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jdk.nashorn.api.scripting.NashornScriptEngine.getInterface(java.lang.Object,java.lang.Class) public java.lang.Object jdk.nashorn.api.scripting.NashornScriptEngine.getInterface(java.lang.Class) public java.lang.Object jdk.nashorn.api.scripting.NashornScriptEngine.invokeMethod(java.lang.Object,java.lang.String,java.lang.Object[]) throws javax.script.ScriptException,java.lang.NoSuchMethodException public java.lang.Object jdk.nashorn.api.scripting.NashornScriptEngine.invokeFunction(java.lang.String,java.lang.Object[]) throws javax.script.ScriptException,java.lang.NoSuchMethodException public javax.script.Bindings jdk.nashorn.api.scripting.NashornScriptEngine.createBindings() public java.lang.Object javax.script.AbstractScriptEngine.get(java.lang.String) public void javax.script.AbstractScriptEngine.put(java.lang.String,java.lang.Object) public javax.script.ScriptContext javax.script.AbstractScriptEngine.getContext() public java.lang.Object javax.script.AbstractScriptEngine.eval(java.lang.String,javax.script.Bindings) throws javax.script.ScriptException public java.lang.Object javax.script.AbstractScriptEngine.eval(java.io.Reader) throws javax.script.ScriptException public java.lang.Object javax.script.AbstractScriptEngine.eval(java.lang.String) throws javax.script.ScriptException public java.lang.Object javax.script.AbstractScriptEngine.eval(java.io.Reader,javax.script.Bindings) throws javax.script.ScriptException public void javax.script.AbstractScriptEngine.setContext(javax.script.ScriptContext) public javax.script.Bindings javax.script.AbstractScriptEngine.getBindings(int) public void javax.script.AbstractScriptEngine.setBindings(javax.script.Bindings,int) public final void java.lang.Object.wait() throws java.lang.InterruptedException public final void java.lang.Object.wait(long,int) throws java.lang.InterruptedException public final native void java.lang.Object.wait(long) throws java.lang.InterruptedException public 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Journal of Southern Medical University ›› 2017, Vol. 37 ›› Issue (05): 622-.

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C-reactive protein/albumin ratio as a novel inflammation-based prognostic index for predicting outcomes of patients with colorectal cancer

  

  • Online:2017-05-20 Published:2017-05-20

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Abstract: Objective To evaluate the association of C-reactive protein/albumin ratio (CAR) with the prognosis of patients with colorectal cancer and compare the prognostic value of CAR with other inflammation-based prognostic scoring systems. Methods We retrospectively evaluated 163 newly diagnosed colorectal cancer patients in Nanfang Hospital between January, 2007 and December, 2014. All recommended cutoff values of the clinicopathological factors were defined using receiveroperating characteristic (ROC) curve analyses. We evaluated the prognostic value of CAR in comparison with Glasgow Prognostic Score (GPS) and neutrophil lymphocyte ratio (NLR) with the area under the ROC curve. Univariate and multivariate analyses using the Cox proportional hazards model were performed to identify the factors closely associated with overall survival of the patients. Kaplan-Meier analysis was used to compare overall survival curves between patients with a high CAR and those with a low CAR. Results The recommended cutoff value of CAR was 0.132. Kaplan-Meier analysis and log rank test demonstrated a significant difference in the overall survival between patients with a low CAR (<0.132) and those with a high CAR (≥0.132) (2157.0±395.3 vs 1661.0±136.4 days, P<0.001). The area under the ROC curve of CAR, NLR and GPS was 0.656, 0.550 and 0.642, respectively, indicating a better prognostic value of CAR. Univariate analyses showed that age, C-reactive protein, albumin, CAR, NLR, GPS, platelet, TMN stage, Dukes stage and chemotherapy regimens were associated with the overall survival of the patients (P<0.05). Multivariate analyses showed that TMN stage [HR= 1.689 (95%CI: 1.146-2.488), P=0.008] and Dukes stage [HR=2.447 (95% CI: 1.349-4.441), P=0.003] were associated with the overall survival of the patients. Conclusions Similar to the previously reported inflammation-based prognostic systems (GPS and NLR), CAR is useful for predicting the survival of patients with colorectal cancer and can be complementary to the two prognostic scoring systems.