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首页> 外文期刊>Oncology letters >Nomogram construction for predicting survival of patients with non-small cell lung cancer with malignant pleural or pericardial effusion based on SEER analysis of 10,268 patients
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Nomogram construction for predicting survival of patients with non-small cell lung cancer with malignant pleural or pericardial effusion based on SEER analysis of 10,268 patients

机译:基于10,268名患者的Seer分析,对恶性胸膜肺癌患者存活的载体构建

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摘要

Determining the accurate outcome of patients with non-small cell lung cancer (NSCLC) and malignant pleural effusion (MPE) or malignant pleural pericardial effusion (MPCE) at the initial diagnosis remains a challenge. The aim of the present study was to develop an effective nomogram for individualized estimation of overall survival in these patients. Patients diagnosed between January 2010 and December 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Age, race, sex, grade, histology, laterality, stage and status of MPE or MPCE at initial diagnosis were included as covariates. Several survival models were created and the performance of each was evaluated. The most effective model was then validated by internal bootstrap resampling and by using an independent external cohort. A nomogram was created based on this survival model and the predictive accuracy of the nomogram was evaluated by calibration plots. Data from 10,268 patients with lung cancer with MPE or MPCE at initial diagnosis were collected. The multivariate analysis with a lognormal model suggested that age, race, sex, histology, stage and status of MPE or MPCE at initial diagnosis were significant independent factors to predict survival. A nomogram was constructed based on the lognormal survival model, which showed the best performance. The concordance index of the survival model in the SEER cohort was 0.736. Both internal and external validation showed an acceptable level of agreement between the nomogram-predicted survival probability and actual survival. The nomogram of the present study based on a large cohort from the SEER database may improve prognostic prediction of patients with NSCLC with MPE or MPCE at initial diagnosis, and allow physicians to make appropriate decisions for disease management of their patients.
机译:在初步诊断中确定非小细胞肺癌(NSCLC)和恶性胸腔积液(MPE)或恶性胸膜心包(MPE)的准确结果仍然是一个挑战。本研究的目的是开发有效的载体,以便个体化估算这些患者的整体生存率。 2010年1月至2015年12月诊断的患者选自监测,流行病学和最终结果(SEER)数据库。作为协变量,包括MPE或MPCE的年龄,种族,性别,等级,组织学,横向,阶段和地位。创建了几种生存模型,评估了每个生存模型。然后通过内部引导重采样验证最有效的模型,并使用独立的外部群组验证。基于该生存模型创建了一个铭文,并通过校准图评估了墨迹图的预测精度。收集来自10,268名肺癌患者的数据,MPE或MPCE初期诊断。具有Lognormal模型的多变量分析表明,初步诊断时,MPE或MPCE的年龄,种族,性别,组织学,阶段和地位是预测生存率的重要因素。基于Lognormal Suvival模型构建了一种铭文,其显示出最佳性能。 Seer Cohort中生存模型的一致性指数为0.736。内部和外部验证都显示了载体预测的生存概率和实际存活之间可接受的协议水平。本研究的载体基于来自SEER数据库的大队列的基于大群组,可以改善NSCLC患者的预后预测MPE或MPCE在初步诊断,并允许医生对其患者的疾病管理做出适当的决定。

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