文献类型：期刊文献

英文题名：Development and validation of a nomogram to predict cardiac death after radiotherapy for esophageal cancer

作者：Lv, Xinfang[1,2];Wu, Xue[2,3];Liu, Kai[2];Zhao, Xinke[2];Pan, Chenliang[4];Zhao, Jing[4];Chang, Juan[5];Guo, Huan[6];Gao, Xiang[2];Zhi, Xiaodong[2];Ren, Chunzhen[2];Chen, Qilin[2];Jiang, Hugang[2];Wang, Chunling[2];Li, Ying-Dong[2]

第一作者：Lv, Xinfang

通信作者：Li, YD[1]

机构：[1]Gansu Univ Tradit Chinese Med, Affiliated Hosp, Dept Geriatr, Lanzhou, Gansu, Peoples R China;[2]Gansu Univ Chinese Med, Sch Integrat Med, Lanzhou, Gansu, Peoples R China;[3]Lanzhou Univ, Hosp 2, Dept Cardiol, Lanzhou, Gansu, Peoples R China;[4]Lanzhou Univ, Hosp 1, Cardiovasc Dis Ctr, Lanzhou, Gansu, Peoples R China;[5]Gansu Prov Hosp, Dept Tradit Med, Lanzhou, Gansu, Peoples R China;[6]Gansu Prov Acad Inst Med Res, Ctr Translat Med, Lanzhou, Gansu, Peoples R China

第一机构：甘肃中医药大学第二附属医院

通信机构：[1]corresponding author), Gansu Univ Chinese Med, Sch Integrat Med, Lanzhou, Gansu, Peoples R China.|[10735]甘肃中医药大学;

年份：2023

卷号：2

期号：5

起止页码：391

外文期刊名：CANCER INNOVATION

收录：Scopus(收录号：2-s2.0-85169161545);WOS:【ESCI(收录号:WOS:001319065900006)】；

基金：National Natural Science Foundation of China, Grant/Award Number: 81873132; 2018 Chinese Medicine Research Projects to Prevent and Treat Major Diseases, Grant/Award Number: GZKZD-2018-02; Lanzhou Science and Technology Plan Project, Grant/Award Number: 2022-3-27; Science and Technology Department of Gansu Province, Grant/Award Number: 21JR7RA399

语种：英文

外文关键词：cardiac death; cardio-oncology; esophageal cancer; nomogram; radiotherapy

摘要：BackgroundPatients frequently die from cardiac causes after radiotherapy for esophageal cancer. Early detection of cardiac death risk in these patients is crucial to improve clinical decision-making and prognosis. Thus, we modeled the risk of cardiac death after irradiation for esophageal cancer.MethodsA retrospective analysis of 37,599 esophageal cancer cases treated with radiotherapy in the SEER database between 2000 and 2018 was performed. The selected cases were randomly assigned to the model development group (n = 26,320) and model validation group (n = 11,279) at a ratio of 7:3. We identified the risk factors most commonly associated with cardiac death by least absolute shrinkage and selection operator regression analysis (LASSO). The endpoints for model development and validation were 5- and 10-year survival rates. The net clinical benefit of the models was evaluated by decision curve analysis (DCA) and concordance index (C-index). The performance of the models was further assessed by creating a receiver operating characteristic curve (ROC) and calculating the area under the curve (AUC). Kaplan-Meier (K-M) survival analysis was performed on the probability of death. Patients were classified according to death probability thresholds. Five- and ten-year survival rates for the two groups were shown using K-M curves.ResultsThe major risk factors for cardiac death were age, surgery, year of diagnosis, sequence of surgery and radiotherapy, chemotherapy and a number of tumors, which were used to create the nomogram. The C-indexes of the nomograms were 0.708 and 0.679 for the development and validation groups, respectively. DCA showed the good net clinical benefit of nomograms in predicting 5- and 10-year risk of cardiac death. The model exhibited moderate predictive power for 5- and 10-year cardiac mortality (AUC: 0.833 and 0.854, respectively), and for the development and validation cohorts (AUC: 0.76 and 0.813, respectively).ConclusionsOur nomogram may assist clinicians in making clinical decisions about patients undergoing radiotherapy for esophageal cancer based on early detection of cardiac death risk. Radiotherapy for esophageal cancer (EC) increased cardiovascular toxicity and mortality in patient d. We developed and validated a nomogram that accurately predicted cardiac mortality variables in EC patients after radiotherapy. Risk factors such as age, year of diagnosis, surgery, sequence of surgery and radiotherapy, chemotherapy, and a number of tumors were included in the nomogram. image