To explore the risk factors of lymphovascular invasion in patients with upper tract urothelial carcinoma and construct a prediction model.

IF 3.5 3区 医学 Q2 ONCOLOGY
Frontiers in Oncology Pub Date : 2025-03-25 eCollection Date: 2025-01-01 DOI:10.3389/fonc.2025.1568774
Qinghui Li, Pengtao Wei, Yanjie Kang, Xiaohui Li, Han Zhang, Jinhui Yang, Jiantao Sun
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Abstract

Background and objective: To explore the risk factors and construct a prediction model of the lymphovascular invasion (LVI) in patients with upper tract urothelial carcinoma (UTUC).

Methods: Clinical data of 143 UTUC patients treated in our hospital during Jan. 2010 and Dec. 2022 were retrospectively analyzed. The patients were divided into LVI positive group and LVI negative group according to the postoperative lymphovascular conditions. Kaplan-Meier method was used to evaluate the overall survival (OS) and cancer-specific survival (CSS) of the two groups, and the survival curve was drawn. The correlation between LVI and inclusion indexes was analyzed using univariate and ultivariate. A prediction model was established and receiver operating characteristic (ROC) curve was drawn to analyze the diagnostic value.

Results: The median survival time of LVI positive patients was 78 months (95%CI 44.47-111.53), lower than the 90months (95%CI 72.77-107.23) for LVI negative patients, and the 5-year OS of LVI positive patients was 53.0%, lower than that of LVI negative patients (79.6%). The difference was statistically significant (P=0.005). The 5-year CSS of LVI positive patients was 57.0%, lower than that of LVI negative patients (85.7%, P=0.009). The results of univariate analysis showed that there were statistically significant differences between the two groups (P < 0.05) in exfoliation cytology (P=0.044), hydronephrosis (P=0.015), preoperative fibrinogen level (P=0.003), lymph node status (P=0.014), pathological stage (P=0.001) and grade (P=0.047). Multivariate Logistic regression analysis showed that hydronephrosis (P=0.022), pathological stage (P < 0.001), lymph node status (P=0.025) and fibrinogen level (P=0.019) were independent factors influencing the occurrence of lymphovascular invasion, and the combination of four indexes above was better than any single index. the ROC curve showed that the area under the curve (AUC) of postoperative LVI was the largest when combined with the four predictors, and the AUC was 0.833 (95%CI 0.759-0.907). When the Youden index was 0.594, the sensitivity was 81.1%, and the specificity was 78.3%.

Conclusion: Lymphovascular invasion is related to hydronephrosis, pathological stage, lymph node condition and fibrinogen level. Patients with preoperative hydronephrosis, high pathological stage, lymph node metastasis and high fibrinogen level were at higher risk of lymphovascular invasion.

探讨上尿路上皮癌患者淋巴血管侵犯的危险因素,并建立预测模型。
背景与目的:探讨上尿路上皮癌(UTUC)患者淋巴血管侵犯(LVI)的危险因素,建立预测模型。方法:回顾性分析我院2010年1月至2022年12月收治的143例UTUC患者的临床资料。根据术后淋巴血管情况将患者分为LVI阳性组和LVI阴性组。采用Kaplan-Meier法评价两组患者的总生存期(OS)和肿瘤特异性生存期(CSS),并绘制生存曲线。采用单因素和多因素分析LVI与纳入指标的相关性。建立预测模型,绘制受试者工作特征(ROC)曲线,分析其诊断价值。结果:LVI阳性患者的中位生存时间为78个月(95%CI 44.47 ~ 111.53),低于LVI阴性患者的90个月(95%CI 72.77 ~ 107.23); LVI阳性患者的5年OS为53.0%,低于LVI阴性患者的79.6%。差异有统计学意义(P=0.005)。LVI阳性患者5年CSS为57.0%,低于LVI阴性患者(85.7%,P=0.009)。单因素分析结果显示,两组患者在剥脱细胞学(P=0.044)、肾积水(P=0.015)、术前纤维蛋白原水平(P=0.003)、淋巴结状态(P=0.014)、病理分期(P=0.001)、分级(P=0.047)方面差异均有统计学意义(P < 0.05)。多因素Logistic回归分析显示,肾积水(P=0.022)、病理分期(P < 0.001)、淋巴结状态(P=0.025)、纤维蛋白原水平(P=0.019)是影响淋巴血管浸润发生的独立因素,且以上4项指标联合使用优于单一指标。ROC曲线显示,4种预测因子联合应用时,术后LVI的曲线下面积(AUC)最大,AUC为0.833 (95%CI 0.759 ~ 0.907)。约登指数为0.594时,敏感性为81.1%,特异性为78.3%。结论:淋巴血管浸润与肾积水、病理分期、淋巴结状况及纤维蛋白原水平有关。术前肾积水、病理分期高、淋巴结转移及纤维蛋白原水平高的患者有较高的淋巴血管浸润风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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