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Novel Model to Predict the Prognosis of Patients with Stage II–III Colon Cancer
BioMed Research International ( IF 3.246 ) Pub Date : 2020-11-23 , DOI: 10.1155/2020/8812974
Yansong Xu 1, 2 , Fangfang Liang 1, 2 , Yi Chen 1, 2 , Zhen Wang 1, 2 , Huage Zhong 1, 2 , Weizhong Tang 1, 2
Affiliation  

Different opinions exist on the relationship between the C-reactive protein-to-albumin ratio (CAR) and the prognosis of colon cancer. This study is aimed at evaluating the relationship between CAR and prognosis of stage II–III colon cancer and establishing a clinical prognosis model. Patients were randomised to a training set (566 cases) and validation set (110 cases). The relationship between CAR and clinicopathological variables was calculated, and the Kaplan-Meier method was used to analyse the overall survival (OS) rate of colon cancer. In the training set, colon cancer independent risk factors were included in the prognosis model and then tested in the validation set. The accuracy and discrimination of the model were assessed using the C-index and calibration curves. Compared with patients with low CAR, patients with high CAR showed significantly poorer survival (). In the multivariate analysis, CAR, carcinoembryonic antigen (CEA), lymph node metastasis, operation mode, and perineural invasion were identified as independent prognostic indicators and adopted to establish the prediction model. The C-index of the nomogram for predicting OS reached 0.751 in the training set and 0.719 in the validation set. The calibration curve exhibited good consistency. In the present study, the CAR may be an independent prognostic factor for stage II–III colon cancer, and the nomogram has a certain predictive value. However, further prospective large-sample research needs to be conducted to validate our findings.

中文翻译:

新型模型预测II–III期结肠癌患者的预后

关于C反应蛋白与白蛋白之比(CAR)与结肠癌预后之间的关系,存在不同的意见。这项研究旨在评估CAR与II–III期结肠癌预后之间的关系,并建立临床预后模型。将患者随机分为训练组(566例)和验证组(110例)。计算CAR与临床病理变量之间的关系,并使用Kaplan-Meier方法分析结肠癌的总生存率。在训练集中,结肠癌独立危险因素包括在预后模型中,然后在验证集中进行测试。使用C指数和校准曲线评估模型的准确性和辨别力。与低CAR患者相比,)。在多变量分析中,将CAR,癌胚抗原(CEA),淋巴结转移,手术模式和神经周浸润确定为独立的预后指标,并建立了预测模型。用于预测OS的列线图的C指数在训练集中达到0.751,在验证集中达到0.719。校准曲线表现出良好的一致性。在本研究中,CAR可能是II-III期结肠癌的独立预后因素,并且诺模图具有一定的预测价值。但是,需要进行进一步的前瞻性大样本研究以验证我们的发现。
更新日期:2020-11-23
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