z-logo
open-access-imgOpen Access
Postoperative nomogram for disease recurrence and cancer-specific death for upper tract urothelial carcinoma: comparison to American Joint Committee on Cancer staging classification.
Author(s) -
Behfar Ehdaie,
Shahrokh F Shariat,
Caroline Savage,
Jonathan Coleman,
Guido Dalbagni
Publication year - 2014
Publication title -
urology journal
Language(s) - English
DOI - 10.22037/uj.v11i2.1891
PURPOSEWe sought to develop prognostic models to predict disease recurrence and cancerspecific mortality in patients with upper tract urothelial carcinoma (UTUC) who underwent radical nephroureterectomy (RNU).MATERIALS AND METHODSData on 253 patients treated with RNU between 1995 and 2008 at a single high-volume tertiary referral center were analyzed. Statistically and clinically significant patient and tumor characteristics were identified in a univariate analysis and incorporated into a multivariable Cox regression model. The model was compared to the 2010 American Joint Committee on Cancer (AJCC) staging classification using the concordance index (c-index), corrected for statistical optimism using bootstrap methods.RESULTSFive-year recurrence-free survival (RFS) and cancer-specific survival (CSS) rates were 73% [95% confidence interval (CI): 66-79%)] and 78% (95% CI: 71-84%), respectively. On multivariate analysis, higher preoperative glomerular filtration rate (GFR) was associated with better CSS [hazard ratio (HR) per 1 mL/min/m2 increase in GFR for CSS: 0.74; P = .002)], while higher pathologic stage (HR for pT2: 2.99 and for ≥ pT3: 7.34; P < .001) and lymph node involvement (HR: 3.75; P < .001) were associated with worse CSS; results were similar for RFS. The ability of the final models, which included preoperative GFR, lymph node status, pathologic grade, and stage, to predict RFS and CSS (c-index 0.82 and 0.83, respectively) was similar to that of the 2010 AJCC staging classification (c-index 0.80 and 0.81, respectively).CONCLUSIONGiven the data-dependent selection of variables in this single institution cohort, it is unlikely that the marginal improvement found with these prediction models would importantly impact clinical decision-making or improve patient care. The 2010 AJCC staging classification alone is very accurate and should continue to guide follow-up after RNU.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom