Department of Family, Population and Preventive Medicine, Stony Brook Medicine, Stony Brook, New York.
Program in Public Health, Stony Brook Medicine, Stony Brook, New York.
Cancer Prev Res (Phila). 2019 Jul;12(7):463-470. doi: 10.1158/1940-6207.CAPR-18-0500.
This prospective investigation derived a prediction model for identifying risk of incident lung cancer among patients with visible lung nodules identified on computed tomography (CT). Among 2,924 eligible patients referred for evaluation of a pulmonary nodule to the Stony Brook Lung Cancer Evaluation Center between January 1, 2002 and December 31, 2015, 171 developed incident lung cancer during the observation period. Cox proportional hazard models were used to model time until disease onset. The sample was randomly divided into discovery ( = 1,469) and replication ( = 1,455) samples. In the replication sample, concordance was computed to indicate predictive accuracy and risk scores were calculated using the linear predictions. Youden index was used to identify high-risk versus low-risk patients and cumulative lung cancer incidence was examined for high-risk and low-risk groups. Multivariable analyses identified a combination of clinical and radiologic predictors for incident lung cancer including ln-age, ln-pack-years smoking, a history of cancer, chronic obstructive pulmonary disease, and several radiologic markers including spiculation, ground glass opacity, and nodule size. The final model reliably detected patients who developed lung cancer in the replication sample ( = 0.86, sensitivity/specificity = 0.73/0.81). Cumulative incidence of lung cancer was elevated in high-risk versus low-risk groups [HR = 14.34; 95% confidence interval (CI), 8.17-25.18]. Quantification of reliable risk scores has high clinical utility, enabling physicians to better stratify treatment protocols to manage patient care. The final model is among the first tools developed to predict incident lung cancer in patients presenting with a concerning pulmonary nodule.
本前瞻性研究旨在为计算机断层扫描（CT）发现的肺部可见结节患者确定肺癌发病风险建立预测模型。在 2002 年 1 月 1 日至 2015 年 12 月 31 日期间，因肺部结节到石溪大学肺癌评估中心就诊的 2924 名符合条件的患者中，有 171 名在观察期间发生了肺癌。使用 Cox 比例风险模型来构建直至发病的时间模型。样本被随机分为发现（n=1469）和复制（n=1455）样本。在复制样本中，计算一致性以指示预测准确性，并使用线性预测计算风险评分。使用约登指数来确定高危与低危患者，并检查高危和低危组的累积肺癌发生率。多变量分析确定了包括 ln 年龄、ln 吸烟包年数、癌症史、慢性阻塞性肺疾病和几种影像学标志物（如分叶征、磨玻璃影和结节大小）在内的肺癌发病的临床和影像学预测因子组合。最终模型可靠地检测到复制样本中发生肺癌的患者（c 指数=0.86，灵敏度/特异性=0.73/0.81）。高危组与低危组的肺癌累积发生率升高[HR=14.34；95%置信区间（CI）：8.17-25.18]。可靠风险评分的量化具有很高的临床实用性，使医生能够更好地分层治疗方案以管理患者的护理。该最终模型是首批用于预测有可疑肺部结节患者肺癌发病的工具之一。
