A risk model for prediction of lung cancer
A risk model for prediction of lung cancer
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DOI：
10.1093/jnci/djk153
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发表时间：
2007-05-02
影响因子：
10.3
通讯作者：
Etzel, Carol J.
中科院分区：
文献类型：
--
作者：
Spitz, Margaret R.;Hong, Waun Ki;Etzel, Carol J.
背景可靠的风险预测工具估计个人肺癌的概率有重要的公共卫生意义。我们构建并验证了一个全面的临床工具，肺癌风险预测吸烟status.Methods流行病学数据从1851例肺癌患者和2001年匹配的对照组被随机分为单独的训练（75%的数据）和验证（25%的数据）集从来没有，以前，和当前的吸烟者，和多变量模型构建的训练集。通过检查受试者工作特征曲线下的面积和一致性统计，在验证集中评估模型的区分能力。使用国家发病率和死亡率数据计算肺癌的绝对1年风险。一个有序的风险指数为每个吸烟状态类别，通过总结每个风险factor.Results的多变量回归分析的比值比，有统计学意义的相关性与肺癌（环境烟草烟雾，癌症家族史，粉尘暴露，以前的呼吸道疾病，吸烟史变量）的所有变量有很强的生物学合理的病因作用的疾病。从未吸烟者、既往吸烟者和当前吸烟者模型的验证集中的一致性统计量分别为0.57、0.63和0.58。对于一个假设的男性吸烟者，计算出的1年肺癌的绝对危险度为8.68%，估计的相对危险度接近9。顺序风险指数表现良好，在指定的高风险类别的真阳性率分别为69%和70%，目前和以前的吸烟者，respectively.Conclusions如果在其他研究中证实，这种风险评估程序可以使用容易获得的临床信息，以确定个人谁可能受益于增加筛查监测肺癌。虽然一致性统计是适度的，但它们与其他风险预测模型的一致性是一致的。
Background Reliable risk prediction tools for estimating individual probability of lung cancer have important public health implications. We constructed and validated a comprehensive clinical tool for lung cancer risk prediction by smoking status.Methods Epidemiologic data from 1851 lung cancer patients and 2001 matched control subjects were randomly divided into separate training (75% of the data) and validation (25% of the data) sets for never, former, and current smokers, and multivariable models were constructed from the training sets. The discriminatory ability of the models was assessed in the validation sets by examining the areas under the receiver operating characteristic curves and with concordance statistics. Absolute 1-year risks of lung cancer were computed using national incidence and mortality data. An ordinal risk index was constructed for each smoking status category by summing the odds ratios from the multivariable regression analyses for each risk factor.Results All variables that had a statistically significant association with lung cancer (environmental tobacco smoke, family history of cancer, dust exposure, prior respiratory disease, and smoking history variables) have strong biologically plausible etiologic roles in the disease. The concordance statistics in the validation sets for the never, former, and current smoker models were 0.57, 0.63, and 0.58, respectively. The computed 1-year absolute risk of lung cancer for a hypothetical male current smoker with an estimated relative risk close to 9 was 8.68%. The ordinal risk index performed well in that true-positive rates in the designated high-risk categories were 69% and 70% for current and former smokers, respectively.Conclusions If confirmed in other studies, this risk assessment procedure could use easily obtained clinical information to identify individuals who may benefit from increased screening surveillance for lung cancer. Although the concordance statistics were modest, they are consistent with those from other risk prediction models.