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Prediction of metachronous multiple primary cancers following the curative resection of gastric cancer

Title
Prediction of metachronous multiple primary cancers following the curative resection of gastric cancer
Authors
Chan Kim;Hong Jae Chon;Sun Young Rha;Sung Hoon Noh;Hyun Cheol Chung5;Hei-Cheul Jeung;Kiyeol Kim;Beodeul Kang
Issue Date
2013
Journal Title
BMC Cancer
ISSN
1471-2407
Citation
BMC Cancer, Vol.13(null) : 394, 2013
Abstract
BACKGROUND: Due to improved survival rate, gastric cancer (GC) patients have an increased risk of developing multiple primary cancer (MPC). The purpose of this study is to evaluate the clinicopathological features of MPC and to generate useful tools for the prediction of metachronous MPC following gastrectomy. METHODS: 3066 patients who underwent curative resection of GC were reviewed retrospectively, based on the clinical information and the medical record. RESULTS: The 5-year incidence of MPC was 2.5%. Of these, 54.3% had a metachronous MPC, while 45.7% had a synchronous MPC. The most prevalent site of metachronous MPC was the colorectum (26.3%), followed by lung (23.7%) and liver (18.4%). Multivariate logistic regression analysis revealed that old age at the time of GC diagnosis (>=60 years), early stage of GC (stage I and II), and multiplicity of GC at the time of gastrectomy were independent predictive factors for metachronous MPC. GC patients with either metachronous or synchronous MPC showed poorer survival than patients without MPC. In addition, patients with a metachronous MPC showed late survival disadvantage, while patients with a synchronous MPC showed early survival disadvantage. Furthermore, we were able to develop and internally validate a nomogram to predict the metachronous MPC after curative gastrectomy (C-index = 0.72). CONCLUSION: Patients at high risk of developing metachronous MPC after curative resection of GC were identified. Individual risk of developing metachronous MPC could be predicted by a novel nomogram. Further external validation with independent patient cohorts is required to improve the accuracy of prediction.
URI

http://ir.ymlib.yonsei.ac.kr/handle/22282913/87776
DOI
10.1186/1471-2407-13-394
Appears in Collections:
1. 연구논문 > 1. College of Medicine > Dept. of Surgery
1. 연구논문 > 1. College of Medicine > Dept. of Internal Medicine
1. 연구논문 > 5. Research Institutes > Oral Cancer Research Institute
Yonsei Authors
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