Shao-Hao Chen1, Long-Yao Xu1, Yu-Peng Wu1, Zhi-Bin Ke1, Peng Huang1, Fei Lin1, Xiao-Dong Li1, Xue-Yi Xue1, Yong Wei1, Qing-Shui Zheng2, Ning Xu3. 1. Department of Urology, the First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, China. 2. Department of Urology, the First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, China. zhengqingshui@fjmu.edu.cn. 3. Department of Urology, the First Affiliated Hospital of Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, China. drxun@fjmu.edu.cn.
Abstract
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most frequent malignancies; however, the present prognostic factors was deficient. This study aims to explore whether there is a relationship between tumor volume (TV) and oncological outcomes for localized ccRCC. METHODS: Seven hundred forty-nine localized ccRCC patients underwent surgery in our hospital. TV was outlined and calculated using a three-dimensional conformal radiotherapy planning system. We used receiver operating characteristic (ROC) curves to identified optimal cut-off value. Univariable and multivariable Cox regression models were performed to explore the association between TV and oncological outcomes. Kaplan-Meier method and log-rank test were used to estimate survival probabilities and determine the significance, respectively. Time-dependent ROC curve was utilized to assess the prognostic effect. RESULTS: Log rank test showed that higher Fuhrman grade, advanced pT classification and higher TV were associated with shortened OS, cancer-specific survival (CSS), freedom from metastasis (FFM) and freedom from local recurrence (FFLR). multivariable analysis showed higher Fuhrman grade and higher TV were predictors of adverse OS and CSS. The AUC of TV for FFLR was 0.822. The AUC of TV (0.864) for FFM was higher than that of pT classification (0.818) and Fuhrman grade (0.803). For OS and CSS, the AUC of TV was higher than that of Fuhrman grade (0.832 vs. 0.799; 0.829 vs 0.790). CONCLUSIONS: High TV was an independent predictor of poor CSS, OS, FFLR and FFM of localized ccRCC. Compared with pT classification and Fuhrman grade, TV could be a new and better prognostic factor of oncological outcome of localized ccRCC, which might contribute to tailored follow-up or management strategies.
BACKGROUND:Clear cell renal cell carcinoma (ccRCC) is one of the most frequent malignancies; however, the present prognostic factors was deficient. This study aims to explore whether there is a relationship between tumor volume (TV) and oncological outcomes for localized ccRCC. METHODS: Seven hundred forty-nine localized ccRCC patients underwent surgery in our hospital. TV was outlined and calculated using a three-dimensional conformal radiotherapy planning system. We used receiver operating characteristic (ROC) curves to identified optimal cut-off value. Univariable and multivariable Cox regression models were performed to explore the association between TV and oncological outcomes. Kaplan-Meier method and log-rank test were used to estimate survival probabilities and determine the significance, respectively. Time-dependent ROC curve was utilized to assess the prognostic effect. RESULTS: Log rank test showed that higher Fuhrman grade, advanced pT classification and higher TV were associated with shortened OS, cancer-specific survival (CSS), freedom from metastasis (FFM) and freedom from local recurrence (FFLR). multivariable analysis showed higher Fuhrman grade and higher TV were predictors of adverse OS and CSS. The AUC of TV for FFLR was 0.822. The AUC of TV (0.864) for FFM was higher than that of pT classification (0.818) and Fuhrman grade (0.803). For OS and CSS, the AUC of TV was higher than that of Fuhrman grade (0.832 vs. 0.799; 0.829 vs 0.790). CONCLUSIONS: High TV was an independent predictor of poor CSS, OS, FFLR and FFM of localized ccRCC. Compared with pT classification and Fuhrman grade, TV could be a new and better prognostic factor of oncological outcome of localized ccRCC, which might contribute to tailored follow-up or management strategies.
Authors: Al B Benson; Michael I D'Angelica; Daniel E Abbott; Thomas A Abrams; Steven R Alberts; Daniel Anaya Saenz; Chandrakanth Are; Daniel B Brown; Daniel T Chang; Anne M Covey; William Hawkins; Renuka Iyer; Rojymon Jacob; Andrea Karachristos; R Kate Kelley; Robin Kim; Manisha Palta; James O Park; Vaibhav Sahai; Tracey Schefter; Carl Schmidt; Jason K Sicklick; Gagandeep Singh; Davendra Sohal; Stacey Stein; G Gary Tian; Jean-Nicolas Vauthey; Alan P Venook; Andrew X Zhu; Karin G Hoffmann; Susan Darlow Journal: J Natl Compr Canc Netw Date: 2017-05 Impact factor: 11.908
Authors: Paul L Crispen; Rodney H Breau; Cristine Allmer; Christine M Lohse; John C Cheville; Bradley C Leibovich; Michael L Blute Journal: Eur Urol Date: 2010-09-15 Impact factor: 20.096