Correlation between symptom graduation, tumor characteristics and survival in renal cell carcinoma

Eur Urol. 2003 Aug;44(2):226-32. doi: 10.1016/s0302-2838(03)00216-1.


Objectives: To compare renal tumors with respect to initial clinical presentation and assess the prognostic value of a symptom based classification.

Material and methods: Based on symptoms at diagnosis, 388 renal tumors were stratified into three groups: (1) asymptomatic tumors; (2) tumors with local symptoms (3) tumors with systemic symptoms. The three groups were compared for usual clinical and pathological variables using chi(2)-tests and Anova regression, for qualitative and quantitative variables, respectively. Survival assessment was made with univariate and multivariate analysis using the Kaplan-Meier method and Cox regression analysis.

Results: The three defined groups were significantly different for all analysed variables except for age, sex ratio and pathological subtype. In univariate analysis: ECOG performance status, symptom classification, tumour size, TNM stage and grade, adrenal, perinephric fat or vein invasion were significant prognostic factors (p<0.001). In multivariate analysis, symptom classification, TNM stage, Fuhrman grade and perinephric fat invasion remained independent prognostic factors (p<0.001).

Conclusion: The proposed classification merits further validation through multi-institutional studies before integrating it in further prognosis algorithms.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Carcinoma, Renal Cell / classification*
  • Carcinoma, Renal Cell / diagnosis
  • Carcinoma, Renal Cell / mortality
  • Carcinoma, Renal Cell / surgery
  • Female
  • Follow-Up Studies
  • Health Status
  • Humans
  • Kidney Neoplasms / classification*
  • Kidney Neoplasms / diagnosis
  • Kidney Neoplasms / mortality
  • Kidney Neoplasms / surgery
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Neoplasm Staging
  • Nephrectomy
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies
  • Survival Analysis