Department of Thoracic Surgery, People’s Hospital of Peking University, No. 11 Xizhimen South Street, Xicheng District, 100044 Beijing, People’s Republic of China.
World J Surg. 2012 Apr;36(4):830-5. doi: 10.1007/s00268-012-1449-8.
The goal of the present study was to differentiate between benign and malignant solitary pulmonary nodules (SPN) by developing a mathematical prediction model.
Records from 371 patients (197 male, 174 female) with SPN between January 2000 and September 2009 were reviewed (group A). Clinical data were collected to estimate the independent predictors of malignancy of SPN with multivariate logistic regression analysis. A clinical prediction model was subsequently developed. Between October 2009 and May 2011, data from an additional 145 patients with SPN were used to validate this new clinical prediction model (group B). The same data were also estimated with two previously published models for comparison with our new model.
The median patient age was 57.1 years in group A; 54% of the nodules were malignant and 46% were benign. Logistic regression analysis identified six clinical characteristics (age, diameter, border, calcification, spiculation, and family history of tumor) as independent predictors of malignancy in patients with SPN. The area under the receiver operator characteristic (ROC) curve for our model (0.874 ± 0.028) was higher than those generated using the other two reported models. In our model, sensitivity = 94.5%, specificity = 70.0%, positive predictive value = 87.8%, and negative predictive value = 84.8%).
Age, diameter, border, calcification, spiculation, and family history of tumor were independent predictors of malignancy in patients with SPN. Our prediction model was sufficient to estimate malignancy in patients with SPN and proved to be more accurate than the two existing models.
本研究旨在建立数学预测模型，以区分良性和恶性孤立性肺结节（SPN）。
回顾了 2000 年 1 月至 2009 年 9 月期间 371 例 SPN 患者（197 例男性，174 例女性）的记录（A 组）。通过多变量逻辑回归分析收集临床数据，以评估 SPN 恶性的独立预测因素。随后开发了一种临床预测模型。2009 年 10 月至 2011 年 5 月，使用另外 145 例 SPN 患者的数据验证了这个新的临床预测模型（B 组）。还使用了两个先前发表的模型来估计相同的数据，以便与我们的新模型进行比较。
A 组患者的中位年龄为 57.1 岁；54%的结节为恶性，46%为良性。逻辑回归分析确定了 6 个临床特征（年龄、直径、边界、钙化、分叶和肿瘤家族史）为 SPN 患者恶性的独立预测因素。我们模型的接收者操作特征（ROC）曲线下面积（0.874±0.028）高于其他两个报告模型。在我们的模型中，敏感性=94.5%，特异性=70.0%，阳性预测值=87.8%，阴性预测值=84.8%）。
年龄、直径、边界、钙化、分叶和肿瘤家族史是 SPN 患者恶性的独立预测因素。我们的预测模型足以估计 SPN 患者的恶性程度，并且比现有的两个模型更准确。
