列线图
医学
累积发病率
入射(几何)
十分位
内科学
肺癌
人口
肿瘤科
恶性肿瘤
置信区间
风险评估
队列
统计
环境卫生
物理
光学
计算机科学
计算机安全
数学
作者
Huaqiang Zhou,Jiayi Shen,Yaxiong Zhang,Yan Huang,Wenfeng Fang,Yunpeng Yang,Shaodong Hong,Jiaqing Liu,Wa Xian,Zhonghan Zhang,Yuxiang Ma,Ting Zhou,Hongyun Zhao,Li Zhang
出处
期刊:Annals of Translational Medicine
[AME Publishing Company]
日期:2019-09-01
卷期号:7 (18): 439-439
被引量:25
标识
DOI:10.21037/atm.2019.09.01
摘要
With the improvement of survival for non-small cell lung cancer (NSCLC), research focused on second primary malignancy (SPM) in NSCLC survivors is becoming urgent. This study aimed to estimate the risk of SPM in NSCLC patients.We retrospectively analysed NSCLC patients diagnosed between 2004 and 2010 in SEER database. We firstly evaluated the crude and cumulative incidence of SPM. SPM incidence in NSCLC survivors compared to that in the reference population was calculated as standardized incidence ratio (SIR). A competing risk nomogram was also built, to predict the incidence of SPM.The crude and 10-year cumulative incidences of SPM were 4.04% and 5.05%, respectively, while the SIR was 1.62. The nomogram was well calibrated and had good discriminative ability, with c-index of 0.80. It showed a significantly wide interval of SPM cumulative incidence between the first and tenth-decile according to the risk model (1.04% vs. 16.70%, P<0.05). The decision curve analysis indicated that the clinical net benefit of risk model was larger than that in other scenarios (all-screening or no-screening) in a range of threshold probabilities (1% to 20%).Our study firstly performed a systematic estimation of the incidence of SPM in NSCLC, which implied the necessity of a risk predicting model. We developed the first competing risk nomogram to predict the risk of SPM, which performed well in the evaluation and might be helpful for individualized SPM screening.
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