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J. Mulshine
Moderator of
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ORAL 09 - CT Screening - New Data and Risk Assessment (ID 95)
- Event: WCLC 2015
- Type: Oral Session
- Track: Screening and Early Detection
- Presentations: 8
- Moderators:J. Mulshine, J.K. Field
- Coordinates: 9/07/2015, 10:45 - 12:15, Mile High Ballroom 2a-3b
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ORAL09.01 - Discerning Malignant and Benign New Nodules at Incidence Rounds of CT Lung Cancer Screening: The Role of Volume and Predicted Volume Doubling Time (ID 1358)
10:45 - 12:15 | Author(s): J.E. Walter, M.A. Heuvelmans, G.H. De Bock, P.A. De Jong, R. Vliegenthart, M. Oudkerk
- Abstract
Background:
Newly detected nodules after baseline screen are common findings in low-dose computed tomography (LDCT) lung cancer screening, and may complicate management. So far little research focused specifically on nodules newly detected at incidence screening rounds. These nodules develop within a known time-frame and are expected to be fast-growing and potentially malignant. Even so, the majority are benign. The aim of this study was to compare volume and predicted growth rate of benign and malignant new solid nodules detected in the incidence screening rounds of the Dutch-Belgian Randomized Lung Cancer Screening Trial (NELSON).
Methods:
The NELSON trial was approved by the Dutch Ministry of Health. All participants gave written informed consent. In total, 7,557 individuals underwent baseline LDCT screening. After the baseline screening, incidence screening rounds took place after 1, 3 and 5.5 years. This study included participants with solid non-calcified nodules, newly detected after baseline and also in retrospect not present on any previous screening. Nodule volume was obtained semi-automatically by Lungcare software (Siemens, Erlangen, Germany). The growth rate at first detection was estimated by calculating the slowest predicted volume-doubling time (pVDT), according to the formula pVDT=[ln(2)*Δt]/[ln(V2/V1)], using the study’s detection limit of 15mm[3] (V1), the volume of the new nodule at first detection (V2), and the time interval between current and last screen (Δt [days]). The pVDT was calculated for nodules with a predicted volume increase of at least 25% (≥ 18.75mm[3]). Lung cancer diagnosis was based on histology. Benignity was based on histology or a stable size for at least two years. Mann-Whitney U testing was used to evaluate differences in volume and pVDT between malignant and benign nodules.
Results:
During the incidence screening rounds, 1,484 new solid nodules in 949 participants were detected of which 77 (5.2%) turned out to be malignant. At first detection, both the median volume of malignant (373mm[3], IQR 120-974mm[3]) and benign (44mm[3], interquartile-range [IQR] 22-122mm[3]) new nodules, as well as the median pVDT of malignant (144 days, IQR 116-213 days) and benign (288 days, IQR 153-566 days) new nodules differed significantly (P<0.001 for both). The calculated median pVDT of adenocarcinomas (183 days, IQR 138-299 days) and squamous-cell carcinomas (150 days, IQR 117-223 days) was similar to previously published volume doubling-times of fast-growing baseline cancers in the NELSON trial of the same histological type (196 days, IQR 135-250 days and 142 days, IQR 91-178 days, respectively).
Conclusion:
At incidence LDCT lung cancer screening, volume and pVDT can be used to differentiate between malignant and benign nature of newly detected solid nodules. The pVDT is a new measure that can assist in adjusting for time differences in screening intervals.
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ORAL09.02 - Results of the Fourth Screening Round of the NELSON Lung Cancer Screening Study (ID 1354)
10:45 - 12:15 | Author(s): U. Yousaf-Khan, C. Van Der Aalst, P. De Jong, R. Vliegenthart, E. Scholten, K. Ten Haaf, M. Oudkerk, H. De Koning
- Abstract
- Presentation
Background:
Although screening can reduce lung cancer (LC) mortality, the optimal screening strategy (e.g. numbers of screening rounds, screening interval) is unclear. The use of different screening intervals in the NELSON study is unique and makes it possible to investigate how the screening test performances (e.g. lung cancer detection rate, false positive rate) and characteristics of screen-detected lung cancers might change. This study describes the results of a fourth screening round that took place 2.5 years after the third round.
Methods:
The Dutch-Belgian randomized-controlled Lung Cancer Screening Trial (NELSON) aims to investigate whether low-dose CT screening would reduce LC mortality by at least 25% relative to no screening after ten years of follow-up. Therefore, screen group participants were screened four times: at baseline and year 1, 3, and 5.5. Screening test results were classified as negative, indeterminate, or positive based on nodule presence, volume (in case of new nodules) and volume doubling time (in case of previous existing nodules). Participants with an indeterminate test result underwent follow-up screening to classify their final screening test result as positive or negative. Participants with a positive scan result were referred to a pulmonologist for a diagnostic work-up. For this study, we included only participants who had attended all four screening rounds (n=5279). Epidemiological, radiological and clinical characteristics of lung cancers detected in the fourth round were compared with those of the lung cancers detected in the first three rounds. In addition, the risk for lung cancer detection in the fourth round (5.5 year risk) was quantified for subgroups.
Results:
In round four, 46 lung cancers were detected; 58.7% were diagnosed at stage I, 15.2% at stage II and 23.8% at stage III/IV. Adenocarcinomas were correlated with better cancer stage distribution, while small-cell carcinomas (SCLC) were associated with higher stage distribution (p=0.064). False positive rate after positive screening was 59.04% (62/105) and the overall false positive rate of the fourth round was 1.15% (62/5383). Relative to the results of the first three rounds, the LC detection rate was lower (0.80 vs 0.80-1.1) and LC was detected at a more advanced stage (23.8% vs 8.1%). In the fourth round more squamous-cell carcinomas (21.7% vs. 16.3%), SCLC (6.5% vs 3.8%) and bronchioloalveolar carcinomas (8.7% vs 5.3%) were detected. No large-cell carcinomas, large-cell neuroendocrine carcinomas or carcinoids were found in the fourth round. Screening results of the first three rounds led to formation of subgroups with significantly different probability of screening result in the fourth round: participants with previous exclusively negative results had a probability of 97.2% of negative screen compared to participants with ≥1 indeterminate or positive screen (94.6% and 87.1%) in the first three rounds. The risk of detecting LC in the fourth round also differed between these subgroups: exclusively negative results (<1.0%) and any time ≥1 indeterminate or positive result (1.5-1.7%).
Conclusion:
The LC detection rate after the third screening round was slightly lower and the stage distribution of screen-detected lung cancers in the fourth round was slightly less favorable. However, the differences seem limited.
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ORAL09.03 - The Danish Lung Cancer Screening Trial: Results 5 Years after Last CT Screening (ID 2384)
10:45 - 12:15 | Author(s): J.H. Pedersen, M.W. Wille, A. Dirksen
- Abstract
- Presentation
Background:
The Danish Lung Cancer Screening Trial (DLCST) is a European randomized controlled trial comparing annual CT screening with no screening. Inclusion ran from 2004 to 2006, and participants have now been followed for 5 years since last CT screening (approximately 10 years since randomization). The American NLST showed 20% decrease in lung cancer mortality in the screening group, and DLCST is the first European trial to present comparable results regarding effect of screening on mortality, causes of death, lung cancer findings and risk stratification after sufficient follow up.
Methods:
4,104 participants aged 50-70 at time of inclusion and a minimum of 20 pack-years of smoking history were randomized to five annual low-dose CT scans or clinical follow up without CT scanning; thus, participants were younger and had fewer pack-years than participants from NLST. Screening was concluded in 2010. Follow up information regarding date and cause of death as well as lung cancer diagnosis, stage and histology was obtained from national registries, latest follow up date was April 7, 2015. . The effects of age, amount of smoking and COPD on lung cancer mortality in the two randomized groups were explored to evaluate possible effects of risk stratification and selection of high-risk individuals on effect of screening.
Results:
More cancers (100 vs. 53, p<0.001) were found in the screening group, in particular adenocarcinomas (58 vs. 18, p<0.001). Significantly more low-staged cancers (stage I+II: 54 vs. 10, p<0.001) and stage IIIa cancers (15 vs. 3, p=0.009) were found in the screening group. However, stage IV cancers were more frequent in the control group (23 vs. 32, p=0.278), and this was statistically significant for the highest-stage cancers (T4N3M1: 8 vs. 21, p=0.025). No differences in lung cancer mortality or all-cause mortality were observed between the two groups (Log Rank tests: p=0.898 and p=0.885, respectively). However, sub-group analyses including participants with higher age, presence of COPD, and more than 35 pack-years of smoking history showed significantly increased risk of death from lung cancer; the highest-risk group (with COPD and >35 pack-years) showed a 20% reduction in lung cancer mortality when screened. Though this result is not statistically significant due to small numbers, it does show compliance with the results from NLST.
Conclusion:
Although no statistically significant effects of 5 annual CT screening rounds on lung cancer mortality were observed in this small study, results indicate that focus on selection of high-risk individuals may be essential for the effect of CT lung cancer screening. We suggest that balancing benefits with harms—such as false positive findings and overdiagnosis— should bring focus to high-risk profiling of screening participants. Thus, the effects of age, amount of smoking, and COPD on the occurrence and mortality of lung cancer in the two randomization groups seems to indicate that limiting lung cancer screening to a higher-risk group improves the outcome of screening.
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ORAL09.04 - Discussant for ORAL09.01, ORAL09.02, ORAL09.03 (ID 3532)
10:45 - 12:15 | Author(s): N. Peled
- Abstract
- Presentation
Abstract not provided
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ORAL09.05 - Lung-RADS versus the McWilliams Nodule Malignancy Score for Risk Prediction: Evaluation on the Danish Lung Cancer Screening Trial (ID 356)
10:45 - 12:15 | Author(s): S.J. Van Riel, F. Ciompi, M.W. Wille, M. Naqibullah, C. Schaefer-Prokop, B. Van Ginneken
- Abstract
Background:
Lung-RADS published in 2014 by the American College of Radiology is based on literature review and expert opinion and uses nodule type, size, and growth to recommend nodule management adjusted to malignancy risk. The McWilliams model (N Engl J Med 2013;369:910-9) is a multivariate logistic regression model derived from the Pan-Canadian Early Detection of Lung Cancer Study and provides a nodule malignancy probability based on nodule size, type, morphology and subject characteristics. We compare the performance of both approaches on an independent data set.
Methods:
We selected 60 cancers from the Danish Lung Cancer Screening Trial as presented in the first scan they were visible, and randomly added 120 benign nodules from baseline scans, all from different participants. Data had been acquired using a low-dose (16x0.75mm, 120kVp, 40mAs) protocol, and 1mm section thickness reconstruction. For each nodule, the malignancy probability was calculated using McWilliams model 2b. Parameters were available from the screening database or scored by an expert radiologist. Completely calcified nodules and perifissural nodules were assigned a malignancy probability of 0, in accordance with model guidelines. All nodules were categorized into their Lung-RADS category based on nodule type and diameter. Perifissural nodules were treated as solid nodules, in accordance with Lung-RADS guidelines. For each Lung-RADS category cut-off sensitivity and specificity were calculated. Corresponding sensitivities and specificities using the McWilliams model were determined.
Results:
Defining Lung-RADS category 2/3/4A/4B and higher as a positive screening result, specificities to exclude lung malignancy were 21%/65%/86%/99% and vice versa sensitivities to predict malignancy were 100%/85%/58%/32%. At the same sensitivity levels as Lung-RADS, McWilliams model yielded overall higher specificities with 2%/86%/98%/100%, respectively (red arrows in Figure 1). Similarly, at the same specificities McWilliams’s model achieved higher sensitivities with 100%/95%/85%/48%, respectively (green arrows in Figure 1). Figure 1
Conclusion:
For every cut-off level of Lung-RADS, the McWilliams model yields superior specificity to reduce unnecessary work-up for benign nodules, and higher sensitivity to predict malignancy. The McWilliams model seems to be a better tool than Lung-RADS to provide a malignancy risk, thus reducing unnecessary work-up and helping radiologists determine which subgroup of nodules detected in a screening setting need more invasive work-up.
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ORAL09.06 - The Cancer Risk Management Model: A Tool to Inform Canadian Policymakers Implementing Low-Dose CT Screening for Lung Cancer (ID 968)
10:45 - 12:15 | Author(s): W.K. Evans, J. Gofffin, W. Flanagan, A. Miller, N. Fitzgerald, S. Memon, S. Fung, M. Wolfson
- Abstract
- Presentation
Background:
Although the National Lung Screening Trial (NLST) demonstrated that 3 annual low-dose CT (LDCT) screens reduced lung cancer specific and overall mortality at 6 years in a defined population of smokers, the decision to implement population-based screening is difficult in the absence of information on factors not evaluated in the NLST including frequency and duration of screening, characteristics of the “at risk” population, program cost and cost-effectiveness. The Canadian Partnership Against Cancer has developed a Cancer Risk Management Model for lung cancer (CRMM-LC) with a screening module informed by data from NLST that can evaluate these factors.
Methods:
CRMM-LC uses longitudinal microsimulation techniques that incorporate Canadian demographic characteristics, risk factors, cancer management approaches and outcomes, resource utilization and other economic factors to assess impacts on population health and costs to the Canadian healthcare system. Data sources include large national population surveys, cancer registries and census data. The diagnostic and therapeutic approaches and outcomes in CRMM-LC are based on input from Canadian lung cancer experts and survival information from medical literature. The simulated mortality reduction from LDCT screening using CRMM-LC is comparable to NLST. The model can projected incident cases, life years and quality adjusted life years over different time periods for populations defined by different age ranges and smoking histories and by screening duration and frequency (annual vs biennial). It can also inform individual provinces of the incremental resources (CT scans, invasive procedures) required for program implementation and project budget impact.
Results:
Based on NLST at risk criteria (55-74 yr old smokers of 30+ pack-years, the base case scenario), 1.4 million or 4% of Canadians would be candidates for LDCT screening in 2014. Annual screening over a 10 year period with a participation rate of 60% and 70% adherence would identify an additional 12,500 (4.7%) incident cases and result in 11,320 life-years saved (undiscounted). Biennial screening would identify 4,620 (1.6%) fewer cases and save 1,454 (12.8%) fewer life-years, but may be more cost-effective than annual screening. Scenarios modeling participation rates of 20, 40 and 80% (linear uptake over 10 years) yield incident cases that vary from 8,380 fewer for the lowest rate to 3,950 more for the highest with life years saved over 10 years ranging from 7,540 fewer to 3,310 more, respectively. The model projects 3,560 more cases would be detected if LDCT was introduced for younger (50 to 69 yr old), 30 pack-year smokers compared to the base case scenario and 1,760 more cases if the threshold number of pack years was decreased to 20 pack-years. The 10 year cumulative incremental cost in Canada of annual and biennial screening would be $1,107 and $709 million, respectively
Conclusion:
CRMM-LC, available at cancerview.ca/cancerriskmanagement, can be used by provincial analysts to estimate the impact of various scenarios on the impact of policy decisions concerning the scope of the LDCT screening program. In the current fiscally constrained healthcare environment, models that can assimilate diverse sources of information and extrapolate beyond clinical trial results can help inform decisions that healthcare administrators confront.
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ORAL09.07 - Economic Evidence for the Use of Risk-Selection and Risk-Stratification for Lung Cancer Screening Programs (ID 2928)
10:45 - 12:15 | Author(s): S. Cressman, S. Lam, M. Tammemägi, S. Peacock
- Abstract
- Presentation
Background:
Screening for lung cancer according to age and smoking history alone could cost billions of dollars of public health expenditure due to the high incidence of potential participants. Risk-adapted lung cancer screening strategies such as participant selection (based on published risk prediction models such as the PLCOm2012 model) and malignancy risk based screening protocols may reduce program costs while improving outcomes among current and former smokers at risk of developing the disease. The Pan-Canadian Early Detection of Lung Cancer Study (PanCan) was designed with the objective of providing economic evidence for an affordable lung cancer-screening program in Canada.
Methods:
Data for 2537 screening participants in the PanCan study (median follow-up time of 4 years) and 25,914 eligible participants from the NLST-CXR arm were included in the analysis. There was adequate power and follow-up to inform the transition probabilities in model and provide the distribution to test all model parameters simultaneously in a probabilistic sensitivity analysis. The cost and health utility inputs are from patient-level trial data with defined ranges of certainty.
Results:
Our results show that risk selection using the PanCan risk prediction model could reduce the need to screen 21,022 (81%) of the NLST population if risk prediction were applied. If risk prediction were applied to Canadians who met the NLST criteria, 2 year program costs could be reduced by 400 million dollars and nearly half a million people could be spared the potential harms from screening that is not likely to result in a Cancer diagnosis. With the economic evidence from the PanCan and NLST trials, we report our initial cost-effectiveness results and will show, for the first time, a definitive description of the uncertainty surrounding our cost-effectiveness ratios.
Conclusion:
Using a model loaded with patient-level screening data has enabled us to predict the likelihood that risk-adapted screening will fall below most commonly referenced thresholds of acceptability for cancer interventions. The initial results and characterization of the parameters affecting cost-effectiveness will be presented. [*]on behalf of the PanCan study team The panCan study is sponsored by the Terry Fox Research Institute and the Canadian Partnership against Cancer, ARCC is funded by the CCSRI The authors thank the National Cancer Institute for access to NCI’s data collected by the National Lung Screening Trial. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by NCI
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ORAL09.08 - Discussant for ORAL09.05, ORAL09.06, ORAL09.07 (ID 3472)
10:45 - 12:15 | Author(s): S. Malkoski
- Abstract
- Presentation
Abstract not provided
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Author of
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MS 15 - Current Screening Trials, Current Evidence and Screening Algorithms (ID 33)
- Event: WCLC 2015
- Type: Mini Symposium
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:P. Mazzone, T. Vidaurre-Rojas
- Coordinates: 9/08/2015, 14:15 - 15:45, Four Seasons Ballroom F3+F4
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MS15.01 - NLST, USPSTF Recommendations - Is Screening Going to Happen in USA? (ID 1912)
14:15 - 15:45 | Author(s): J. Mulshine
- Abstract
- Presentation
Abstract:
In the wake of the demonstrated 20% mortality reduction benefit reported from the randomized National Lung Screening Trial (NLST), the United States Preventive Services Task Forces gave a “B” recommendation for low dose CT screening of for lung cancer in high risk populations (1). This favorable endorsement in turn led the Centers for Medicare and Medicaid Service to fully reimbursement the cost of providing this service by federal and commercial insurers for high risk smokers between the ages of 55-77 who have been smoking within the last 15 years. With these provisions, national lung cancer screening is now being implemented in the United States. The protocol and screening process used for the NLST was fixed at the time of study initiation in 2002 when 4-detector scanners were the default CT device and screening management was delivered based on the existing community standard (2). In the time since the NLST was conducted there have been a number of developments that have improved the process of lung cancer screening services (3). These innovations range from the introduction of more capable CT scanners, lower medical radiation scanning protocols, more effective and efficient diagnostic work up approaches, as well as improved and more tailored surgical approaches. The aggregate effect of all of these advances is that the cost efficiency of this process is also improving (4). Further improvements with clinical management may occur as the use of quantitative CT imaging allows for more consistent measurement of suspicious pulmonary nodules, as size criteria is emerging as a key determinant guiding invasive screening work-up (5). However implementing national CT screening to ensure delivery of high quality, best-practice early lung cancer detection in the target population of tobacco-exposed individuals constitutes a profound challenge. Still the public health impact of tobacco-exposure is singularly lethal. In the United States alone over 438,000 annual deaths are related to tobacco-exposure with lung cancer being the most common cause of tobacco-related death approaching 30% of this total mortality burden. Advocacy groups have worked with academic medical centers as well as community hospitals to address this implementation challenge by creating a consortium of institutions that are conducting screening programs to systematically adopt best standard of screening practice for all components of clinical management (6). A critical aspect of the “Framework” process includes the expectation that participating institutions will prospectively acquire clinical follow-up information so that the outcomes of lung cancer screening efforts can be accessed and reported (6). This effort builds on previous models of cooperative research such as with using institutional feedback to accelerate learning curve in allowing new screening institutions to rapidly implement effective screening process. The best example to date of this approach with screening is the use of the recent I-ELCAP screening outcomes to evaluate the most favorable pulmonary nodule size to use as a threshold for a more invasive diagnostic work-up (7). Increasing the nodule size as the threshold for further diagnostic work-up markedly improves the efficiency of the screening management while reducing the rate of false positive work-ups, cost and morbidity (7). An indispensible element in the national implementation of screening is the simultaneous provision of best practice smoking cessation services for those individuals that continue to smoke. Pyenson and co-workers have reported that routine integration of smoking cessation with the annual CT screening process can improve the cost utility ratio of quality adjusted life years by close to 40% (4). Indisputably implementing national annual CT screening in high risk populations is a significant societal cost. However there are attractive opportunities to leverage this new pattern of care to further benefit health outcomes in this at-risk cohort. For example, the annual CT visit provides a scaffolding to support more intensive research to define better smoking cessation measures. In asymptomatic tobacco-exposed individuals, a growing body of research suggests that the CT scan done to evaluate for early lung cancer also commonly finds individuals with evidence of asymptomatic COPD/emphysema or coronary artery disease (8, 9). These diseases along with lung cancer account for close to 70% of the excess mortality in heavily tobacco-exposed populations. Lung cancer screening will permit additional research opportunities in this tobacco-exposed cohort including catalyzing the development for more effective drugs to manage the early stage of lung cancer. With screening, the frequency of finding early stage lung cancer is greatly increased and focusing on these early stage patients could allow for much more rapid evaluation of new targeted therapeutic agents compared to the current setting. For the same reason, lung cancer screening will also find many more early asymptomatic COPD patients and quantitative CT provides an economical biomarker to allow much more efficient COPD drug development research than is currently possible. Particular classes of drug targets such as immunomodulators could conceivably show benefit in arresting the progression of both early lung cancer and COPD. This time of initial US national screening dissemination is allowing a full national discussion not only about how to provide high quality lung cancer screening services, but also about how to thoughtfully leverage this newly reimbursed screening service to extend the utility of the thoracic imaging encounter and greatly accelerate progress with improving health outcomes in heavily tobacco-exposed populations. At the very least, evidence for one or more of these additional diseases on annual screening may heighten a smoker’s motivation to stop that habit. Other life style interventions such as diet modification and exercise are being successfully employed to manage the consequence of asymptomatic coronary calcification. Life style counseling could also emerge as integral part of the annual CT evaluation as these interventions can have markedly positive impact for a range of tobacco-dependent conditions. The emergence of lung cancer screening as a public health tool has evoked a lively global debate regarding its potential merits. While this healthy debate should continue, there are potentially unprecedented opportunities arising with this new approach to the lethality of chronic tobacco exposure that merit serious consideration. References: 1) Moyer VA. Screening for lung cancer: U.S. preventive services task force recommendation statement. Ann Intern Med. 2013 Dec 31. 2) Aberle D, Adams A, Berg C et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011; 365(5): 395-409. 3) Mulshine JL, D'Amico TA. Issues with implementing a high-quality lung cancer screening program. CA Cancer J Clin. 2014 Jun 27. 4) Villanti AC, Jiang Y, Abrams DB, Pyenson BS. A cost-utility analysis of lung cancer screening and the additional benefits of incorporating smoking cessation interventions. PLoS One. 2013 Aug 7; 8(8): e71379. PMCID: PMC3737088. 5) Mulshine JL1, Avila R, Yankelevitz D et al. Lung Cancer Workshop XI: Tobacco-Induced Disease: Advances in Policy, Early Detection and Management. J Thorac Oncol. 2015 May;10(5):762-7. doi: 10.1097/JTO.0000000000000489. 6) Rights and expectations for excellence in lung cancer screening and continuum of care.[homepage on the Internet]. Available from: http://www.screenforlungcancer.org/national-framework/. 7) Henschke CI. Definition of a positive test result in computed tomography screening for lung cancer: A cohort study. Ann Intern Med. 2013; 158(4): 246-252. 8) Zulueta J, Wisnivesky J, Henschke C, et al. Emphysema scores predict death from COPD and lung cancer. Chest. 2012; 141(5): 1216-1223. 9) Htwe Y, Cham MD, Henschke CI, et al. Coronary artery calcification on low-dose computed tomography: comparison of Agatston and Ordinal Scores. Clin Imaging. 2015 Apr 18. pii: S0899-7071(15)00098-4. doi: 10.1016/j.clinimag.2015.04.006. [Epub ahead of print]
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