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

机译:CT检测到的肺结节患者中肺癌的可能性:低剂量CT筛查的NELSON试验数据的预先分析

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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 mm3 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 mm3 (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 mm3 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 mm3 or diameter 5 mm) are not predictive for lung cancer. Immediate diagnostic evaluation is necessary for large nodules (≥300 mm3 or ≥10 mm). Volume doubling time assessment is advocated only for intermediate-sized nodules (with a volume ranging between 100-300 mm3 or diameter of 5-10 mm). Nodule management protocols based on these thresholds performed better than the simulated ACCP nodule protocol. Funding: Zorgonderzoek Nederland Medische Wetenschappen and Koningin Wilhelmina Fonds.
机译:背景:CT筛查肺癌的主要挑战是肺结节的高发率和相对较低的肺癌发生率。管理规程使用结节大小和生长率阈值来确定哪些结节需要其他诊断程序,但这些程序应基于个体患肺癌的可能性。在这项预先确定的分析中,我们使用NELSON CT筛选试验的数据,旨在量化结节直径,体积和体积倍增时间如何影响CT扫描2年内患肺癌的可能性,并提出并评估阈值管理协议。方法:符合条件的NELSON试验参与者为年龄在50-75岁之间,每天吸烟15支或更多烟超过25年,或吸烟10支或更多烟超过30年且仍在吸烟或已停止吸烟的参与者。不到十年前参加者以增加的间隔随机分配到低剂量CT筛查,或者不进行筛查。我们纳入了分配给筛查小组的所有参与者,他们参加了至少一轮筛查,其结果可从美国国家癌症登记数据库中获得。我们计算了肺癌的概率,按结节直径,体积和体积倍增时间分层,并使用直径,体积,体积倍增时间和多结节作为潜在的预测变量进行了逻辑回归分析。我们根据结节阈值特征的特异性和敏感性评估了管理策略,并将其与美国胸科医师学院(ACCP)指南进行了比较。 NELSON试用版在www.trialregister.nl上注册,编号ISRCTN63545820。结果:在NELSON筛查组中的7155名参与者中,通过CT筛查发现了9681个非钙化结节的体积,体积加倍时间和基于体积的直径,以量化肺癌的可能性。结节体积为100 mm3或更小(0.6%[95%CI 0.4-0.8])或最大横向直径小于5 mm(0.4%[0.2-0.7])的参与者,肺癌发生的可能性较低。来自没有结节的参与者(分别为0.4%[0.3-0.6],p = 0.17和p = 1.00)。如果结节的体积为100-300 mm3(2.4%[95%CI 1.7-3.5])或直径为5-10 mm(1.3%[1.0-1.8]),则肺癌发生率处于中等水平(需要随访CT) 。体积加倍时间进一步将概率分层:对于600天或以上的体积加倍时间为0.8%(95%CI 0.4-1.7),对于体积为400-600天的体积加倍时间为4.0%(1.8-8.3),以及9.9%(6.9-14.1) ),以实现400天或更短的交易时间。对于结节体积为300 mm3或更大(16.9%[95%CI 14.1-20.0])或直径为10 mm或更大(15.2%[12.7-18.1])的参与者,肺癌发生的可能性很高。模拟的ACCP管理方案产生的敏感性和特异性分别为90.9%(95%CI 81.2-96.1)和87.2%(86.4-87.9)。基于直径的方案与基于体积的结节直径产生更高的灵敏度(92.4%[95%CI 83.1-97.1])和更高的特异性(90.0%[89.3-90.7])。基于体积的方案(阈值基于肺癌的可能性)产生与ACCP方案相同的灵敏度(90.9%[95%CI 81.2-96.1])和更高的特异性(94.9%[94.4-95.4])。解释:小结节(体积<100 mm3或直径<5 mm的结节)不能预测肺癌。对于大结节(≥300mm3或≥10mm),必须立即进行诊断评估。仅对中等大小的结节(体积在100-300 mm3之间或直径在5-10 mm之间)提倡体积加倍时间评估。基于这些阈值的根瘤管理协议的性能优于模拟的ACCP根瘤协议。资金来源:Zorgonderzoek Nederland Medische Wetenschappen和Koningin Wilhelmina Fonds。

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