基于增强CT的细胞外容积分数预测肾透明细胞癌术后复发转移的价值

The Value of Predicting Postoperative Recurrence and Metastasis of Clear Cell Renal Cell Carcinoma by Extracellular Volume Fraction Based on Enhanced CT

目的 探讨基于增强CT的细胞外容积分数(ECV)术前无创评估肾透明细胞癌(ccRCC)复发转移的价值。方法 回顾性分析169例病理证实为ccRCC患者,搜集患者的年龄、性别、最大瘤径、手术方式、病理分级、肿瘤分期、系统性免疫炎症指数(SII)及术前ECV等资料,根据有无复发转移分为复发转移组(n=33)和无复发转移组(n=136),采用独立样本t检验、Mann-Whitney U检验、Fisher精确检验及卡方检验对两组资料进行单因素分析,纳入单因素分析有意义的指标进行多因素Logistic回归确定ccRCC术后复发转移的独立危险因素,基于独立危险因素制作列线图。结果 单因素分析结果显示,ECV、SII、最大瘤径、病理分级、肿瘤分期是ccRCC术后复发转移的影响因素(P<0.05),多因素Logistic回归分析显示,ECV、SII、病理分级、肿瘤分期是ccRCC患者复发转移的独立危险因素(P<0.05)。受试者工作特征曲线显示,基于增强CT的ECV预测ccRCC术后复发转移的的曲线下面积为0.812。联合独立危险因素构建的列线图预测模型,曲线下面积为0.909。结论 基于增强CT的ECV、SII、肿瘤分期、病理分级能够较好地预测ccRCC术后的复发转移风险;基于ECV及临床预后因素构建的列线图预测模型效能更佳,有助于临床制定个体化治疗方案。

Objective This study aims to evaluate the value of preoperative non-invasive assessment of extracellular volume fraction(ECV)using enhanced CT in predicting the recurrence and metastasis of clear cell renal cell carcinoma(ccRCC).Methods A retrospective analysis was performed on 169 patients with pathologically confirmed ccRCC.Collected data included age,gender,maximum tumor diameter,surgical method,pathological grade,tumor stage,systemic immune-inflammation index(SII),and preoperative ECV.Based on their outcomes,patients were divided into a recurrence/metastasis group(n=33)and a non-recurrence/metastasis group(n=136).Univariate analyses were conducted using independent sample t-tests,Mann-Whitney U tests,Fisher's exact tests,and chi-square tests.Multivariate Logistic regression was used to identify independent risk factors for postoperative recurrence and metastasis,and a nomogram was developed based on these factors.Results Univariate analysis revealed that ECV,SII,maximum tumor diameter,pathological grade,and tumor stage significantly influenced postoperative recurrence and metastasis of ccRCC(P<0.05).Multivariate logistic regression analysis identified ECV,SII,pathological grade,and tumor stage as independent risk factors for recurrence and metastasis in ccRCC patients(P<0.05).The receiver operating characteristic(ROC)curve demonstrated that the area under the curve(AUC)for predicting postoperative recurrence and metastasis of ccRCC using ECV derived from enhanced CT was 0.812.The nomogram predictive model constructed from these independent risk factors achieved an AUC value of 0.909.Conclusion ECV,SII,tumor stage,and pathological grade derived from enhanced CT can effectively predict the risk of postoperative recurrence and metastasis in ccRCC patients.The nomogram predictive model based on ECV and clinical factors demonstrates superior performance and can aid in developing individualized treatment plans.