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Y. Satoh

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    OA 15 - Diagnostic Radiology, Staging and Screening for Lung Cancer II (ID 684)

    • Event: WCLC 2017
    • Type: Oral
    • Track: Radiology/Staging/Screening
    • Presentations: 9
      • Abstract
      • Presentation
      • Slides

      Background:
      Retrospective studies indicate that selecting individuals for low dose computed tomography (LDCT) lung cancer screening based on a highly predictive risk model is superior to applying National Lung Screening Trial (NLST)-like criteria, which use only categorized age, pack-year and smoking quit-time information. The Pan-Canadian Early Detection of Lung Cancer Study (PanCan Study) was designed to prospectively evaluate whether individuals at high risk for lung cancer could be identified for screening using a risk prediction model. This paper describes the study design and results.

      Method:
      2537 individuals were recruited through 8 centers across Canada based on a ≥2% of lung cancer risk estimated by the PanCan model, a precursor to the validated PLCOm2012 model. Individuals were screened at baseline and 1 and 4 years post-baseline.

      Result:
      At a median 5.5 years of follow-up, 164 individuals (6.5%) were diagnosed with 172 lung cancers. This was a significantly greater percentage of persons diagnosed with lung cancers than was observed in the NLST(4.0%)(p<0·001). Compared to 57% observed in the NLST, 77% of lung cancers in the PanCan Study were early stage (I or II) (p<0.001) and to 25% in a comparable population, age 50-75 during 2007-2009 in Ontario, Canada’s largest province, (p<0·001).

      Conclusion:
      Enrolling high-risk individuals into a LDCT screening study or program using a highly predictive risk model, is efficient in identifying individuals who will be diagnosed with lung cancer and is compatible with a strong stage shift – identifying a high proportion at early, potentially curable stage. Funding This study was funded by the Terry Fox Research Institute and Canadian Partnership Against Cancer. ClinicalTrials.gov number, NCT00751660

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      OA 15.02 - Benefits, Harms, and Economic Efficiency of Low-Dose CT Lung Cancer Screening Strategies in a Population-Based Setting (ID 7999)

      14:30 - 16:15  |  Presenting Author(s): Alexander Kuhlmann  |  Author(s): M. Treskova, I. Aumann, H. Golpon, J. Vogel-Claussen, T. Welte, J.-. Graf Von Der Schulenburg

      • Abstract
      • Presentation
      • Slides

      Background:
      In lung cancer screening, a nodule management protocol describes nodule assessment and thresholds for nodule size and growth rate to identify patients who require immediate diagnostic evaluation or additional imaging exams. The NELSON and NLST clinical trials used different selection criteria and nodule management protocols. Several modelling studies have reported variations in screening outcomes and cost-effectiveness across selection criteria and screening intervals; however, the effect of variations in the nodule management protocol remains uncertain. This study evaluated the effects of the eligibility criteria and nodule management protocols on the benefits, harms, and cost-effectiveness of lung screening scenarios in a population-based setting in Germany.

      Method:
      We developed a modular microsimulation model: a biological module simulated individual histories of lung cancer development from carcinogenesis onset to death; a screening module simulated patient selection, screening-detection, nodule management protocols, diagnostic evaluation and screening outcomes. Benefits included mortality reduction, life years gained, averted lung cancer deaths. Harms were costs, false-positives, overdiagnosis. Comparator was no screening. Evaluated 57 screening scenarios included variations in selection criteria and thresholds for nodule size and growth rate.

      Result:
      Five years of annual screening resulted in an 11.3–12.6% lung cancer mortality reduction in the screened population. The efficient scenario included volumetric assessment, a threshold for a volume of 300 mm[3], and a threshold for a volume doubling time of 400 days. Assessment of volume doubling time is essential for reducing overdiagnosis and false-positives. Incremental cost-effectiveness ratios of the efficient scenarios were 19,389–23,804 Euro per life years gained and 178,673–285,630 Euro per averted lung cancer death.

      Conclusion:
      Lung cancer screening can be cost-effective in Germany. Along with the eligibility criteria, the nodule management protocol influences screening performance and cost-effectiveness. Definition of the thresholds for nodule size and nodule growth in the nodule management protocol should be considered in detail when defining optimal screening strategies.

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      OA 15.03 - Gene-Based Risk Stratification of NLST-ACRIN Screening Participants Identifies The "Sweet Spot" of Screening (N=10,054) (ID 8625)

      14:30 - 16:15  |  Presenting Author(s): Robert P Young  |  Author(s): Raewyn J Hopkins, F. Duan, E. Greco, C. Chiles, D.R. Aberle, G.D. Gamble

      • Abstract
      • Presentation
      • Slides

      Background:
      Screening of high risk smokers with computed tomography (CT) aims to identify early stage lung cancers in screening participants amenable to curative surgery. The National Lung Screening Trial (NLST) demonstrated a 20% reduction in lung cancer specific mortality in the CT arm compared to chest x-ray (control) arm. European screening trial results to date have failed to show any evidence of a reduction in lung cancer mortality. Reduction in lung cancer mortality comes from the combined effects of successful surgical removal of life-threatening early stage lung cancers and post-operative survival. In screening participants of the NLST, who are older chronic smokers, there exists a balance between mortality from lung cancer and mortality from non-lung cancer related causes.

      Method:
      This study aimed to validate a gene-based risk tool for dying of lung cancer and examine the outcomes from screening according to tertiles of risk. It also aimed to establish the utility of adding SNP-based data to risk prediction and efficacy in identifying which screening participants get the best outcomes from screening. Using prospective data from the NLST-ACRIN cohort (N=10,054), we examined the utility of combining risk genotypes with clinical risk variables in our risk model for dying of lung cancer. We then stratified screening participants into risk tertiles according to our risk model and compared the outcomes from CT versus CXR screening

      Result:
      The addition of risk genotypes (combined genetic risk score) to our clinical risk model for dying of lung cancer was significantly improved (AUC increased from 0.61 to 0.66, P=0.014). We show that screening participants in the middle risk tertile achieves a lung cancer specific mortality reduction of 55% and all-cause mortality reduction of 21%. In this group the number of lung cancers averted is maximised (12/1000 person screened) and number needed to screen to avert one lung cancer reduced to 84. We show that this is achieved through minimising pre-existing co-morbid disease and by maximising screen detected lung cancers amenable to CT detection and successful surgical intervention. We believe genetic data provides useful information on lung cancer biology.

      Conclusion:
      The “Sweet spot” of CT screening comes from identifying high risk smokers optimised according to co-existing premorbid disease (especially COPD), early stage lung cancers amenable to surgical cure and least likely to die of other complications of smoking. Gene-based risk testing appears superior to just clinical risk models alone in prioritising high risk smokers for screening.

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      OA 15.04 - Community-Based Lung Cancer Screening, Targeting High-Risk Ever Smokers in Deprived Areas of Manchester: an NHS Implementation Project. (ID 7525)

      14:30 - 16:15  |  Presenting Author(s): Haval Balata  |  Author(s): P. Crosbie, M. Evison, L. Yarnell, A. Threlfall, P. Barber, J. Tonge, R. Booton

      • Abstract
      • Presentation
      • Slides

      Background:
      Lung cancer (LC) is the commonest cause of cancer-related death in the world. Screening with low-dose computer tomography (LDCT) had been shown to reduce LC specific and all-cause mortality. Benefit is greatest in those at highest risk, such as current smokers from areas of high socio-economic deprivation, yet participation in these ‘hard-to-reach’ populations remains a challenge and must be improved if we are to succeed with screening. The aim of this NHS implementation project was to assess LC screening within the community in deprived areas.

      Method:
      Ever smokers, aged 55-74, registered at 14 participating general practitioner (GP) practices in deprived areas of Manchester were invited to attend and have a free ‘Lung Health Check’ (LHC) in a mobile unit located at their local shopping centres. Lung cancer risk score (PLCO~M2012~), respiratory symptoms and spirometry were assessed as part of the LHC with results communicated back to the GPs. Those at high risk of LC, i.e. 6-year lung cancer risk ≥1.51%, were offered immediate LDCT in a co-located mobile CT scanner. These were all reported by thoracic radiologists with an interest in pulmonary oncology. Specifically designed nodule algorithms were followed in the reporting.

      Result:
      The maximum available capacity of the project was filled within days of going live. 2,541 individuals attended for a LHC and consented to data analysis. The mean age was 64.1±5.5, 51.0% (n=1,296) were female, 35.1% (n=891) were current smokers and 74.5% (n=1,893) ranked in lowest deprivation quintile. Of these 56.2% (n=1,429) qualified for a LDCT scan (PLCO~M2012~ risk score ≥1.51%). 46 lung cancers were detected in 42 individuals, a prevalence of 3.0%, of which 80% (n=37/46) were early stage (I+II). A treatment with curative intent was offered to 89.1% (n=41/46) of screen detected cancers and the surgical resection rate was 65.2%, which is almost fourfold the UK national average (16.8%).

      Conclusion:
      Taking lung cancer screening into the community can identify and target those at most risk, using the PLCO~m2012~ model, resulting in a significant stage shift in screen detected lung cancers in deprived populations.

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      OA 15.05 - Discussant - OA 15.01, OA 15.02, OA 15.03, OA 15.04 (ID 10835)

      14:30 - 16:15  |  Presenting Author(s): David F Yankelevitz

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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      OA 15.06 - Management of Nonresolving New Solid Nodules after Initial Detection in Incidence Rounds of CT Lung Cancer Screening (ID 8922)

      14:30 - 16:15  |  Presenting Author(s): Joan E Walter  |  Author(s): M.A. Heuvelmans, R. Vliegenthart, P.M. Ooijen, Harry J De Koning, Matthijs Oudkerk

      • Abstract
      • Presentation
      • Slides

      Background:
      Low-dose computed tomography (LDCT) lung cancer screening is recommended by US guidelines for high-risk individuals. New solid nodules are regularly found in incidence screening rounds and have a higher lung cancer probability at smaller size than do baseline nodules, leading to the proposal of lower size cutoffs at initial new solid nodule detection. However, currently there is no evidence concerning the risk-stratification of new solid nodules at first LDCT screening after initial detection.

      Method:
      In the ongoing, multicenter, randomized controlled Dutch-Belgian Lung Cancer Screening (NELSON) Trial, 7,295 participants underwent the second and 6,922 participants the third screening round. We included participants with solid non-calcified nodules, that were registered by the NELSON radiologists as new or smaller than 15mm[3] (study detection limit) at previous screens and received a follow-up or regular LDCT screening after initial detection; thereby excluding high-risk nodules according to the NELSON management protocol (nodules ≥500mm[3]). Nodule volume was generated semiautomatically. For assessment of the predictive performance, the area under the receiver operating characteristics curve (AUC) of nodule volume, volume doubling time (VDT), and VDT combined with a predefined 200mm[3] volume cutoff were evaluated with eventual lung cancer diagnosis as outcome.

      Result:
      Overall, 680 participants with 1,020 low and intermediate risk new solid nodules were included. A total of 562 (55%) new solid nodules were resolving, leaving 356 (52%) participants with a nonresolving new solid nodule of whom 25 (7%) were eventually diagnosed with lung cancer in such a nodule. At first follow-up or regular LDCT screening after initial new solid nodule detection, VDT, volume, and VDT combined with the predefined ≥200mm[3] volume cutoff had a high discriminative performance for lung cancer (VDT, AUC: 0.91; volume, AUC: 0.88; VDT and ≥200mm[3] combination, AUC: 0.94). A cutoff combination of ≤590 days VDT or ≥200mm[3] at first LDCT after initial new solid nodule detection, classifying a nodule positive when at least one criterion was fulfilled, provided 100% (95% confidence interval [CI] 84-100%) sensitivity and 84% (95%CI 80-87%) specificity for discriminating lung cancer, with positively classified nodules having a lung cancer probability of 27% (95%CI 19-37%).

      Conclusion:
      More than half of new solid nodules identified in LDCT lung cancer screening are resolving nodules. At first follow-up, a cutoff combination of ≤590 days VDT or ≥200mm[3] volume can be used for risk stratification.

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      OA 15.07 - Value of Nodule Characteristics in Risk-Stratification of New Incident Nodules Detected in CT Lung Cancer Screening (ID 9067)

      14:30 - 16:15  |  Presenting Author(s): Joan E Walter  |  Author(s): M.A. Heuvelmans, R. Vliegenthart, P.M. Ooijen, Harry J De Koning, Matthijs Oudkerk

      • Abstract
      • Presentation
      • Slides

      Background:
      New solid nodules detected in low-dose computed tomography (LDCT) lung cancer screening have a higher lung cancer probability at a smaller size than baseline nodules and lower size cutoff values for risk stratification at initial detection have been proposed. So far, it is unknown whether nodule characteristics, such as morphology or location, could improve risk stratification by size in new solid nodules.

      Method:
      This study forms part of the ongoing, randomized controlled Dutch-Belgian Lung Cancer Screening (NELSON) trial. This analysis included solid non-calcified nodules detected during the three incidence screening rounds and registered by the NELSON radiologists as new or previously below detection limit (15mm[3]). Nodule volume was generated semiautomatically. The predictive performance of nodule characteristics (location, distribution [peripheral, nonperipheral], shape [round, polygonal, irregular], margin [smooth, lobulated, spiculated, irregular], visibility <15mm[3] in retrospect) combined with previously established volume cutoffs (<30mm[3], low risk; 30-<200mm[3], intermediate risk; ≥200mm[3] high risk) was evaluated by multivariable logistic regression analysis with eventual lung cancer diagnosis as outcome. Discrimination of lung cancer based on volume, the final parsimonious model, and the model stratified into three risk groups (low, intermediate, high) was assessed through the area under the receiver operating characteristics curve (AUC) and compared using DeLong's Method.

      Result:
      Overall, 1,280 new nodules were included with 73 (6%) being diagnosed as lung cancer eventually. Of the new nodules visible <15mm[3] in retrospect and now ≥30mm[3], 22% (6/27) were lung cancer. Discrimination based on volume cutoffs (AUC: 0.80, 95% confidence interval [CI] 0.75-0.84) and continuous volume (AUC: 0.82, 95%CI 0.77-0.87) was comparable (P=0.14). After adjustment for volume cutoffs, only location in the right upper lobe (odds ratio [OR] 2.0, 95%CI 1.2-3.4), nonperipheral distribution (OR 2.4, 95%CI 1.4-4.2), and visibility <15mm[3] in retrospect (OR 4.7, 95%CI 1.7-12.8) remained significant predictors. Discrimination based on the model (AUC: 0.85, 95%CI 0.81-0.89) was superior to the volume cutoffs alone (P=0.0002), but when stratified into three risk groups (AUC: 0.82, 95%CI 0.78-0.86) discrimination was comparable (P=0.2).

      Conclusion:
      At initial detection, nodule volume is the strongest predictor for lung cancer in new nodules. Nodule characteristics may further improve lung cancer prediction, but only have limited incremental discriminatory value additional to volume cutoffs in a three-category stratification approach.

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      OA 15.08 - Thoroughness of Staging and the Outcomes of Surgical Resection Outcomes in Potentially Curable Non-Small Cell Lung Cancer (NSCLC) (ID 10059)

      14:30 - 16:15  |  Presenting Author(s): Matthew P Smeltzer  |  Author(s): Y. Lee, N.R. Faris, M.A. Ray, C. Fehnel, C. Houston-Harris, P. Ojeabulu, O. Akinbobola, L. Deese, E. Owen, B. Wolf, H.L. Wiggins, C. Mutrie, V. Sachdev, P. Levy, R.S. Signore, E.T. Robbins, Raymond U. Osarogiagbon

      • Abstract
      • Presentation
      • Slides

      Background:
      Substantial variation exists in the processes of care for potentially curable NSCLC. We examined the impact of thoroughness of staging for patients undergoing NSCLC surgery in a large, heterogeneous population within a lung cancer endemic region of the US.

      Method:
      We evaluated all surgically resected patients in the Mid-South Quality of Surgical Resection (MS-QSR) cohort from 2009-2017. MS-QSR is a population-based cohort including all curative-intent NSCLC resections at 11 hospitals in the mid-south US. Patients were classified into 8 groups based on use (Yes/No) of the following staging modalities: PET/CT, pre-operative invasive staging, operative mediastinal nodal examination (MLE). We compared stage distribution, adjuvant therapy, and overall survival outcomes across groups using the chi-square test and adjusted Proportional Hazards Models.

      Result:
      The 2,370 patients had a median age of 67 years, were 53% male. The racial distribution was: 70% White, 25% Black, 5% Other. Clinical N-stage was similar between the 8 groups. We found statistically significant differences in pathologic stage distribution, adjuvant therapy usage, and overall survival across the 8 groups (Table 1). Patients who received PET/CT, invasive staging, and MLE (Group 1) had significantly higher pathologic N-stage distribution compared to the other groups due to substantial nodal upstaging. Group 1 had 76% eligibility and 31% use of adjuvant chemotherapy compared to 51% and 8% in the Group 8 (No PET/CT, No Invasive Staging, No MLE). Use and eligibility for adjuvant radiation therapy was also highest in Group 1. There was an overall difference in survival across the groups (p-value=0.0019) which remained significant after adjusting for age, sex, race, histology, and path stage (p-value=0.0013). After adjustment, Group 8 had a 14% increased hazard of death compared with Group 1. Figure 1



      Conclusion:
      A less thorough approach to staging may lead to less nodal upstaging and less eligibility for adjuvant therapy, which could have implications for long term survival.

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      OA 15.09 - Discussant - OA 15.06, OA 15.07, OA 15.08 (ID 10836)

      14:30 - 16:15  |  Presenting Author(s): John Kirkpatrick Field

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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