Guangdong Lung Cancer Institute, Guangdong General Hospital and Guangdong Academy of Medical Sciences, Guangzhou, China.
J Thorac Oncol. 2012 Oct;7(10):1534-40. doi: 10.1097/JTO.0b013e3182641b82.
Computed tomography screening can detect lung cancer that is curable. However, some studies demonstrated that the risk for false-positives was about 50%. To make screening more efficient, we sought to create a forecasting model for individuals with different risks for lung cancer.
We used multiple logistic regression analysis to identify independent predictors and to develop a prediction model. The pathological diagnoses in Guangdong Lung Cancer Institute were consecutively chosen as probands. All first-degree relatives of probands and their spouses were included as subjects. We divided the probands and their spouses into three subgroups according to the odds ratios (ORs), and the accuracy of lung cancer predictions for patients within the subgroups increased synchronously.
There were 633 proband pedigrees and 565 spouse pedigrees. Independent predictors of lung cancer included sex (OR, 1.6; 95% confidence interval [CI], 1.1-2.3), smoking history (light smoker: OR, 1.1; 95% CI, 0.7-1.8; heavy smoker: OR, 4.7; 95% CI, 3.1-7.1), lung disease history (OR, 5.3; 95% CI, 2.8-10.0), occupational exposure (OR, 1.6; 95% CI, 1.1-2.2), and number of affected individuals among first-degree relatives (n = 1: OR, 2.1; 95% CI, 1.3-3.4; n ≥ 2: OR, 4.7; 95% CI, 0.5-41.2). The accuracy of the pretest probability increased for those with higher ORs: low-OR subgroup, 68.3%; mid-OR subgroup, 84.0%; and high-OR subgroup, 91.9%.
Our prediction rule is recommended for estimating the pretest probability of lung cancer, thereby facilitating early screening.
计算机断层扫描筛查可以发现可治愈的肺癌。然而，一些研究表明，假阳性的风险约为 50%。为了使筛查更有效，我们试图为具有不同肺癌风险的个体创建一个预测模型。
我们使用多元逻辑回归分析来识别独立的预测因子并开发预测模型。广东肺癌研究所的病理诊断连续作为病例。所有病例的一级亲属及其配偶均作为研究对象。我们根据比值比（OR）将病例及其配偶分为三个亚组，亚组内患者的肺癌预测准确性也随之同步提高。
共纳入 633 个病例家系和 565 个配偶家系。肺癌的独立预测因子包括性别（OR，1.6；95%置信区间[CI]，1.1-2.3）、吸烟史（轻度吸烟者：OR，1.1；95% CI，0.7-1.8；重度吸烟者：OR，4.7；95% CI，3.1-7.1）、肺部疾病史（OR，5.3；95% CI，2.8-10.0）、职业暴露（OR，1.6；95% CI，1.1-2.2）以及一级亲属中受影响个体的数量（n=1：OR，2.1；95% CI，1.3-3.4；n≥2：OR，4.7；95% CI，0.5-41.2）。具有更高 OR 的个体的预测试概率准确性提高：低 OR 亚组，68.3%；中 OR 亚组，84.0%；高 OR 亚组，91.9%。
我们的预测规则推荐用于估计肺癌的预测试概率，从而有助于早期筛查。
