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자료유형
학술저널
저자정보
Lejia Sun (PUMC and Chinese Academy of Medical Sciences) Wenmo Hu (PUMC and Chinese Academy of Medical Sciences) Meixi Liu (PUMC and Chinese Academy of Medical Sciences) Yang Chen (PUMC and Chinese Academy of Medical Sciences) Bao Jin (PUMC and Chinese Academy of Medical Sciences) Haifeng Xu (PUMC and Chinese Academy of Medical Sciences) Shunda Du (PUMC and Chinese Academy of Medical Sciences) Yiyao Xu (PUMC and Chinese Academy of Medical Sciences) Haitao Zhao (PUMC and Chinese Academy of Medical Sciences) Xin Lu (PUMC and Chinese Academy of Medical Sciences) Xinting Sang (PUMC and Chinese Academy of Medical Sciences) Shouxian Zhong (PUMC and Chinese Academy of Medical Sciences) Huayu Yang (PUMC and Chinese Academy of Medical Sciences) Yilei Mao (PUMC and Chinese Academy of Medical Sciences)
저널정보
대한암학회 Cancer Research and Treatment Cancer Research and Treatment 제52권 제4호
발행연도
2020.1
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1,199 - 1,210 (12page)

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Purpose The systemic inflammation response index (SIRI) has been reported to have prognostic ability in various solid tumors but has not been studied in gallbladder cancer (GBC). We aimed to determine its prognostic value in GBC. Materials and Methods From 2003 to 2017, patients with confirmed GBC were recruited. To determine the SIRI’s optimal cutoff value, a time-dependent receiver operating characteristic curve was applied. Univariate and multivariate Cox analyses were performed for the recognition of significant factors. Then the cohort was randomly divided into the training and the validation set. A nomogram was constructed using the SIRI and other selected indicators in the training set, and compared with the TNM staging system. C-index, calibration plots, and decision curve analysis were performed to assess the nomogram’s clinical utility. Results One hundred twenty-four patients were included. The SIRI’s optimal cutoff value divided patients into high (≥ 0.89) and low SIRI (< 0.89) groups. Kaplan-Meier curves according to SIRI levels were significantly different (p < 0.001). The high SIRI group tended to stay longer in hospital and lost more blood during surgery. SIRI, body mass index, weight loss, carbohydrate antigen 19-9, radical surgery, and TNM stage were combined to generate a nomogram (C-index, 0.821 in the training cohort, 0.828 in the validation cohort) that was significantly superior to the TNM staging system both in the training (C-index, 0.655) and validation cohort (C-index, 0.649). Conclusion The SIRI is an independent predictor of prognosis in GBC. A nomogram based on the SIRI may help physicians to precisely stratify patients and implement individualized treatment.

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