Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
The First Clinical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
BMC Cancer. 2024 Aug 22;24(1):1035. doi: 10.1186/s12885-024-12806-5.
Inflammatory factors play an important role in the onset and progression of colorectal cancer (CRC). This study aimed to develop and validate a novel scoring system that utilizes specific inflammatory factor indicators to predict intestinal obstruction in CRC patients.
This study conducted a retrospective analysis of 1,470 CRC patients who underwent surgical resection between January 2013 and July 2018. These patients were randomly allocated to the training group (n = 1060) and the validation group (n = 410). Univariate and multivariate logistic regression analyses were performed to identify independent predictive factors for intestinal obstruction. The CRC peculiar inflammation score (CPIS), comprising lymphocyte-to-monocyte ratio (LMR), prognostic nutrition index (PNI), and alanine transaminase-to-lymphocyte ratio index (ALRI) scores, was significantly associated with the occurrence of intestinal obstruction. A nomogram combining CPIS with other clinical features was developed to predict this occurrence. Model accuracy was assessed by determining the area under the receiver operating characteristic (ROC) curve (AUC).
The CPIS generated by multi-factor logistic regression was as follows: - 1.576 × LMR - 0.067 × PNI + 0.018 × ALRI. Using CPIS cutoff values of 50% (- 7.188) and 85% (- 6.144), three predictive groups were established. Patients with a high CPIS had a significantly higher risk of intestinal obstruction than those with a low CPIS (odds ratio [OR]: 10.0, confidence interval [CI]: 5.85-17.08, P < 0.001). The predictive nomogram demonstrated good calibration and discrimination abilities. The AUC of the ROC curve for the obstruction nomogram was 0.813 (95% CI: 0.777-0.850) in the training set and 0.806 (95% CI: 0.752-0.860) in the validation set. The calibration curve exhibited neither bias nor high credibility. Decision curve analysis indicated the utility of this predictive model.
CRC-associated intestinal obstruction is closely linked to inflammatory markers in patients. CPIS is a CRC-specific inflammatory predictive score based on a combination of inflammatory-related indicators. A high CPIS serves as a strong indicator of intestinal obstruction. Its integration with other clinical factors and preoperative inflammatory-specific indicators significantly enhances the diagnosis and treatment of CRC patients with intestinal obstruction.
炎症因子在结直肠癌(CRC)的发病和进展中起重要作用。本研究旨在开发和验证一种新的评分系统,该系统利用特定的炎症因子指标预测 CRC 患者的肠梗阻。
本研究回顾性分析了 2013 年 1 月至 2018 年 7 月间接受手术切除的 1470 例 CRC 患者。这些患者被随机分配到训练组(n=1060)和验证组(n=410)。采用单因素和多因素 logistic 回归分析确定与肠梗阻发生相关的独立预测因素。CRC 特有炎症评分(CPIS)由淋巴细胞与单核细胞比值(LMR)、预后营养指数(PNI)和丙氨酸转氨酶与淋巴细胞比值指数(ALRI)评分组成,与肠梗阻的发生显著相关。建立了一个结合 CPIS 与其他临床特征的列线图来预测这种发生。通过确定接收者操作特征(ROC)曲线下面积(AUC)来评估模型准确性。
多因素 logistic 回归生成的 CPIS 如下:-1.576×LMR-0.067×PNI+0.018×ALRI。使用 CPIS 截断值 50%(-7.188)和 85%(-6.144),建立了三个预测组。CPIS 高的患者发生肠梗阻的风险明显高于 CPIS 低的患者(优势比[OR]:10.0,95%置信区间[CI]:5.85-17.08,P<0.001)。梗阻列线图的 ROC 曲线 AUC 在训练集为 0.813(95%CI:0.777-0.850),在验证集为 0.806(95%CI:0.752-0.860)。校准曲线既没有偏差也没有高可信度。决策曲线分析表明该预测模型的实用性。
CRC 相关的肠梗阻与患者的炎症标志物密切相关。CPIS 是一种基于炎症相关指标组合的 CRC 特异性炎症预测评分。高 CPIS 是肠梗阻的强烈指标。它与其他临床因素和术前炎症特异性指标的结合,显著提高了 CRC 合并肠梗阻患者的诊断和治疗效果。