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Article type: Research Article
Authors: Yu, Yongming | Wu, Zhou | Shen, Zhonglei | Cao, Yisheng*
Affiliations: Department of Colorectal Surgery, HwaMei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang, China
Correspondence: [*] Corresponding author: Yisheng Cao, Department of Colorectal Surgery, HwaMei Hospital, University of Chinese Academy of Sciences, No. 41 Xibei Road, Haishu District, Ningbo, Zhejiang 315000, China. E-mail: dr_caoyisheng@sina.com.
Abstract: BACKGROUND: Anastomotic leak (AL), as one of the most devastating complications, is the leading cause of mortality in colorectal cancer (CRC) patients after resection. This study was aimed to investigate potential risk factors for AL in elderly surgical CRC patients. METHODS: A total of 1068 elderly subjects who underwent elective curative colorectal surgery from 2012 to 2018 were retrospectively evaluated and enrolled into this study population. The predictive value of C-reactive protein-to-albumin ratio (CAR) for AL in surgical CRC patients was evaluated by receiver operating characteristic (ROC) curve analysis. Potential risk factors for AL were assessed by the univariate and multivariate logistic regression analyses. RESULTS: Of all the 1068 enrolled patients, 81 patients have developed AL with an incidence of 7.6% (81/1068). Preoperative CAR was an effective predictor for AL with an area under the curve (AUC) of 0.758, 95% CI of 0.700–0.817, a cut-off value of 2.44, a sensitivity of 61.09% and a specificity of 80.25%, respectively (P< 0.001). Duration of operation (OR: 2.05, 95% CI: 1.21–3.44, P= 0.013) and preoperative CAR (OR: 1.94, 95% CI: 1.21–3.11, P= 0.007) were two independent risk factors for AL by the multivariate logistic regression analysis. CONCLUSIONS: Our study indicate that preoperative CAR level and duration of operation were two independent predictors for AL among elderly surgical CRC patients.
Keywords: Colorectal cancer, anastomotic leak, risk factor, C-reactive protein-to-albumin ratio
DOI: 10.3233/CBM-190470
Journal: Cancer Biomarkers, vol. 27, no. 3, pp. 295-302, 2020
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