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中华腔镜泌尿外科杂志(电子版) ›› 2025, Vol. 19 ›› Issue (03) : 323 -328. doi: 10.3877/cma.j.issn.1674-3253.2025.03.007

临床研究

术前炎性指标对肾透明细胞癌WHO/ISUP病理分级的预测价值
张志昱1, 张凡2, 周奇3, 欧阳骏1, 林宇鑫1, 张学锋1,()   
  1. 1. 215000 江苏,苏州大学附属第一医院泌尿外科
    2. 215000 江苏,苏州大学附属第一医院肾内科
    3. 215000 江苏,苏州大学附属第一医院生殖医学中心
  • 收稿日期:2024-01-17 出版日期:2025-06-01
  • 通信作者: 张学锋
  • 基金资助:
    国家自然科学基金(32200533)

The predictive value of preoperative inflammatory indicators for the WHO/ISUP pathological grading of clear cell renal cell carcinoma

Zhiyu Zhang1, Fan Zhang2, Qi Zhou3, Jun Ouyang1, Yuxin Lin1, Xuefeng Zhang1,()   

  1. 1. Department of Urology,The First Affiliated Hospital of Soochow University,Suzhou 215000,China
    2. Department of Nephrology,The First Affiliated Hospital of Soochow University,Suzhou 215000,China
    3. Department of Reproductive Medicine Center,The First Affiliated Hospital of Soochow University,Suzhou 215000,China
  • Received:2024-01-17 Published:2025-06-01
  • Corresponding author: Xuefeng Zhang
引用本文:

张志昱, 张凡, 周奇, 欧阳骏, 林宇鑫, 张学锋. 术前炎性指标对肾透明细胞癌WHO/ISUP病理分级的预测价值[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2025, 19(03): 323-328.

Zhiyu Zhang, Fan Zhang, Qi Zhou, Jun Ouyang, Yuxin Lin, Xuefeng Zhang. The predictive value of preoperative inflammatory indicators for the WHO/ISUP pathological grading of clear cell renal cell carcinoma[J/OL]. Chinese Journal of Endourology(Electronic Edition), 2025, 19(03): 323-328.

目的

研究术前炎性指标与肾透明细胞癌世界卫生组织/国际泌尿病理学会(WHO/ISUP)病理分级的关系,并构建预测模型。

方法

回顾性分析2018 年1 月至2019 年12 月于苏州大学附属第一医院泌尿外科行手术治疗的肾透明细胞癌患者资料。根据WHO/ISUP 病理分级系统将153 例入组患者分为低级别组(Ⅰ、Ⅱ级)与高级别组(Ⅲ、Ⅳ级),比较两组间临床病理参数的差异。通过Logistic 多因素分析寻找预测病理分级的独立危险因素,绘制列线图构建预测模型,利用calibration 校准曲线评估模型拟合度。最后使用受试者工作特征(ROC)曲线检验模型诊断效能,借助决策曲线(DCA)评估模型净收益情况。

结果

低级别和高级别组间在肿瘤直径、中性粒淋巴细胞比(NLR)、血小板淋巴细胞比(PLR)、淋巴单核细胞比(LMR)、系统免疫炎症指数(SII)等方面差异有统计学意义(P<0.05)。对有差异影响因素进行Logistic 多因素分析,发现肿瘤直径(OR=1.026,95%CI:1.003~1.050)、NLR(OR=3.725,95%CI:1.818~7.630)及PLR(OR=1.021,95%CI:1.008~1.035)为预测肾透明细胞癌病理高分级的独立危险因素(P<0.05)。依据Logistic 多因素模型构建诺莫图预测模型及calibration 校准曲线,其模型拟合度较好(χ2=12.853,P=0.117)。ROC 曲线结果表明,预测模型AUC 最高(0.809),显著高于单肿瘤直径、NLR 或PLR 诊断效能(P<0.05)。DCA 图显示,预测模型的临床净获益高于其他指标。

结论

肿瘤直径、NLR 及PLR 与肾透明细胞癌WHO/ISUP 病理分级有关,且由此构建的预测模型有较强的诊断效能。

Objective

To investigate the relationship between preoperative inflammatory indicators and the WHO/ISUP pathological grading of clear cell renal cell carcinoma, and to construct a predictive model.

Methods

The data of clear cell renal cell carcinoma patients who underwent surgical treatment in the Urology Department of the First Affiliated Hospital of Soochow University from January 2018 to December 2019 were analyzed retrospectively.According to the WHO/ISUP pathological grading system, 153 patients were divided into a low-grade group (grade I, II) and a high-grade group (grade III,IV), and the differences in clinical and pathological parameters between the two groups were compared.Multivariate logistic analyses were used to identify independent risk factors for predicting pathological grading, and a nomogram predictive model was constructed and evaluated using a calibration curve.Lastly,the diagnostic efficacy of the model was tested using receiver operating characteristic (ROC) curves and decision curve analysis (DCA) was used to evaluate the net benefits of the model.

Results

There were significant differences between the low-grade and high-grade groups in tumor diameter, neutrophil-tolymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune inflammation index (SII) (P<0.05).Multivariate logistic analyses revealed that tumor diameter (OR=1.026, 95%CI: 1.003-1.050), NLR (OR=3.725, 95%CI: 1.818-7.630), and PLR (OR=1.021,95%CI: 1.008-1.035) were independent risk factors for predicting the pathological high grading of clear cell renal cell carcinoma (P<0.05).A predictive model was constructed using the multivariate logistic model and the calibration curve, which demonstrated good predictive accuracy (χ2=12.853, P=0.117).The ROC curve results suggested that the predictive model had the highest area under the curve (AUC)value (0.809), which was significantly higher than that of the single diagnostic parameters including tumor diameter, NLR, and PLR (P<0.05).The DCA presented higher clinical net benefits for the predictive model as compared to other indicators.

Conclusions

The tumor diameter, NLR, and PLR are related to the WHO/ISUP pathological grading of clear cell renal cell carcinoma, and the constructed predictive model has strong diagnostic efficacy.

表1 肾透明细胞癌患者术后WHO/ISUP 病理分级低级别组与高级别组临床病理特征比较
表2 肾透明细胞癌患者术后WHO/ISUP 分级系统病理级别高低预测因素的多因素Logistic 回归分析
图1 肾透明细胞癌患者术后WHO/ISUP 分级系统病理级别高低预测的列线图 图2 Calibration校准曲线
图3 列线图预测模型与各单个独立危险因素指标预测WHO/ISUP 分级系统高级别肿瘤的ROC 曲线 图4 决策曲线分析 注:NLR 为中性粒淋巴细胞比,PLR 为血小板淋巴细胞比
表3 列线图预测模型与单个独立危险因素诊断价值比较
[1]
Lane BR, Tiong HY, Campbell SC, et al.Management of the adrenal gland during partial nephrectomy[J].J Urol, 2009, 181(6): 2430-2437.DOI: 10.1016/j.juro.2009.02.027.
[2]
Syafruddin SE, Rodrigues P, Vojtasova E, et al.A KLF6-driven transcriptional network links lipid homeostasis and tumour growth in renal carcinoma[J].Nat Commun, 2019, 10(1): 1152.DOI: 10.1038/s41467-019-09116-x.
[3]
Campbell S, Uzzo RG, Allaf ME, et al.Renal mass and localized renal cancer: AUA guideline[J].J Urol, 2017, 198(3): 520-529.DOI:10.1016/j.juro.2017.04.100.
[4]
Zhang Z, Zhou Q, Ouyang J, et al.Expression and clinical significance of interleukin-9 in renal tumors[J].Transl Androl Urol,2020, 9(6): 2657-2664.DOI: 10.21037/tau-20-761.
[5]
Yu Z, Lv Y, Su C, et al.Integrative single-cell analysis reveals transcriptional and epigenetic regulatory features of clear cell renal cell carcinoma[J].Cancer Res, 2023, 83(5): 700-719.DOI:10.1158/0008-5472.CAN-22-2224.
[6]
李国良, 吴凡, 李浩民, 等.抽栓技术在完全腹腔镜左肾癌合并Ⅳ级腔静脉癌栓取出术的应用[J/OL].中华腔镜泌尿外科杂志(电子版), 2023, 17(4): 403-406.DOI: 10.3877/cma.j.issn.1674-3253.2023.04.018.Li GL, Wu F, Li HM, et al.Application of thrombus aspiration in total laparoscopic thrombectomy in treatment of left renal cell carcinoma with level Ⅳ inferior vena Cava thrombus[J/OL].Chin J Endourol Electron Ed, 2023, 17(4): 403-406.DOI: 10.3877/cma.j.issn.1674-3253.2023.04.018.
[7]
Delahunt B, Eble JN, Egevad L, et al.Grading of renal cell carcinoma[J].Histopathology, 2019, 74(1): 4-17.DOI: 10.1111/his.13735.
[8]
Delahunt B, Sika-Paotonu D, Bethwaite PB, et al.Grading of clear cell renal cell carcinoma should be based on nucleolar prominence[J].Am J Surg Pathol, 2011, 35(8): 1134-1139.DOI: 10.1097/PAS.0b013e318220697f.
[9]
张志昱, 宋振, 周奇, 等.术前炎性指标对PSA 灰区且PIRADS 评分3 分患者患临床有意义前列腺癌的预测价值[J].大连医科大学学报, 2023, 45(3): 198-203, 209.DOI: 10.11724/jdmu.2023.03.02.Zhang ZY, Song Z, Zhou Q, et al.Efficacy of preoperative inflammatory markers in predicting clinically significant prostate cancer in patients with gray zone PSA levels and PI-RADS 3 lesions and a novel model construction[J].J Dalian Med Univ, 2023, 45(3):198-203, 209.DOI: 10.11724/jdmu.2023.03.02.
[10]
Ding L, Deng X, Wang K, et al.Preoperative systemic inflammatory markers as a significant prognostic factor after TURBT in patients with non-muscle-invasive bladder cancer[J].J Inflamm Res, 2023,16: 283-296.DOI: 10.2147/JIR.S393511.
[11]
Gaitanidis A, Wiseman D, El Lakis M, et al.Preoperative systemic inflammatory markers are prognostic indicators in recurrent adrenocortical carcinoma[J].J Surg Oncol, 2019, 120(8): 1450-1455.DOI: 10.1002/jso.25760.
[12]
Wang J, Ye J, Zhao X, et al.Prognostic value and model construction of preoperative inflammatory markers in patients with metastatic renal cell carcinoma[J].World J Surg Oncol, 2023, 21(1): 211.DOI:10.1186/s12957-023-03110-w.
[13]
Zapała Ł, Ślusarczyk A, Garbas K, et al.Complete blood countderived inflammatory markers and survival in patients with localized renal cell cancer treated with partial or radical nephrectomy: a retrospective single-tertiary-center study[J].Front Biosci (Schol Ed),2022, 14(1): 5.DOI: 10.31083/j.fbs1401005.
[14]
段刘剑, 章顺, 张林, 等.外周血免疫指标对肾癌术前诊断与分期的临床意义[J].临床泌尿外科杂志, 2023, 38(2): 120-123, 127.DOI: 10.13201/j.issn.1001-1420.2023.02.008.Duan LJ, Zhang S, Zhang L, et al.Clinical significance of peripheral blood immune indexes in guiding renal cell carcinoma diagnosis and staging[J].J Clin Urol, 2023, 38(2): 120-123, 127.DOI: 10.13201/j.issn.1001-1420.2023.02.008.
[15]
陈怀安, 刘硕, 李秀君, 等.炎症生物标志物对输尿管尿路上皮癌患者预后预测的临床价值[J].北京大学学报(医学版), 2021,53(2): 302-307.DOI: 10.19723/j.issn.1671-167X.2021.02.012.Chen HA, Liu S, Li XJ, et al.Clinical value of inflammatory biomarkers in predicting prognosis of patients with ureteral urothelial carcinoma[J].J Peking Univ Health Sci, 2021, 53(2): 302-307.DOI:10.19723/j.issn.1671-167X.2021.02.012.
[16]
Salazar-Valdivia FE, Valdez-Cornejo VA, Ulloque-Badaracco JR, et al.Systemic immune-inflammation index and mortality in testicular cancer: a systematic review and meta-analysis[J].Diagnostics (Basel),2023, 13(5): 843.DOI: 10.3390/diagnostics13050843.
[17]
Hu C, Bai Y, Li J, et al.Prognostic value of systemic inflammatory factors NLR, LMR, PLR and LDH in penile cancer[J].BMC Urol,2020, 20(1): 57.DOI: 10.1186/s12894-020-00628-z.
[18]
Liu Y, Li X, Zhang C, et al.LINC00973 is involved in cancer immune suppression through positive regulation of Siglec-15 in clear-cell renal cell carcinoma[J].Cancer Sci, 2020, 111(10): 3693-3704.DOI: 10.1111/cas.14611.
[19]
赵盼盼, 康旭, 杨浩.肾透明细胞癌患者CT 表现与Fuhrman核分级的相关性[J].海南医学, 2023, 34(12): 1766-1769.DOI:10.3969/j.issn.1003-6350.2023.12.022.Zhao PP, Kang X, Yang H.Correlation between CT findings and Fuhrman nuclear grade in patients with clear cell renal cell carcinoma[J].Hainan Med J, 2023, 34(12): 1766-1769.DOI:10.3969/j.issn.1003-6350.2023.12.022.
[20]
Nikolaou VS, Malahias MA, Kaseta MK, et al.Comparative clinical study of ultrasound-guided A1 pulley release vs open surgical intervention in the treatment of trigger finger[J].World J Orthop,2017, 8(2): 163-169.DOI: 10.5312/wjo.v8.i2.163.
[21]
潘正波, 程伟松, 蔡海荣, 等.术前系统免疫炎症指数与高危/极高危前列腺癌根治术后患者预后的相关性研究[J].中国现代医师, 2020, 58(13): 49-52, 56.Pan ZB, Cheng WS, Cai HR, et al.Correlation between preoperative systemic immune inflammation index and prognosis of high-risk/very high-risk prostate cancer patients after radical operation[J].China Mod Dr, 2020, 58(13): 49-52, 56.
[22]
董超男, 翟文萍, 王雪野.血小板介导肿瘤细胞生长和转移的机制研究进展[J].医学综述, 2020, 26(4): 695-699.DOI: 10.3969/j.issn.1006-2084.2020.04.014.Dong CN, Zhai WP, Wang XY.Research progress in mechanism of platelet-mediated tumor cell growth and metastasis[J].Med Recapitul,2020, 26(4): 695-699.DOI: 10.3969/j.issn.1006-2084.2020.04.014.
[23]
徐明彬, 赵雨桐, 黎承杨, 等.术前外周血淋巴细胞与单核细胞比值和白蛋白在肾透明细胞癌预后评估中的价值[J].中国癌症杂志, 2019, 29(11): 887-898.DOI: 10.19401/j.cnki.1007-3639.2019.11.008.Xu MB, Zhao YT, Li CY, et al.Predictive value of lymphocyteto-monocyte ratio and serum albumin in patients with clear cell renal cell carcinoma[J].China Oncol, 2019, 29(11): 887-898.DOI:10.19401/j.cnki.1007-3639.2019.11.008.
[24]
牛路, 薛博, 高哈尔·卡德尔汉, 等.基于外周血细胞的肾癌患者术后预后风险评估与精准化预测[J].现代泌尿生殖肿瘤杂志,2023, 15(2): 69-74, 83.DOI: 10.3870/j.issn.1674-4624.2023.02.002.Niu L, Xue B, Gaohaer·Kadeerhan, et al.Risk assessment and precision prediction of postoperative prognosis in patients with renal cell carcinoma based on peripheral blood cells[J].J Contemp Urol Reprod Oncol, 2023, 15(2): 69-74, 83.DOI: 10.3870/j.issn.1674-4624.2023.02.002.
[25]
Bulut N, Unsal A, Erdem GU, et al.Diagnostic value of the preoperative platelet/lymphocyte ratio and red cell distribution volume in patients with renal masses[J].Bratisl Lek Listy, 2023,124(9): 685-689.DOI: 10.4149/BLL_2023_105.
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