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M.W. Wille
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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: 2
- Moderators:J. Mulshine, J.K. Field
- Coordinates: 9/07/2015, 10:45 - 12:15, Mile High Ballroom 2a-3b
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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): M.W. Wille
- 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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ORAL09.05 - 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): M.W. Wille
- 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.
