Postoperative nomogram for disease recurrence and cancer-specific death for upper tract urothelial carcinoma: comparison to American Joint Committee on Cancer staging classification.
Academic Article
Overview
abstract
PURPOSE: We 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 METHODS: Data 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. RESULTS: Five-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). CONCLUSION: Given 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.
