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Recurrence and prognostic model for identifying patients at risk for esophageal cancer after surgery

Authors Chen D, Wang W, Chen Y, Hu J, Yang M, Mo J, Wen Z

Received 2 September 2018

Accepted for publication 10 October 2018

Published 21 November 2018 Volume 2018:10 Pages 6109—6120

DOI https://doi.org/10.2147/CMAR.S186194

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Colin Mak

Peer reviewer comments 2

Editor who approved publication: Dr Xueqiong Zhu


Dongni Chen,1,* Weidong Wang,1,* Youfang Chen,1 Jia Hu,1 Men Yang,2 Junxian Mo,3 Zhesheng Wen1

1Department of Thoracic Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; 2Department of Cardio-Thoracic Surgery, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong 518000, China; 3Department of Cardio-Thoracic Surgery, The Seventh Affiliated Hospital of Guangxi Medical University, Wuzhou, Guangxi 543000, China

*These authors contributed equally to this work

Objective: The aim of this study was to construct a risk model to assess overall survival (OS) and disease-free survival (DFS) in patients with esophageal cancer (EC) after surgery.
Patients and methods: A total of 872 consecutive EC patients who had undergone surgery between February 2009 and October 2012 were retrospectively analyzed. The cutoff for risk value (RV) was inferred by receiver operating characteristic curves and the Youden index. A log-rank test was used to compare the survival curves, and a Cox regression analysis was performed to clarify the significant prognostic factors.
Results: The area under the curve was 0.688 for OS and 0.645 for DFS. The survival rates were 69.4% (259/373) and 39.1% (195/499), and the rates of recurrence were 19.2% (70/364) and 27.6% (132/479), respectively, for RV<0.218 and RV≥0.218 (Χ2=78.83, P<0.001; Χ2=9.07, P=0.003; respectively). A multivariate Cox regression analysis identified cases suffering from higher overall mortalities with RV≥0.218 compared to RV<0.218 (HR=1.45; 95% CI, 1.21–2.02; P=0.015); similar results were also found for DFS (HR=1.38; 95% CI, 1.03–1.86; P=0.033). Kaplan–Meier survival curves showed that cases with RV<0.218 had better OS and DFS than cases with RV≥0.218 (log rank = 75.80, P<0.001; log rank = 24.78, P<0.001).
Conclusion: This model could be applied to an integrated assessment of recurrence and prognostic risk after the surgical treatment of EC.

Keywords: esophageal cancer, surgery, recurrence, prognosis, model

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