positive results of the NELSON study that were presented at the World Conference on Lung Cancer last year in Toronto, lung cancer screening is now considered in many countries across the globe. This low uptake of lung cancer screening is however a cause of concern.
The reasons for the low participation rate are multi-factorial. The novelty of the lung cancer screening program is such a factor, resulting in lower uptake and might be the easiest one to address. The identification of the target population is more challenging due to the fact that the population to be screened is more defined than just age and sex. In addition, the lower socioeconomic status, which presents a significant portion of the to be screened population, and those who face barriers to care present a major challenge for implementing a successful screening program with a satisfactory uptake rate.
Several strategies have been proposed to improve lung cancer screening uptake.
In the socioeconomically deprived and heavy smoking communities, lung cancer is perceived as an uncontrollable disease 4, while cure rates in yearly screening programs lead to a cure in the majority of patients when lung cancer is detected 5,6. Therefore, public awareness of the curability of lung cancer when screening programs are implemented could boost the participation rate.
Mobile lung cancer testing in supermarket car parks proved to be a successful pilot 7. This strategy avoids difficulties relating to the distance of travel, lack of public transport available, and the cost of either the journey itself or hospital parking. This strategy is currently explored in a larger cohort.
One potential intervention that is being evaluated in clinical trials to improve the uptake and implementation of lung cancer screening is a patient navigator. A navigator can be a layperson, a medical assistant, or a nurse who will directly contact potential candidates for lung cancer screening for enrollment 3.
The Accelerate, Coordinate, Evaluate (ACE) Programme, initiated in the United Kingdom, is an early diagnosis of cancer initiative focused on testing innovations that either identify individuals at high risk of cancer earlier 8. This program consists of several individual programs in different regions of the UK, of which The Liverpool Healthy Lung Programme is a participant. Among other goals, this initiative tries to improve uptake in the hard to reach cohort. They used general practitioners’ records to invite participants meeting the criteria to a ‘Lung Health Check’. This ‘Lung Health Check’ is a novel approach that may overcome or minimize the emotional barriers associate with the term “lung cancer screening”. This method resulted in an uptake level up to 40% 9. This initiative is an example that a higher uptake rate is indeed possible, even in the hard to reach population.
At the IASLC World Conference on Lung Cancer in Barcelona, the issues regarding participation of the target population in lung cancer screening will be addressed and possible strategies will be discussed to overcome these challenges. As lung cancer screening is yet to be implemented in the majority of countries worldwide, we now have a unique opportunity to test and apply these strategies to successfully implement lung cancer screening in order to reduce lung cancer mortality.
References
1. The National Lung Screening Trial Research Team. Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening. N Engl J Med. 2011;365(5):395-409. doi:10.1056/NEJMoa1102873
2. Koning HD, Aalst CVD, Haaf KT, Oudkerk M. PL02.05 Effects of Volume CT Lung Cancer Screening: Mortality Results of the NELSON Randomised-Controlled Population Based Trial. J Thorac Oncol. 2018;13(10):S185. doi:10.1016/j.jtho.2018.08.012
3. Triplette M, Thayer JH, Pipavath SN, Crothers K. Poor Uptake of Lung Cancer Screening: Opportunities for Improvement. J Am Coll Radiol JACR. 2019;16(4 Pt A):446-450. doi:10.1016/j.jacr.2018.12.018
4. Quaife SL, Marlow LAV, McEwen A, Janes SM, Wardle J. Attitudes towards lung cancer screening in socioeconomically deprived and heavy smoking communities: informing screening communication. Health Expect Int J Public Particip Health Care Health Policy. 2017;20(4):563-573. doi:10.1111/hex.12481
5. Survival of Patients with Stage I Lung Cancer Detected on CT Screening. N Engl J Med. 2006;355(17):1763-1771. doi:10.1056/NEJMoa060476
6. Jonnalagadda S, Bergamo C, Lin JJ, et al. Beliefs and attitudes about lung cancer screening among smokers. Lung Cancer Amst Neth. 2012;77(3):526-531. doi:10.1016/j.lungcan.2012.05.095
7. Wise J. Mobile lung cancer testing in supermarket car parks is to be expanded. BMJ. 2017;359:j5450. doi:10.1136/bmj.j5450
8. Proactive Approaches to Individuals at High Risk of Lung Cancer; Accelerate, Coordinate, Evaluate (ACE) Programme. V1.1a.; 2018. https://www.cancerresearchuk.org/sites/default/files/ace_proactive_lung_report_with_economic_evaluation_final_version_1.1a.pdf. Accessed July 9, 2019.
9. Ghimire B, Maroni R, Vulkan D, et al. Evaluation of a health service adopting proactive approach to reduce high risk of lung cancer: The Liverpool Healthy Lung Programme. Lung Cancer. 2019;134:66-71. doi:10.1016/j.lungcan.2019.05.026
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ES08.02 - Nodule Growth Assessment (Now Available) (ID 3192)
13:30 - 15:00 | Presenting Author(s): Matthijs Oudkerk
- Abstract
- Presentation
Abstract
In the past 15 years several lung cancer screening trials have been performed in Europe1. Experts involved in these trials recently published a position paper in the Lancet Oncology2.
Several conclusions and recommendations were drawn to enable a smooth and timely implementation of lung cancer screening in Europe. The experts made a strong and conditional argument on the methodology of lung cancer screening by low-dose computed tomography (CT). Quality control by regular CT phantom testing enabling standardization of CT data acquisition as well as benchmarking of CT software post processing and data analysis are mandatory. It is promoted to execute the CT screening Q/A control through national reference centers similar to the organizational structure of breast screening programs. In this manner the CT screening programs can be implemented in a responsible way avoiding the detrimental side effects of too high false positive CT outcome rates on the one hand and keeping up the most effective lung cancer early detection rate on the other hand.
Apart from the acquisition protocol, the CT lung nodule analysis methodology is a critical factor for successful implementation of CT lung cancer screening 3. The diameter based NLST protocol used a 4 mm threshold (~ 30 mm3) as significant suspicion for malignancy. This approach yielded a positive rate of approximately 27% in the baseline round with a very low positive predictive value for lung cancer of 3.8%4. The NELSON study introduced a nodule volume analysis and a volume doubling time methodology with 2 CT measurements with a 3-month interval to calculate the volume doubling time as a biomarker for growth rate in indeterminate nodules. This approach resulted in a 2.6% positive rate in the baseline round with a high positive predictive value for lung cancer of approximately 36%, which is within the criteria needed for lung cancer screening implementation3. In the meantime, a ten times higher threshold of 8 mm (~300 mm3) was recommended to correct the high false positive rate of the NLST diameter methodology by several international societies5. After the publications of the NELSON data on increased lung cancer probability in baseline nodules at a threshold of 100 mm3the US guideline recommendations shifted from 300 mm3to 100 mm3(~ 6mm)6. A direct comparison of diameter and volume protocols cannot be performed through the assumption that all nodules are spherical. While this approach was chosen in a recent publication of the IELCAP investigators7, even the slightest correction for the assumption of sphericity reveals the substantial inferiority of diameter protocols. At follow-up CT examination at annual incident screen new nodules represent a high lung cancer probability at lower volumes than at baseline screen8,9. The upper threshold is at 200 mm3as indication for further clinical workup while new nodule at incident screen between the 30-200 mm3are classified as indeterminate and need a repeat scan at 3 months to calculate the volume doubling time. Lung cancer screening should be integrated in a defined national program and therefore opportunistic screening is not recommended. Calcium scoring as a screening methodis not yet established as a validated tool for early detection of coronary artery disease and the outcomes of the ROBINSCA study (risk or benefit in screening for cardiovascular disease www.robinsca.nl) are being awaited. Thus, so far, it is not indicated as a combined clinical routine screening methodology since ECG triggering is mandatory10. Non-triggered CT coronary artery calcium scoring will result in high false negative percentages. A lower CT radiation exposure threshold at a DLP of 50 mGy or 0.6 mSv is defined to assure the calibration of the quantitative imaging biomarkers for lung nodule detection. Lower radiation doses will induce false negative and unreliable growth rate results.
References
1 An update on the European Lung Cancer Screening Trials and Comparison of the Lung Cancer Screening Recommendations in Europe . Han et alJournal of Thoracic Imaging 2019; 34(1): 65–71.
2 European position statement on lung cancer screening Oudkerk M Devaraj ALancet Oncology 2017 Dec;18(12):e754-e766.
3 Management of lung nodules detected by volume CT scanning van Klaveren R Oudkerk M et al N Engl J Med. 2009 Dec 3;361(23):2221-9.
4 Reduced lung-cancer mortality with low-dose computed tomographic screening Aberle DR et al N Engl J Med 2011 Aug 4;365(5):395-409.
5 CT screening for lung cancer: alternative definitions of positive test result based on the national lung screening trial and international early lung cancer action program databases Yip R Henschke CI Radiology 2014 Nov;273(2):591-6.
6 Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017 Mac Mahon H Radiology: Volume 284: Number 1—July 2017
7 CT screening for lung cancer: comparison of three baseline screening protocol Henschke CI et al Eur Rad 2018 Dec 3
8 Occurrence and lung cancer probability of new solid nodules at incidence screening with low-dose CT: analysis of data from the randomised, controlled NELSON trial Walter JE Heuvelmans MA et al Lancet Oncology 2016 Jul;17(7):907-916.
9.Persisting new nodules in incidence rounds of the NELSON CT lungcancer screening study Walter JE Heuvelmnans MA Thorax. 2018 Dec 27
10 Can nontriggered thoracic CT be used for coronary artery calcium scoring? A phantom study Xueqian Xie et al Medical Physics, Vol. 40, No. 8, August 2013
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ES08.03 - The Magnitude of the Benefit (Now Available) (ID 3193)
13:30 - 15:00 | Presenting Author(s): David F. Yankelevitz
- Abstract
- Presentation
Abstract
Why do people get screened? The obvious answer is so that cancer can be detected early with a view towards a higher chance of cure with early treatment. Therefore the critical questions that must be addressed relate to the risk of cancer over time and then, how likely cure will be when screen-detected versus clinically detected. Current approaches to evaluate screening have relied on randomized controlled trials with a view towards demonstrating that a benefit actually exists but are not designed to quantify the magnitude of the benefit. Current trial designs have limited rounds of screening and long-term follow up after screening has stopped. When these parameters change, the results of the trial will also change. Several approaches currently exist to estimate that critical parameter regarding the curability of screen detected lung cancer. This includes modeling approaches which can use data extracted from a variety of sources, they can also be measured directly as was done in the I-ELCAP study which measures directly the reduction in case fatality rate by using long term survival as a measure of cure, and an additional approach would be to screen continuously in the context of a clinical trial and measure the reduction in mortality after several years of screening where the benefit of screening reaches its maximum and becomes equivalent to the reduction in case fatality rate. When applied to lung cancer it can be shown that this benefit is far greater than the 20% so commonly reported and instead is in the 60=80% range for cure. Were this to be fully understood the entire rationale behind requiring shared decision making would be called into question as it was thought that the balance between benefits and harms was so tenuous that shared decision making was necessary.
When considering whether a particular type of screening is to be considered beneficial there is also a tendency to compare different types of screening and seeing how many screens are necessary to save a life. Here to, this approach suffers from the same mistake. Each of those screening exams estimates this number based on their own randomized trial and each of these differ in terms of the design parameters, therefore the comparisons are essentially meaningless.
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ES08.04 - Management Algorithms (Now Available) (ID 3194)
13:30 - 15:00 | Presenting Author(s): Claudia I Henschke | Author(s): Rowena Yip, Teng Ma, Samuel Miguel Aguayo, Javier Zulueta, David Yankelevitz
- Abstract
- Presentation
Abstract
Introduction
Clinical management decisions arising from the first, baseline round of screening for lung cancer are most challenging, as nodules that are seen for the first time may have accumulated over a lifetime and almost all of them are of no clinical concern [1]. In contrast, new or changing findings on subsequent annual repeat low-dose CT scans (LDCTs) have much greater clinical significance.
Efficiency is particularly important in the baseline round in order to minimize unnecessary harms caused by work-up within the 12 months after the baseline LDCT. Potential workup includes surgery, biopsies, and diagnostic tests requiring intravenous injection (e.g., PET scans, contrast CT). Biopsies and surgery have greater risks than LDCT, and thus the management protocols should aim to minimize these higher risk procedures as much as possible [2]. It is also important not to discourage participants undergoing the baseline round from future participation in annual rounds as these provide the real benefit of annual LDCT screening.
Methods
We compared the efficiency of three published baseline LDCT screening protocols [2], the International Early Lung Cancer Action Program (I-ELCAP) [3], American College of Radiology (ACR)-LungRADS [4], and the European Consortium protocols [5] for participants 50 years of age or older with at least 20 pack-years of smoking.
The three protocols provide recommendations for immediate workup, 3-month and 6-month LDCT as shown in Table 1 [1]. The three protocols use the diameter of the entire solid and nonsolid non-calcified nodule (NCN), but differ for part-solid NCNs. For part-solid NCNs, I-ELCAP uses the diameter of the solid component [6], while ACR-LungRADS uses both the entire diameter of the part-solid NCN as well as the diameter of its solid component. The European Consortium protocol determines the volume of a solid NCN using their software [5], but also specifies the equivalent diameter values for the entire part-solid and nonsolid NCNs as volumetric measurements for these are problematic as was recognized [5]. Measurement error and rounding of measurements are also an important consideration [7,8].
Efficiency was defined as an efficiency ratio (ER): the number of participants recommended for a particular workup divided by the resulting number of participants diagnosed with lung cancer [2]. An ER of 1 would mean that each recommended workup resulted in a diagnosis of lung cancer. An optimum ER has not been established for lung cancer, but it has been suggested that for lung surgery, a rate of 10% for non-malignant resections is desirable (9), this would be an ER of 1.1. In breast cancer biopsies which have a much lower risk than lung biopsies, it is recommended that 40% of biopsies should be negative to ensure sufficient workup to diagnose breast cancers early enough this would represent an ER of 1.4
Results
Table 1 provides the frequency of following the recommendations, the number of cancers diagnosed and the ER for each protocol. In summary, I-ELCAP recommendations had the lowest ER values for overall, immediate and delayed workup, and for potential biopsies.
Discussion
All three protocols used LDCT to guide evaluation of NCNs, particularly for the smaller NCNs. LDCT is a very low risk test as it requires no injection of contrast, the radiation dose is deemed “small” and “hypothetical” by the American Association of Physicists in Medicine [10], and the charge for a LDCT is 10-20 times lower than for a PET scan. This underscores the recognition that LDCT is a very useful tool for identifying growth at a malignant rate prior to further invasive testing.
The main point is that the definition of a “positive result” needs to be continually reevaluated and updated in light of emerging technology and evidence from ongoing screening programs with the goal of reducing unnecessary invasive procedures for non-malignant pulmonary NCNs, which will markedly reduce the concerns about potential harms and increase the benefit by early diagnosis and treatment of small, early curable lung cancers.
References
1. Henschke CI, Salvatore M, Cham M, Powell CA, DiFabrizio L, Flores R, et al. Baseline and annual repeat rounds of screening: implications for optimal regimens of screening. Eur Radiol. 2018; 28:1085-1094.
2. Henschke CI, Yip R, Ma T, Aguayo SM, Zulueta J, Yankelevitz DF, for the I-ELCAP Investigators. CT screening for lung cancer: comparison of three baseline screening protocols. Eur Radiol 2018; 29:3321-3322.
3. International Early Lung Cancer Action Program protocol. (2016) www.IELCAP.org/sites/default/files/I-ELCAP-protocol.pdf Accessed June 27, 2019
4. American College of Radiology (ACR). Lung CT screening reporting & data system (Lung-RADS Version 1.0). https://www.acr.org/Quality-Safety/Resources/LungRADS
5. Oudkerk M, Devaraj A, Vliegenthart R, Henzler T, Prosch H, Heussel CP, et al. European position statement on lung cancer screening. Lancet Oncology 2017; 18: e754-e766.
6. Henschke CI, Yip R, Wolf A, Flores R, Liang M, Salvatore M, et al. CT screening for lung cancer: part-solid nodules in baseline and annual repeat rounds. AJR Am J Roentgenol 2016; 11:1-9.
7. Radiologic Society of North America Quantitative Imaging Biomarkers Alliance (QIBA) Calculator. (2017) http://accumetra.com/solutions/qiba-lung-nodule-calculator. Accessed May 1, 2018.
8. Li K, Yip R, Avila R, Henschke CI, Yankelevitz DF. Size and growth assessment of pulmonary nodules: consequence of the rounding. J Thorac Oncol 2016; 12: 657-62.
9. Flores R, Bauer T, Aye R, et al. Balancing curability and unnecessary surgery in the context of computed tomography screening for lung cancer. J Thorac Cardiovasc Surg. 2014; 147:1619-26.
10. American Association of Physicists in Medicine. AAPM Position Statement on Radiation Risks from Medical Imaging Procedures. https://www.aapm.org/org/policies/details.asp?id=406&type=PP Accessed June 27, 2019
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ES08.05 - Advances in Artificial Intelligence - How Lung Cancer CT Screening Will Progress? (Now Available) (ID 3195)
13:30 - 15:00 | Presenting Author(s): Debora Gil | Author(s): Antoni Rosell
- Abstract
- Presentation
Abstract
Predictive models for personalized medicine (also known as radiomics) is a recent discipline that uses sophisticated image analysis and artificial intelligence (AI) methods to obtain quantitative image-based features that correlate to final diagnosis and treatment outcome [1].
The application of radiomics in lung cancer screening can represent a critical shift in this field. Some recent studies, like [2-3], show that radiomic features (including tumor shape descriptors and texture analysis) extracted from CT scans have significantly better predictive value than volumetry alone (AUC= 0.9 vs 0.74). Texture analysis reflects tumour heterogeneity and has recently introduced in PET images. In fact, PET texture analysis has demonstrated its value in establishing survival [4], predicting distant metastasis [5], detecting mutations and establishing radiotherapy doses [6]. However, and despite the promising results, there are some limitations like the low reliability of heterogeneity parameters in tumours with small volume, the low repeatability and reproducibility of textural features in the clinical setting and the limitation of the analytic methods.
A multi-radiomic model that could integrate morphological features from the CT together with biological characteristics from the PET and clinical risk factors (age, smoking history, contact with asbestos or family cancer background), would become a highly accurate diagnostic and prognostic method and, thus, make lung cancer screening programs cost-effective. However, in order that radiomics become the cornerstone for clinical decision-making, new machine learning and statistical strategies adapted to the specific requirements of clinical applications should be formulated.
A main pitfall in current state of the art AI methods is the use of generic machine learning and statistical tools borrowed from other fields of application which fall short under clinical conditions [7]. Predictive radiomic models for personalized medicine should address several specific challenges different from the ones common to other application areas of artificial intelligence. First, models should collect and integrate diverse multimodal data sources in a quantitative manner that delivers unambiguous clinical predictions. Second, models should also be easily interpreted from a clinical point of view to allow the analysis of the clinical factors that have an impact on the clinical decision. Third, predictions should be robust concerning data uncertainties due to the impact of collection conditions (like acquisition parameters or variability in manual annotations) and the presence of rare and/or outlying cases, which become highly influential for minority classes lead to overfitting.
This work reviews state-of-the-art AI methods for radiomics, the specific challenges that they must face in medical imaging applications and the latest advances for reliable personalized early diagnosis of lung cancer.
References
[1] P Lambin, et al, Radiomics: the bridge between medical imaging and personalized medicine, Nature Reviews,12, 749-53, 2017.
[2] Hawkins et al. Prediction of pathological nodal involvement by CT-based Radiomic features of the primary tumor in patients with clinically node-negative peripheral lung adenocarcinomas, Med. Phys. 45 (6), 2018.
[3] Peikert T et al. Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial, PLOS ONE 13(10), 2018.
[4] Ohri N, Duan F, Snyder BS, Wei B, Machtay M, Alavi A, et al. Pretreatment 18F-FDG PET textural features in locally Advanced non-small cell lung cancer: secondary analysis of ACRIN 6668/RTOG 0235. J Nucl Med.57:842–8, 2016.
[5] Wu J,Aguilera, et al. Early-stage non-small cell lung cancer: quantitative imaging characteristics of (18)F fluorodeoxyglucose PET/CT allow prediction of distant metastasis. Radiology, 281:270–8, 2016.
[6] Yip SS, et al. Associations between somatic mutations and metabolic imaging phenotypes in non-small cell lung cancer. J Nucl Med. 58:569–76, 2017.
[7] JP. Cohen et al, Distribution matching losses can hallucinate features in medical image translation, MICCAI 2018.
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ES08.06 - Cost Effectiveness of Comprehensive Screening and Smoking Cessation Programmes (Now Available) (ID 3196)
13:30 - 15:00 | Presenting Author(s): Bruce Pyenson
- Abstract
- Presentation
Abstract
There is broad consensus that lung cancer screening with low-dose CT is cost-effective. However, there has been slow take-up in the US where it is covered by commercial insurance and by the federal Medicare program.
One way to optimize LC screening is to consider screening as part of an integrated program that specializes in population health for the cluster of smoking-related illness. There are four components of this,
LC screening centers can provide high-quality screening and systematic follow-up and appropriate referrals
Imaging for LC screening can quantify cardiac calcification, COPD, and osteoporosis, all of which may be associated with smoking
LC screening centers can operate as a center for smoking cessation, exercise counseling, and adherence support
For the 1.5 million annual indeterminant pulmonary nodules in the US, LC screening centers can provide appropriate follow-up. The vast majority of such cases receive no follow-up.
There are both economic and financial consequences for integrated screening. The economic consequences are measured in cost-effectiveness. The financial consequences are attracting high-utilizing people away from lower-quality providers, which can offset the loss of income from treating late stage lung cancers.
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ES08.07 - System Approach to Screening Management (Now Available) (ID 3197)
13:30 - 15:00 | Presenting Author(s): Anthony P Reeves
- Abstract
- Presentation
Abstract
IASLC ES08 - Critical Concerns in Screening 2019
System Approach to Screening Management
Anthony P. Reeves
School of Electrical and Computer Engineering
Cornell University
Screening seeks to identify a specific disease or set of diseases at an early stage where therapy can be most effective. It involves application of a medical test or tests to a group of asymptomatic individuals at-risk for the disease. Only a very small fraction of the tested population will be expected to have the target disease. Thus, a system for managing the screening process focuses on a single complex protocol and differs significantly from the more traditional medical practice that has a focus on symptomatic diseases and medical conditions. Very high compliance with the protocol and timeliness in follow up actions are critical to extract the maximum benefit of the screening process and avoid unnecessary actions on the majority of the participants that do not have the disease.
System requirements for Lung Cancer Screening
Screening involves detection of early stage asymptomatic disease and timely follow-up to provide the maximum therapeutic benefit of early stage detection. This requires a system to track participants throughout the screening process, from initial contact to documentation of screening results to follow-up. To maintain the highest degree of quality and timeliness, the screening management system should be comprehensive for all the digital data in the screening program and incorporate the screening protocol in its design.
For lung cancer screening (LCS), the web-based I-ELCAP management system was implemented in 2000 [1] with integration of all screening functions into a single system, including: scheduling, data collection, follow-up, patient reports and QA reports. This system includes structured reports for all patient interactions and medical events. The screening protocol is built in to the system; hence, there are real-time checks on adherence to the screening protocol. Any deviations from the protocol, such as a missing report or appointment schedule are flagged for attention. In addition, the management system includes all acquired digital images linked to the patient records; physicians may review images from within the system. Finally, the system includes computer image analysis methods for automated pulmonary nodule detection and for nodule growth rate assessment.
Additional findings and Computer Aided Diagnosis
Since that early system implementation in 2000, the importance of additional findings for other organs visible in the chest CT scans have become apparent. The radiological structured reporting requirements have been increased to include findings of the heart, and the lungs (emphysema, COPD) which, with lung cancer, covers the three main causes of death for the high-risk screening population. The detailed reporting of the CT scan reading, especially once the initial baseline scan has been read, places an increased burden on the radiologist. To improve the program quality and to address the reading issues a number of additional automated computer analysis functions have been integrated into the system, Reeves et. al. (2017) [2]. These include measures for: coronary calcium, heart size, the aorta, pulmonary hypertension, emphysema, major airways, bone mineral density from thoracic vertebra, breast density, and liver density. In addition, an automated quality assessment of the CT scan itself is reported.
The role for AI in screening management
Recent advances in AI technology, including deep learning with convolutional neural networks, have increased the capabilities of computer aided diagnostics. A landmark paper by Gulshan et. al. (2016) [3] showed that an automated end-to-end review of eye fundus images for diabetic retinopathy to determine if a follow-up action was indicated could be effectively accomplished without requiring a human read of the images. Following this work a commercial product for this task is now available. A recent paper by Ardila et. al. (2019) [4] showed that, for LCS CT scans, a similar approach with a more complex system could be used for predicting cancer events in a manner similar to LungRADS. A challenge with this LCS study, compared to Gulshan diabetic retinopathy study, is the cost and reporting complexity of the former for training data. While the Gulshan study was prospective and trained on over 120,000 cases, the Ardila study was retrospective with a subset of the NLST data of around 10,000 cases and only considered lung cancer. These methods employ the natural advantage of computer analysis with respect to human readers in attention to detail and lack of fatigue. Further, modern AI methods when appropriately designed, can assimilate data from millions of cases, far beyond human capacity. Efficient large-scale documentation methods have been developed to address the data issue for LCS [2] in which over 25,000 cases have been documented for multiple diseases.
These studies move us closer to the point where the majority of the CT image report for LCS could be automatically completed and the role of the physician focused to reviewing a small number of the most significant findings.
References
1. Reeves, A. P., Kostis, W. J., Yankelevitz, D. F., and Henschke, C. I. A web-based database system for multi-institutional research studies on lung cancer. RSNA 87th Scientific Meeting 221 (Nov. 2001), 372
2. Reeves, A. P., Xie, Y., and Liu, S. Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation. Journal of Medical Imaging 4, 2 (2017), 024505.
3. Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., ... & Kim, R. (2016). Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. Jama, 316(22), 2402-2410.
4. Ardila, D., Kiraly, A. P., Bharadwaj, S., Choi, B., Reicher, J. J., Peng, L., ... & Naidich, D. P. (2019). End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nature medicine, 1.
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Author of
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MS18 - Role of Biomarkers in Lung Cancer Screening (ID 81)
- Event: WCLC 2019
- Type: Mini Symposium
- Track: Screening and Early Detection
- Presentations: 1
- Now Available
- Moderators:Luis M Montuenga, Luis M Seijo
- Coordinates: 9/10/2019, 14:30 - 16:00, Vancouver (2003)
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MS18.02 - Circulating Nucleic Acid Biomarkers (Now Available) (ID 3545)
14:30 - 16:00 | Author(s): Ugo Pastorino
- Abstract
- Presentation
Abstract
Encouraging results in lung cancer (LC) mortality reduction were obtained by the introduction of low dose computed tomography (LDCT) for lung cancer screening. The results of Nelson screening trial showed a 26% reduction in lung cancer mortality in the LDCT arm thus confirming the benefit of LC screening with LDCT already published by the NLST group (1).
In MILD trial we showed that at 10 years follow up the mortality reduction was even higher (-39%) proving that extended LDCT screening is effective in reducing lung cancer mortality (2).
Nonetheless, the development of non-invasive complementary biomarkers could be helpful to improve the efficacy of LDCT screening by improving LC risk prediction and defining personalised LDCT screening intervals as well as to decrease false positives identified by LDCT and monitor disease evolution in patients after curative resection.
The value of circulating tumor DNA (ctDNA) as a biomarker in advanced tumor stages is well established. However, its role in early lung cancer detection is still uncertain. The biggest technical challenge is sensitivity. Current efforts to develop next-generation sequencing (NGS) technologies to study ctDNA in the context of early detection might improve sensitivity in this context.
The scientific community is awaiting the results of the Circulating Cell-free Genome Atlas (CCGA) Study for early cancer detection, enrolling 15,000 participants in the United States and Canada. Plasma samples collected at baseline and during 5 years of follow-up will be analyzed by whole genome sequencing(WGS) for copy number variation(CNV), targeted DNA sequencing (a 507-gene panel), and whole genome methylome profiling. Preliminary results in an observational case-control setting include 95% specificity, high sensitivity for advanced lung cancer in 54 patients (85% for targeted sequencing, 91% for CNV WGS, and 93% for methylome profiling), and modest sensitivity for 63 patients with stage I to III lung cancer (48% for targeted NGS, 54% for CNV WGS, and 56% for methylome profiling)(3). Therefore, the generalizability of these findings to the screening setting is uncertain.
In order to implement lung cancer screening programs, we focused on circulating microRNAs which may reflect the contribution not only of the tumor but also of its microenvironment and the host. We developed a plasma miRNA Classifier (MSC) composed of 24 miRNAs which showed high performance in terms of sensitivity (87%) and specificity (81%) in 940 subjects enrolled in the MILD screening trial. The classifier was able to identify, in longitudinal plasma samples of the patients, a risk profile to develop LC up to two years before a significant tumor burden was visible at LDCT(4). These results prompted us to launch in 2013 a prospective screening trial, called bioMILD, to test the efficacy of a combined LDCT-MSC approach as forefront screening tests in a large cohort of 4119 smokers, 50 yrs or older. We succesfully completed the baseline of all the volunteers and executed a LDCT in 11,012 and miRNA test in 9,156 subjects. BioMILD has now reached the 3 yrs follow up for all subjects and 4.2 year median follow up for the all cohort. Analyses of the results are ongoing and will be presented.
Concerning the origin of the 24 miRNA, since the classifier was able to identify a risk profile to develop lung cancer up to two years before the radiological diagnosis, we hypothesized that that such circulating miRNAs could be released not merely by cancer cells but rather by the damaged lung microenvironment and the host response that may sustain tumor development. Using in vitro models and clinical samples we showed that c-miRNAs originated mostly from blood cells, with activated neutrophils showing modulation of the 24 miRNAs overlapping that observed in plasma of MSC positive subjects(5).
The role of immunity in modulating the risk of disease development remains to be elucidated, while it could have enormous impact in terms of prevention and early intervention. Therefore we characterized peripheral blood immune cell profiles as possible complementary biomarkers for risk assessment and analyzed their relationship with MSC. In a case control study of 40 lung cancer patients and 20 controls we found immune cell subpopulations differentially expressed between screening detected lung cancer patients and controls. Of interest an MSC high risk profile in patients was associated with specific circulating immune cell subsets including higher numbers of exausted T cells and monocytes/MDSC and lower cytotoxic T and NK cells. These findings suggest that MSC high risk profile might reflect an immunosuppressive status and prompted us to study the possible utility of MSC in lung cancer immunotherapy settings. Using a prospective cohort of 140 consecutive advanced NSCLC patients treated with immune checkpoints inhibitors we found that MSC either alone or in combination with PD-L1 expression in the tumor was associated with patients survival(6). Therefore, plasma MSC, reflecting an impaired tumor immune contexture, could supplement PD-L1 tumor expression to identify a subgroup of patients who do not benefit from immunotherapy.
References:
D.R. Aberle, A.M. Adams, C.D. Berg, et al.Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med, 365 (2011), pp. 395-409
Pastorino U, Silva M, Sestini S. et al. Prolonged Lung Cancer Screening Reduced 10-year Mortality in the MILD Trial. Ann Oncol. 2019 Apr 1.
GR. Oxnard T. Maddala E. Hubbell et al. Genome-widesequencing for early stage lung cancer detection fromplasma cell-free DNA (cfDNA): the Circulating CancerGenome Atlas (CCGA) study. Paper presented at: 2018 American Society of Clinical Oncology Annual Meeting.June 1–5, 2018; Chicago, IL
Sozzi G, Boeri M, Rossi M.et al. Clinical Utility of a Plasma-based microRNA Signature Classifier within Computed Tomography Lung Cancer Screening: A Correlative MILD Trial Study. J Clin Oncol. 2014 Mar 10;32(8):768-73.
Fortunato O, Borzi C, Milione M, et al.Circulating mir-320a promotes immunosuppressive macrophages M2 phenotype associated with lung cancer risk. Int J Cancer. 2019 Jun 1;144(11):2746-2761. doi: 10.1002/ijc.31988. Epub 2019 Jan 6.
Boeri M, Milione M, Proto C. et al. Circulating miRNAs and PD-L1 Tumor Expression Are Associated with Survival in Advanced NSCLC Patients Treated with Immunotherapy: a Prospective Study. Clin Cancer Res. 2019 Apr 1;25(7):2166-2173. doi: 10.1158/1078-0432.CCR-18-1981. Epub 2019 Jan 7.
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PL02 - Presidential Symposium including Top 7 Rated Abstracts (ID 89)
- Event: WCLC 2019
- Type: Plenary Session
- Track:
- Presentations: 1
- Now Available
- Moderators:Giorgio Vittorio Scagliotti, Ramon Rami-Porta
- Coordinates: 9/09/2019, 08:00 - 10:15, Barcelona (2005)
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PL02.04 - Blood MicroRNA and LDCT Reduce Unnecessary LDCT Repeats in Lung Cancer Screening: Results of Prospective BioMILD Trial (Now Available) (ID 907)
08:00 - 10:15 | Presenting Author(s): Ugo Pastorino
- Abstract
- Presentation
Background
The National Lung Screening Trial (NLST) showed that lung cancer (LC) screening by three annual rounds of low-dose computed tomography (LDCT) reduced lung cancer mortality, and MILD trial provided additional evidence that extended intervention beyond 5 years, with annual or biennial rounds, enhanced the benefit of screening. The new bioMILD trial tested the additional value of blood microRNA (miRNA) assay at the time of LDCT on a large series of volunteers, with the aim of targeting next LDCT intervals on the basis of individual risk profile.
Method
BioMILD trial offered a lung cancer screening program combining LDCT and blood microRNA assay, to heavy smokers (current or former ≤10 years) aged 50-75 years (clinicaltrials.gov ID: NCT02247453). At baseline, LDCT and miRNA were tested independently with blind evaluation, choosing a 3-year interval for the next repeat in participants with double negative LDCT and miRNA.
Result
From January 2013 to March 2016, bioMILD prospectively enrolled 4,119 volunteers at Istituto Nazionale Tumori of Milan. The median age was 60 years, median pack-years 42, current smokers 79% and females 39%. According to baseline LDCT and miRNA profile, 2384 subjects (58%) with double negative LDCT and miRNA (2neg) were sent to 3-year LDCT repeat, 1526 (37%) with positive miRNA or indeterminate/positive LDCT (1pos) and 209 (5%) with positive miRNA and indeterminate/positive LDCT (2pos) were sent to annual or shorter LDCT repeat, depending on LDCT results. After four screening runs (LDCT 0/1/2/3), a total of 115 LCs were diagnosed (2.8%). Cumulative LC incidence was significantly different in the three groups: 0.6% for 2neg subjects, 3.8% for 1pos and 20.1% for 2pos (p<0.0001); LC mortality was 0.1%, 0.6% and 3.8% respectively (p<0.0001). Interval cancer incidence, proportion of stage I and resected LC were not statistically different among groups.
Conclusion
The combination of microRNA assay and LDCT is a valuable and safe tool to assess individual risk profile and reduce unnecessary LDCT repeats in lung cancer screening. Targeting LDCT intervals on individual risk profile did not cause any detrimental effects on LC detection or mortality.
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PR03 - Press Conference (ID 94)
- Event: WCLC 2019
- Type: Press Conference
- Track:
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 11:00, CC7.1 A&B
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PR03.04 - Blood MicroRNA and LDCT Reduce Unnecessary LDCT Repeats in Lung Cancer Screening: Results of Prospective BioMILD Trial (Now Available) (ID 3615)
10:15 - 11:00 | Presenting Author(s): Ugo Pastorino
- Abstract
- Presentation
Abstract not provided
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S01 - IASLC CT Screening Symposium: Forefront Advances in Lung Cancer Screening (Ticketed Session) (ID 96)
- Event: WCLC 2019
- Type: Symposium
- Track: Screening and Early Detection
- Presentations: 1
- Now Available
- Moderators:John Kirkpatrick Field, James L Mulshine
- Coordinates: 9/07/2019, 07:00 - 12:00, Colorado Springs (1994)
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S01.05 - Panel Discussion (Now Available) (ID 3631)
07:00 - 12:00 | Presenting Author(s): Ugo Pastorino
- Abstract
- Presentation
Abstract not provided
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