The National Lung Screening Trial (NLST) demonstrated that non-small cell lung cancer (NSCLC) mortality can be reduced by a program of annual CT screening in high-risk individuals. However, CT screening regimens and adherence vary, potentially impacting the lung cancer mortality benefit. We defined the NSCLC cure threshold as the maximum tumor size at which a given NSCLC would be curable due to early detection. We obtained data from 518,234 NSCLCs documented in the U.S. SEER cancer registry between 1988 and 2012 and 1769 NSCLCs detected in the NLST. We demonstrated mathematically that the distribution function governing the cure threshold for the most aggressive NSCLCs, G(x|Φ = 1), was embedded in the probability function governing detection of SEER-documented NSCLCs. We determined the resulting probability functions governing detection over a range of G(x|Φ = 1) scenarios and compared them with their expected functional forms. We constructed a simulation framework to determine the cure threshold models most consistent with tumor sizes and outcomes documented in SEER and the NLST. Whereas the median tumor size for lethal NSCLCs documented in SEER is 43 mm (males) and 40 mm (females), a simulation model in which the median cure threshold for the most aggressive NSCLCs is 10 mm (males) and 15 mm (females) best fit the SEER and NLST data. The majority of NSCLCs in the NLST were treated at sizes greater than our median cure threshold estimates. New technology is needed to better distinguish and treat the most aggressive NSCLCs when they are small (i.e., 5-15 mm).
BACKGROUND:The Mayo Lung Project (MLP) was a randomized clinical trial designed to test whether periodic screening by chest x-ray reduced lung cancer (LC) mortality in men who were high-risk smokers. Among MLP participants, there were more deaths from LC in the screening arm both at the trial's end and after long-term follow-up. Overdiagnosis was cited widely as an explanation for the MLP results, whereas a role for excess LC risk attributable to undergoing numerous chest x-ray screenings largely was unexamined. The authors of this report examined the consistency of the MLP data with a modified 2-stage clonal expansion (TSCE) model of excess LC risk. METHODS: By using a simulation model calibrated to the initial MLP data, the authors examined the expected statistical variance of LC incidence and mortality between the screening and control arms. A Bayesian estimation framework using a modified version of the TSCE model to evaluate the role of excess LC risk attributable to chest x-ray screening was derived and applied to the MLP data. RESULTS: Simulation experiments indicated that the overall difference in LC deaths and incidence between the study arm and the control arm was unlikely (P ¼ .0424 and P ¼ .0104, respectively) assuming no excess risk of LC. The authors estimated that the 10-year excess LC risk for a man aged 60 years who smoked and who received 10 chest x-ray screenings was 0.574% (P ¼ .0021). CONCLUSIONS: The excess LC risk observed among screening arm participants was found to be statistically significant with respect to the TSCE model framework in part because of the incorporation of key risk correlates of age and screen frequency into the estimation framework. Cancer
The effectiveness of population-wide lung cancer screening strategies depends on the underlying natural course of lung cancer. We evaluate the expected stage distribution in the Mayo CT screening study under an existing simulation model of non-small cell lung cancer (NSCLC) progression calibrated to the Mayo lung project (MLP). Within a likelihood framework, we evaluate whether the probability of 5-year NSCLC survival conditional on tumor diameter at detection depends significantly on screening detection modality, namely chest X-ray and computed tomography. We describe a novel simulation framework in which tumor progression depends on cellular proliferation and mutation within a stem cell compartment of the tumor. We fit this model to randomized trial data from the MLP and produce estimates of the median radiologic size at the cure threshold. We examine the goodness of model fit with respect to radiologic tumor size and 5-year NSCLC survival among incident cancers in both the MLP and Mayo CT studies. An existing model of NSCLC progression under-predicts the number of advanced-stage incident NSCLCs among males in the Mayo CT study (p-value 5 0.004). The probability of 5-year NSCLC survival conditional on tumor diameter depends significantly on detection modality (p-value 5 0.0312). In our new model, selected solution sets having a median tumor diameter of 16.2-22.1 mm at cure threshold among aggressive NSCLCs predict both MLP and Mayo CT outcomes. We conclude that the median lung tumor diameter at cure threshold among aggressive NSCLCs in male smokers may be small (<20 mm).
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