Title of article :
Nodal staging score: A tool for survival prediction of node-negative bladder cancer
Author/Authors :
Ku، نويسنده , , Ja Hyeon and Kim، نويسنده , , Hyeon Hoe and Kwak، نويسنده , , Cheol، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Abstract :
Purpose
ntly developed nodal staging score (NSS) might give an estimation of the likelihood of lymph node (LN) metastasis more accurately than simple cutoff of the number of LNs removed. The study aimed to evaluate whether patients with higher NSS will have a better outcome, since the NSS may provide an accurate staging across tumor stages.
als and methods
inical and histopathologic data from 242 patients with LN-negative urothelial bladder cancer (pN0) were analyzed. Probability of missing positive LN of <10% (clinical NSS 90%) was set by examining 6 nodes for clinical Ta-Tis tumors, 9 nodes for cT1 tumors, and 25 nodes for cT2 tumors. Multivariate analysis by Coxʹs proportional hazards model was used to determine the contribution of NSS to cancer-specific survival rates of patients. Discrimination, calibration, and clinical net benefit of the Cox regression model were evaluated using a time-dependent receiver operating characteristics curve, plotting Kaplan-Meyer curve and decision curve analysis.
s
status and NSS exhibited independent contributions in the Cox regression model. The predictive accuracy of the Cox regression model was 0.756. The Cox regression model successfully stratified the outcome into three different groups based on score. At 2, 5, and 8 years, the Cox regression model performed well across a wide range of threshold probabilities using decision curve analysis.
sions
ndings support the prognostic relevance of the NSS 90% cutoff in patients with LN-negative bladder cancer. The present results should be validated by prospective studies with defined LN dissection area.
Keywords :
bladder cancer , Urothelial carcinoma , Radical cystectomy , Lymph node , Outcomes
Journal title :
Urologic Oncology
Journal title :
Urologic Oncology