Tumor-size breakpoint for prognostic stratification of localized renal cell carcinoma

Urology. 2004 Feb;63(2):235-9; discussion 239-40. doi: 10.1016/j.urology.2003.09.081.

Abstract

Objectives: To identify an optimal tumor-size breakpoint to distinguish between two groups with different prognoses in a large cohort of patients with localized renal cell carcinoma (RCC).

Methods: We reviewed the clinical records of 813 patients who had undergone surgical treatment for localized RCC from 1976 to 2000. The optimal breakpoint for the pathologic size was calculated by receiver operating characteristic curve analysis.

Results: The receiver operating characteristic curve analysis identified 5.5 cm as the optimal breakpoint to predict cancer-specific survival rates. The pathologic size was 5.5 cm or less in 565 neoplasms (69.5%) and more than 5.5 cm in 248 (30.5%). In the multivariate analysis, the more predictive model included the 5.5-cm-or-less pathologic size breakpoint. The pathologic size of 7 cm or less was not an independent variable in this cohort of patients.

Conclusions: In a large cohort of patients with localized RCC, 5.5 cm was the optimal breakpoint to classify patients with localized RCC into two subgroups with different prognoses; the 7-cm-or-less cutoff value was not an independent variable. The data obtained by analyzing a large cohort of consecutive patients should be validated by other large series with the prospective of redefining the TNM staging system.

Publication types

  • Comparative Study
  • Evaluation Study
  • Review

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Carcinoma, Renal Cell / mortality
  • Carcinoma, Renal Cell / pathology*
  • Cohort Studies
  • Female
  • Follow-Up Studies
  • Humans
  • Italy / epidemiology
  • Kidney Neoplasms / mortality
  • Kidney Neoplasms / pathology*
  • Life Tables
  • Likelihood Functions
  • Male
  • Middle Aged
  • Neoplasm Staging
  • Neoplasms, Multiple Primary / mortality
  • Neoplasms, Multiple Primary / pathology
  • Prognosis
  • Proportional Hazards Models
  • ROC Curve
  • Retrospective Studies
  • Sensitivity and Specificity
  • Survival Analysis
  • Survival Rate