The clinical value of a nomogram constructed from CEA, CA199, PT, FIB, tumor differentiation and TNM stage in colorectal cancer.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-01-01 DOI:10.3233/CBM-230116
Kang Wang, Lulu Ma, Liying Chen, Yatong Jiang, Ningquan Liu, Jianchun Cai, Yiyao Zhang
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Abstract

Background: The accurate Tumor-Node-Metastasis (TNM) staging of colorectal cancer (CRC) is of great guiding significance for the judgment of tumor progression and prognosis, and the formulation of treatment strategies.

Objective: The aim of this study was to construct a recurrence risk scoring (RRS) system and prognostic prediction model to improve the accuracy of staging, prognosis prediction, and clinical decision making in resectable CRC.

Methods: CRC patients who underwent radical resection were retrospectively enrolled into study. Multivariable Cox regression model was applied to screen for independent prognostic factors. The RRS system is composed of independent prognostic factors which was awarded 1point each. A prognostic model composed of RRS and TNM staging system (RRS-TNM model) was applied to predict postoperative recurrence.

Results: TNM stage, tumor differentiation, preoperative elevated Carcinoembryonic Antigen, Carbohydrate Antigen 199, Prothrombin Time and Fibrinogen were the independent prognostic biomarkers. 173 of 540 patients had recurrence. The 5-year cumulative recurrence rate (5-y CRR) and disease-free survival (DFS) of postoperative p-TNM stage I, II, and III were 12.7% and 104.8 months, 26.5% and 89.3 months, and 55.5% and 57.3 months, respectively. The 5-y CRR and DFS of preoperative Low-risk (RRS 0-1score), Middle-risk (RRS 2-3scores), and High-risk (RRS 4-5scores) groups were 13.9% and 101.1 months, 40.9% and 75.5 months, and 70.2% and 41.1 months. The AUC (area under ROC curve) of RRS system was not inferior to that of TNM staging system (0.713 vs. 0.666; P= 0.093). The AUC (0.770) and C-index value (0.721) of RRS-TNM model were significantly better than both RRS and TNM staging system (P< 0.001).

Conclusions: The RRS system accurately identifies CRC patients with high-risk recurrence preoperatively. Constructing a nomogram using the RRS system and TNM staging significantly improves the accuracy of staging and prognosis prediction, which is of great clinical significance for individualized clinical treatment and follow-up of CRC.

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CEA、CA199、PT、FIB、肿瘤分化及TNM分期构成的图在结直肠癌中的临床价值
背景:准确判断结直肠癌(CRC)的肿瘤-淋巴结-转移(tumor - node - metastasis, TNM)分期对判断肿瘤进展及预后、制定治疗策略具有重要的指导意义。目的:建立可切除结直肠癌复发风险评分(RRS)系统及预后预测模型,以提高结直肠癌分期、预后预测及临床决策的准确性。方法:对行根治性手术的结直肠癌患者进行回顾性研究。采用多变量Cox回归模型筛选独立预后因素。RRS系统由独立的预测因素组成,每个因素加1分。采用由RRS和TNM分期系统组成的预后模型(RRS-TNM模型)预测术后复发。结果:TNM分期、肿瘤分化、术前癌胚抗原、碳水化合物抗原199、凝血酶原时间和纤维蛋白原升高是独立的预后生物标志物。540例患者中有173例复发。术后p-TNM I、II、III期的5年累积复发率(5-y CRR)和无病生存期(DFS)分别为12.7%和104.8个月,26.5%和89.3个月,55.5%和57.3个月。术前低危组(RRS 0-1分)、中危组(RRS 2-3分)、高危组(RRS 4-5分)5年CRR和DFS分别为13.9%和101.1个月、40.9%和75.5个月、70.2%和41.1个月。RRS分期的AUC (ROC曲线下面积)不低于TNM分期(0.713 vs. 0.666;P = 0.093)。RRS-TNM模型的AUC(0.770)和c指数值(0.721)均显著优于RRS和TNM分期系统(P< 0.001)。结论:RRS系统可准确识别结直肠癌高危复发患者。利用RRS系统和TNM分期构建nomogram,可显著提高分期和预后预测的准确性,对CRC的个体化临床治疗和随访具有重要的临床意义。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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