Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecifi ed analysis of data from the NELSON trial of low-dose CT screening

Background The main challenge in CT screening for lung cancer is the high prevalence of pulmonary nodules and the relatively low incidence of lung cancer. Management protocols use thresholds for nodule size and growth rate to determine which nodules require additional diagnostic procedures, but these should be based on individuals' probabilities of developing lung cancer. In this prespecified analysis, using data from the NELSON CT screening trial, we aimed to quantify how nodule diameter, volume, and volume doubling time affect the probability of developing lung cancer within 2 years of a CT scan, and to propose and evaluate thresholds for management protocols. Methods Eligible participants in the NELSON trial were those aged 50-75 years, who have smoked 15 cigarettes or more per day for more than 25 years, or ten cigarettes or more for more than 30 years and were still smoking, or had stopped smoking less than 10 years ago. Participants were randomly assigned to low-dose CT screening at increasing intervals, or no screening. We included all participants assigned to the screening group who had attended at least one round of screening, and whose results were available from the national cancer registry database. We calculated lung cancer probabilities, stratified by nodule diameter, volume, and volume doubling time and did logistic regression analysis using diameter, volume, volume doubling time, and multinodularity as potential predictor variables. We assessed management strategies based on nodule threshold characteristics for specificity and sensitivity, and compared them to the American College of Chest Physicians (ACCP) guidelines. The NELSON trial is registered at www.trialregister.nl, number ISRCTN63545820. Findings Volume, volume doubling time, and volumetry-based diameter of 9681 non-calcified nodules detected by CT screening in 7155 participants in the screening group of NELSON were used to quantify lung cancer probability. Lung cancer probability was low in participants with a nodule volume of 100 mm 3 or smaller (0.6% [95% CI 0.4-0.8]) or maximum transverse diameter smaller than 5 mm (0.4% [0.2-0.7]), and not significantly different from participants without nodules (0.4% [0.3-0.6], p=0.17 and p=1.00, respectively). Lung cancer probability was intermediate (requiring follow-up CT) if nodules had a volume of 100-300 mm(3) (2.4% [95% CI 1.7-3.5]) or a diameter 5-10 mm (1.3% [1.0-1.8]). Volume doubling time further stratified the probabilities: 0.8% (95% CI 0.4-1.7) for volume doubling times 600 days or more, 4.0% (1.8-8.3) for volume doubling times 400-600 days, and 9.9% (6.9-14.1) for volume doubling times of 400 days or fewer. Lung cancer probability was high for participants with nodule volumes 300 mm 3 or bigger (16.9% [95% CI 14.1-20.0]) or diameters 10 mm or bigger (15.2% [12.7-18.1]). The simulated ACCP management protocol yielded a sensitivity and specificity of 90.9% (95% CI 81.2-96.1), and 87.2% (86.4-87.9), respectively. A diameter-based protocol with volumetry-based nodule diameter yielded a higher sensitivity (92.4% [95% CI 83.1-97.1]), and a higher specificity (90.0% [89.3-90.7). A volume-based protocol (with thresholds based on lung cancer probability) yielded the same sensitivity as the ACCP protocol (90.9% [95% CI 81.2-96.1]), and a higher specificity (94.9% [94.4-95.4]). Interpretation Small nodules (those with a volume <100 mm(3) or diameter <5 mm) are not predictive for lung cancer. Immediate diagnostic evaluation is necessary for large nodules (>= 300 mm(3) or >= 10 mm). Volume doubling time assessment is advocated only for intermediate-sized nodules (with a volume ranging between 100-300 mm(3) or diameter of 5-10 mm). Nodule management protocols based on these thresholds performed better than the simulated ACCP nodule protocol.