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Original Article | Open Access

Development and validation of a nomogram to predict cardiac death after radiotherapy for esophageal cancer

Xinfang Lv1,2,Xue Wu2,3,Kai Liu2Xinke Zhao2Chenliang Pan4Jing Zhao4Juan Chang5Huan Guo6Xiang Gao2Xiaodong Zhi2Chunzhen Ren2Qilin Chen2Hugang Jiang2Chunling Wang2Ying‐Dong Li2( )
Department of Geriatrics, Affiliated Hospital of Gansu University of Traditional Chinese Medicine, Lanzhou, Gansu, China
School of Integrative Medicine, Gansu University of Chinese Medicine, Lanzhou, Gansu, China
Department of Cardiology, The Second Hospital of Lanzhou University, Lanzhou, Gansu, China
Cardiovascular Disease Center, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
Department of Traditional Medicine, Gansu Provincial Hospital, Lanzhou, Gansu, China
Center for Translational Medicine, Gansu Provincial Academic Institute for Medical Research, Lanzhou, Gansu, China

Xinfang Lv and Xue Wu contributed equally to this work and shared the first authorship.

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Graphical Abstract

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.

Abstract

Background

Patients 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.

Methods

A 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.

Results

The 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).

Conclusions

Our nomogram may assist clinicians in making clinical decisions about patients undergoing radiotherapy for esophageal cancer based on early detection of cardiac death risk.

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Cancer Innovation
Pages 391-404
Cite this article:
Lv X, Wu X, Liu K, et al. Development and validation of a nomogram to predict cardiac death after radiotherapy for esophageal cancer. Cancer Innovation, 2023, 2(5): 391-404. https://doi.org/10.1002/cai2.89

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Received: 11 February 2023
Accepted: 30 June 2023
Published: 01 September 2023
© 2023 The Authors. Tsinghua University Press.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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