Prognostic significance of tumor grade for renal cell carcinoma

Int J Urol. 2000 Jan;7(1):4-9. doi: 10.1046/j.1442-2042.2000.00132.x.


Background: The natural history and prognosis of renal cell carcinoma cannot be predicted. Based on the Japanese classification system, the value of nuclear grade were assessed as a possible prognostic factor for renal cell carcinomas.

Methods: In this retrospective study of 116 patients with renal cell carcinoma, radical nephrectomy was performed. Survival rates were calculated using the Kaplan-Meier method and multivariate analysis was performed using Cox's proportional hazard model.

Results: Distribution by stage and grade in the population of renal cell carcinomas was as follows: pT1 in 13 cases (11.3%), pT2 in 65 cases (56.5%), pT3 in 36 cases (31.3%) and pT4 in one case (0.9%) and grade 1, 28 (24.1%), grade 2, 69 (59.5%) and grade 3, 16 (13.8%). Three cases could not be determined because of pre-operative embolization of the renal cell carcinomas. Nuclear grade was correlated with stage (P=0.0002), the presence of perirenal fat involvement (P=0.003) and metastases (P=0.007). A significant difference in survival was found between grades 1 and 3 (P=0.0001) and grades 2 and 3 (P=0.0001), respectively. Survival was significantly correlated with sex (P=0.0125), tumor size (P=0.0001), the presence of lymph node metastasis (P=0.0001), renal vein involvement (P=0.0001), perirenal fat involvement (P=0.002) or distant metastasis (P=0.0001). The multivariate analysis showed that the occurrence of tumor grade (P=0.0006) or distant metastasis were independent prognostic values.

Conclusion: The observations lead us to conclude that the nuclear grade according to the Japanese classification system appears to be of reliable prognostic value for renal cell carcinomas.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Carcinoma, Renal Cell / pathology*
  • Carcinoma, Renal Cell / secondary
  • Female
  • Humans
  • Kidney Neoplasms / pathology*
  • Lymphatic Metastasis
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prognosis
  • Proportional Hazards Models
  • Survival Analysis