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Objective To investigate the risk factors of abdominal infection after orthotopic liver transplantation. Methods Clinical data of 284 recipients undergoing orthotopic liver transplantation were retrospectively analyzed. All recipients were divided into the infection group (n=51) and non-infection group (n=233) according to the incidence of postoperative abdominal infection. Univariate and multivariate logistic regression analyses were used to identify the risk factors of abdominal infection. Nomogram prediction models were constructed and the prediction efficiency of these models was evaluated. The predictive value of continuous variables for abdominal infection was assessed. Results Among 284 recipients, 51 developed abdominal infection with an incidence of 18.0%. Diabetes mellitus before surgery[odds ratio (OR) 2.66, 95% confidence interval (CI) 1.13-6.14, P=0.013], long operation time (OR 1.98, 95%CI 1.03-3.57, P=0.038), low prognostic nutritional index (PNI) (OR 2.18, 95%CI 1.06-4.44, P=0.023), high systemic immune-inflammation index (SII) (OR 2.21, 95%CI 1.06-4.78, P=0.012) and high C-reactive protein/albumin ratio (CAR) (OR 1.90, 95%CI 1.05-3.49, P=0.029) were independent risk factors for abdominal infection after liver transplantation. The area under curve (AUC) of nomogram model for predicting abdominal infection after liver transplantation was 0.761. The standard model yielded high consistency. CAR, PNI and SII were all predictors of abdominal infection after liver transplantation (all P < 0.05), with AUC of 0.648, 0.611 and 0.648, and cut-off values of 2.75, 43.15 and 564.50, respectively. Conclusions CAR, SII and PNI are predictors of abdominal infection after liver transplantation. The nomogram model based on PNI, SII and CAR may effectively predict the incidence of abdominal infection after liver transplantation.
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Objective:To investigate the relationship between systemic immune-inflammation index (SII) and the prognosis of esophageal cancer patients treated with radical radiotherapy and to predict the prognosis of the patients using the SII combined with clinical staging.Methods:A retrospective analysis was conducted for 248 patients with esophageal cancer who were admitted to the Department of Radiotherapy in the Fourth Hospital of Hebei Medical University between 2014 and 2016. These patients included 146 males and 102 females, with a median age of 67 years. Among them, 134 patients received concurrent chemotherapy and 114 patients received radiotherapy alone. The SII before radiotherapy was defined as platelet count × neutrophil count/lymphocyte count. The patients were divided into a low-SII group and a high-SII group according to the optimal cutoff value of pretreatment SII determined by the receiver operating characteristics (ROC) curve. Survival analysis was calculated using the Kaplan-Meier method, and the Cox proportional hazards model was used for multivariate analysis. For these patients, the prognosis effects and the predictive value for survival of different SII levels combined with TNM staging were compared.Results:According to the ROC curves, the optimal cutoff value of SII before radiotherapy was 740.80. Based on this number, the patients were divided into a low-SII group (< 740.80, 150 cases) and a high-SII group (≥ 740.80, 98 cases). The objective response rate of the low-SII group was significantly higher than that of the high-SII group (86.0% vs 75.5%, χ2=4.39, P=0.036). The 1-, 3-, and 5-year overall survival (OS) rates of the low-SII group were 78.6%, 45.6%, and 32.3%, respectively. These rates were significantly higher than the corresponding rates of the high-SII group, which were 71.0%, 28.3%, and 16.4% ( χ2=11.22, P=0.001), respectively. Moreover, the 1-, 3- and 5-year progression-free survival (PFS) rates of the low-SII group were 67.0%, 36.9%, and 32.0%, respectively. Again, these rates were significantly higher than those of the high-SII group, which were 45.5%, 17.5%, and 12.5% ( χ2=15.38, P < 0.001), respectively. Multivariate analysis showed that TNM staging, treatment method, and SII were independent prognostic factors for OS and PFS ( HR=1.39-1.60, P<0.05). Patients with low SII and early clinical staging had a better prognosis than other subgroups ( χ2=13.68, 13.43, P=0.001). The area under curve (AUC) of SII combined with TNM staging (0.70) was higher than that of SII (0.63) and TNM staging (0.62) ( Z=2.48, 2.57, P < 0.05). Conclusions:Pretreatment SII has a high predictive value for the prognosis of esophageal cancer after radiotherapy, and higher SII indicates a worse prognosis. Thus, combining SII with TNM staging can improve the prediction accuracy of the prognosis of esophageal cancer patients.