谷歌浏览器插件
订阅小程序
在清言上使用

Tumor Margin Irregularity Degree is an Important Preoperative Predictor of Adverse Pathology for Clinical T1/2 Renal Cell Carcinoma and the Construction of Predictive Model.

World journal of urology(2024)

引用 0|浏览13
暂无评分
摘要
PURPOSE:To explore the critical role of the tumor margin irregularity degree (TMID) of renal tumors in predicting adverse pathology of patients with clinical T1/2 (cT1/2) renal cell carcinoma (RCC).METHODS:A total of 821 patients with cT1/2 RCC undergoing nephrectomy in the Second Hospital of Tianjin Medical University between January 2017 and December 2020 were reviewed. The tumor margin irregularity (TMI) was classified into renal mass with locally raised protrusion and smooth margin called 'lobular', sharply and unsmooth nodular margin called 'spiculation', blurred margins between tumor and renal parenchyma or a completely irregular and non-elliptical shape. The ratio between the number of irregular cross-sections (X) and the number of total cross-sections from top to bottom occupied (Y) was defined as TMID (X/Y). The logistic regression was performed to determine the independent predictors of adverse pathology, and the Kaplan-Meier curve and log-rank test were used to analyze the survival outcomes.RESULTS:Among 821 cT1/2 RCC patients, 245 (29.8%) had adverse pathology. The results of the univariate and multivariate logistic regressions showed that the age, tumor size, hemoglobin, and TMID were the independent predictors of adverse pathology. Incorporation of TMID could increase the discrimination of the predictive model with the area under curve (AUC) of ROC curves increasing from 0.725 to 0.808. Patients with adverse pathology or higher TMID both had significantly shorter recurrence-free survival (RFS).CONCLUSION:The nomogram model incorporated with TMID for predicting adverse pathology could increase its discrimination, calibration, and clinical application values, compared with the models without TMID.
更多
查看译文
关键词
Renal cell carcinoma,Adverse pathology,Predictor,Nomogram,Prognosis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要