目的: 评估炎症相关标志物对输尿管尿路上皮癌患者预后预测的临床价值。方法: 采用分割样本验证将200例输尿管尿路上皮癌患者随机分为建模组和验证组,回顾患者石蜡病理标本,免疫组织化学法检测肿瘤组织浸润中性粒细胞(tumor-infiltrating neutrophil,TIN)(CD66b⁺标记)、肿瘤相关巨噬细胞(tumor-associated macrophage,TAM)(CD163⁺标记)及淋巴细胞(CD⁺、CD4⁺、CD8⁺标记)计数,以及外周血中性粒细胞/淋巴细胞比值(neutrophil/lymphocyte ratio,NLR)、肿瘤组织中性粒细胞/单核细胞比值(neutrophil/monocyte ratio,NMR),按病理分期结果将患者分成非肌层浸润性和肌层浸润性输尿管尿路上皮癌组,分别建立预后预测列线图模型。对模型进行分辨度评价,分别建立仅包含外周血参数和包含全部参数的预后列线图模型,比较两种模型对输尿管尿路上皮癌患者预后判断的准确性。结果: 患者中位随访时间36个月,无进展生存时间40个月,3年内出现肿瘤进展42例(21.0%)。肿瘤大小、病理分期、病理分级等指标均为预测输尿管尿路上皮癌术后3年首次复发的单因素变量,肿瘤大小、病理分期、病理分级、TIN、TAM、NLR、NMR是预测输尿管尿路上皮癌术后3年首次复发的多因素变量。非肌层浸润性输尿管尿路上皮癌104例,术后3年首次复发10例(9.6%),肌层浸润性输尿管尿路上皮癌96例,术后3年首次复发32例(33.3%),两组比较差异有统计学意义(χ²=15.53,P<0.05)。建立两组无进展生存率的预测列线图模型发现,非肌层浸润组和肌层浸润组一致性指数分别为0.722(95%CI:0.70~0.78)和0.725(95%CI:0.71~0.79),与实际观察到的3年生存率一致性较佳。区分度测试结果显示,输尿管尿路上皮癌的全参数预后预测模型一致性指数为0.726,高于输尿管尿路上皮癌的外周血参数预后预测模型(一致性指数0.672),尿路上皮癌肿瘤组织的免疫微环境提高了模型的预测准确性。结论: 以免疫炎症相关标志物为基础的全参数预后预测模型可以作为现有病理分级和分期系统的完善和补充,为输尿管尿路上皮癌患者的精准个体化治疗提供了依据;以外周血标本相关指标为基础的预后预测模型标本易于获取,检测方法简单、经济,更利于临床推广应用。

Objective: To evaluate the clinical value of inflammation-related markers in predicting the prognosis of patients with ureteral urothelial carcinoma. Methods: 200 patients with ureteral urothelial carcinoma were randomly divided into two groups by split sample validation: modeling group and validation group. Paraffin embedded pathological specimens of the patients were reviewed. Immunohistochemical method was used to detect tumor-infiltrating neutrophil (TIN) (CD66b⁺), tumor-associated macrophage (TAM) (CD163⁺), lymphocyte (CD⁺, CD4⁺, CD8⁺) counts, peripheral blood neutrophil / lymphocyte ratio (NLR) and tumor tissue neutrophil/monocyte ratio (NMR). According to the results of pathological staging, the patients were divided into non-muscle-invasive and muscle-invasive ureteral urothelial carcinoma group. The resolution of the models was evaluated, and the prognostic nomogram models including only peripheral blood parameters and all parameters were established to compare the accuracy of the two models in predicting the prognosis of patients with urothelial carcinoma of the ureter. Results: The median follow-up time was 36 months, the progression-free survival was 40 months, and 42 cases (21.0%) showed tumor progression within 3 years. Tumor size, pathological stage and pathological grade were all single-factor variables predicting the first recurrence of ureteral urothelial carcinoma three years after operation. Tumor size, pathological stage, pathological grade, TIN, TAM, NLR and NMR were multi-factor variables predicting the first recurrence three years after operation. Among 104 cases of non-muscle-invasive ureteral urothelial carcinoma, 10 cases (9.6%) recurred for the first time 3 years after operation, 96 cases (33.3%) of muscle invasive ureteral urothelial carcinoma, and the diffe-rence between the two groups was statistically significant (χ²=15.53, P<0.05). The predictive nomogram model of progression free survival was established. The concordance index of progression free survi-val was 0.722 (95%CI: 0.70-0.78) in non-muscle-invasion group, and 0.725 (95%CI: 0.71-0.79) in muscle-invasion group, which was in good agreement with the observed 3-year survival rate. The results of discrimination test showed that the concordance index of the whole parameter prediction model of ureteral urothelial carcinoma was 0.726, which was higher than that of peripheral blood parameters (consistency index 0.672). The immune microenvironment of ureteral urothelial carcinoma improved the prediction accuracy of the model. Conclusion: The prognosis prediction model based on immune inflammation-related markers was established as a perfection and supplement for the existing pathological grading and staging system, providing a basis for accurate individualized treatment of patients with urete-ral urothelial carcinoma. The prognosis prediction model based on the relevant indicators of peripheral blood samples is established, which is easy to obtain specimens, and the detection method is simple and economical, which is more conducive to clinical application.