TY -的AU -王,小芳盟——张,燕盟,郝Shiying AU -郑,乐盟——廖,嘉盟——你们Chengyin盟——夏,Minjie AU -王,奥利弗盟——刘,莫迪AU -翁,Ching Ho AU - Duong,儿子问非盟-金,博盟——阿尔弗雷德,肖恩T非盟-斯登,弗兰克盟——Kanov劳拉盟——西尔维斯特,卡尔·G盟——扩大埃里克•AU - McElhinney脱B非盟- Ling,雪峰B PY - 2019 DA - 2019/05/16 TI - 1年期肺癌的风险事件的预测:使用缅因州电子健康记录的前瞻性研究JO - J Med Internet Res SP - e13260 VL - 21 IS - 5 KW -肺癌风险预测模型KW -电子健康记录KW -前瞻性研究AB -背景:肺癌是全球癌症死亡的主要原因。早期发现有肺癌风险的个体对于降低死亡率至关重要。目的:本研究的目的是建立并验证一种前瞻性风险预测模型，以识别普通人群中未来1年内有新发肺癌风险的患者。方法:从缅因州健康信息交换网络中提取个人患者电子健康记录(EHRs)的数据。研究人群包括2016年4月1日至2018年3月31日期间至少有一次电子病历的患者，且无肺癌病史。建立回顾性队列(N=873,598)和前瞻性队列(N=836,659)进行模型构建和验证。采用极限梯度增强(XGBoost)算法建立模型。它给每个人打分，以量化2016年10月1日至2017年9月31日期间新发肺癌诊断的概率。该模型使用前6个月的回顾性队列临床资料进行训练，并通过前瞻性队列进行验证，以预测2017年4月1日至2018年3月31日期间发生肺癌的风险。 Results: The model had an area under the curve (AUC) of 0.881 (95% CI 0.873-0.889) in the prospective cohort. Two thresholds of 0.0045 and 0.01 were applied to the predictive scores to stratify the population into low-, medium-, and high-risk categories. The incidence of lung cancer in the high-risk category (579/53,922, 1.07%) was 7.7 times higher than that in the overall cohort (1167/836,659, 0.14%). Age, a history of pulmonary diseases and other chronic diseases, medications for mental disorders, and social disparities were found to be associated with new incident lung cancer. Conclusions: We retrospectively developed and prospectively validated an accurate risk prediction model of new incident lung cancer occurring in the next 1 year. Through statistical learning from the statewide EHR data in the preceding 6 months, our model was able to identify statewide high-risk patients, which will benefit the population health through establishment of preventive interventions or more intensive surveillance. SN - 1438-8871 UR - //www.mybigtv.com/2019/5/e13260/ UR - https://doi.org/10.2196/13260 UR - http://www.ncbi.nlm.nih.gov/pubmed/31099339 DO - 10.2196/13260 ID - info:doi/10.2196/13260 ER -