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C反应蛋白与鳞状细胞癌抗原联合用于预测食管鳞状细胞癌患者术后预后

Combination of c-reactive protein and squamous cell carcinoma antigen in predicting postoperative prognosis for patients with squamous cell carcinoma of the esophagus.

作者信息

Feng Ji-Feng, Chen Sheng, Yang Xun

机构信息

Department of Thoracic Surgery, Zhejiang Cancer Hospital, Hangzhou 310022, China.

Key Laboratory Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou 310022, China.

出版信息

Oncotarget. 2017 Jun 27;8(38):63132-63139. doi: 10.18632/oncotarget.18667. eCollection 2017 Sep 8.

Abstract

BACKGROUND

We initially proposed a useful and novel prognostic model, named CCS [Combination of c-reactive protein (CRP) and squamous cell carcinoma antigen (SCC)], for predicting the postoperative survival in patients with esophageal squamous cell carcinoma (ESCC).

METHODS

Two hundred and fifty-two patients with resectable ESCC were included in this retrospective study. A logistic regression was performed and yielded a logistic equation. The CCS was calculated by the combined CRP and SCC. The optimal cut-off value for CCS was evaluated by X-tile program. Univariate and multivariate analyses were used to evaluate the predictive factors. In addition, a novel nomogram model was also performed to predict the prognosis for patients with ESCC.

RESULTS

In the current study, CCS was calculated as CRP+6.33 SCC according to the logistic equation. The optimal cut-off value was 15.8 for CCS according to the X-tile program. Kaplan-Meier analyses demonstrated that high CCS group had a significantly poor 5-year cancer-specific survival (CSS) than low CCS group (10.3% vs. 47.3%, <0.001). According to multivariate analyses, CCS ( =0.004), but not CRP ( =0.466) or SCC ( =0.926), was an independent prognostic factor. A nomogram could be more accuracy for CSS (Harrell's c-index: 0.70).

CONCLUSION

The CCS is a usefull and independent predictive factor in patients with ESCC.

摘要

背景

我们最初提出了一种有用且新颖的预后模型,名为CCS[C反应蛋白(CRP)与鳞状细胞癌抗原(SCC)的组合],用于预测食管鳞状细胞癌(ESCC)患者的术后生存率。

方法

本回顾性研究纳入了252例可切除的ESCC患者。进行逻辑回归分析并得出一个逻辑方程。通过联合CRP和SCC计算CCS。使用X-tile程序评估CCS的最佳临界值。采用单因素和多因素分析来评估预测因素。此外,还构建了一种新颖的列线图模型来预测ESCC患者的预后。

结果

在本研究中,根据逻辑方程,CCS计算为CRP + 6.33 SCC。根据X-tile程序,CCS的最佳临界值为15.8。Kaplan-Meier分析表明,高CCS组的5年癌症特异性生存率(CSS)显著低于低CCS组(10.3%对47.3%,<0.001)。多因素分析显示,CCS(=0.004)是独立的预后因素,而CRP(=0.466)或SCC(=0.926)不是。列线图对CSS的预测可能更准确(Harrell's c指数:0.70)。

结论

CCS是ESCC患者有用的独立预测因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a749/5609909/30fcfeb9cf6a/oncotarget-08-63132-g001.jpg

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