基于血常规炎症指标与临床病理特征的结直肠癌术后淋巴结转移风险列线图模型构建

Development of a nomogram for predicting postoperative lymph node metastasis in colorectal cancer based on inflammatory markers and clinicopathologic features

摘要:

背景与目的 结直肠癌（CRC）术后淋巴结转移是影响患者预后的关键因素。传统评估方法依赖病理学检查，缺乏便捷的术前预测手段。血常规衍生炎症指标如中性粒细胞-淋巴细胞比值（NLR）和血小板-淋巴细胞比值（PLR）在肿瘤进展中具有潜在价值。本研究旨在分析CRC患者术后淋巴结转移的相关危险因素，并构建结合血常规指标的预测模型。方法 回顾性纳入2020年1月—2023年12月接受根治性手术的125例CRC患者，随访1年，根据术后是否发生淋巴结转移分为转移组（n=31）和未转移组（n=94）。收集临床病理资料及术前血常规指标。采用单因素分析筛选相关变量，进一步进行多因素Logistic回归分析确定独立危险因素，并构建列线图模型。通过一致性指数、校准曲线及受试者工作特征（ROC）曲线评估模型性能。结果 单因素分析显示，肿瘤直径≥3 cm、低分化、浸润深度（黏膜下层）、脉管侵犯以及中性粒细胞计数（NE）、单核细胞计数（MN）、血小板计数（PLT）、PLR、NLR升高和淋巴细胞计数（LYM）降低与术后淋巴结转移明显有关（均P<0.05）。多因素分析表明，低分化（OR=2.044）、浸润深度（黏膜下层）（OR=2.643）、脉管侵犯（OR=2.542）、PLR升高（OR=3.022）及NLR升高（OR=2.380）为独立危险因素（均P<0.05）。基于上述变量构建的列线图模型一致性指数为0.881（95% CI=0.828~0.934），校准曲线显示预测结果与实际观察值一致性良好。ROC分析显示模型曲线下面积为0.874（95% CI=0.821~0.927），敏感度为91.66%，特异度为68.05%。结论 基于病理特征及血常规炎症指标构建的列线图模型对CRC患者术后淋巴结转移具有较高预测效能，可为临床个体化风险评估和辅助治疗决策提供参考。

Abstract:

Background and Aims Postoperative lymph node metastasis is a major determinant of prognosis in colorectal cancer (CRC). However, reliable and convenient preoperative predictive tools remain limited. Inflammatory markers derived from routine blood tests, such as neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), have shown potential prognostic value. This study aimed to identify risk factors and develop a predictive model for postoperative lymph node metastasis in CRC patients.Methods A total of 125 CRC patients who underwent radical surgery between January 2020 and December 2023 were retrospectively enrolled and followed for one year. Patients were divided into metastasis (n=31) and non-metastasis groups (n=94). Clinicopathologic features and preoperative blood parameters were collected. Univariate analysis and multivariate logistic regression were performed to identify independent risk factors. A nomogram model was constructed and evaluated using the concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) curve.Results Univariate analysis showed that tumor size ≥3 cm, poor differentiation, submucosal invasion, vascular invasion, elevated neutrophil count, monocyte count, platelet count, PLR, NLR, and decreased lymphocyte count were significantly associated with lymph node metastasis (all P<0.05). Multivariate analysis identified poor differentiation (OR=2.044), submucosal invasion (OR=2.643), vascular invasion (OR=2.542), high PLR (OR=3.022), and high NLR (OR=2.380) as independent risk factors (all P<0.05). The nomogram achieved a C-index of 0.881 (95% CI=0.828-0.934), with good calibration. The AUC was 0.874 (95% CI=0.821-0.927), with a sensitivity of 91.66% and specificity of 68.05%.Conclusion The nomogram integrating pathological features and blood-derived inflammatory markers demonstrates good predictive performance for postoperative lymph node metastasis in CRC patients and may assist in individualized clinical decision-making.