title: Prediction of progression after radical nephrectomy for patients with clear cell renal cell carcinoma: a stratification tool for prospective clinical trials.
abstract: BACKGROUND
  The objective of the current study was to develop an algorithm to predict progression to metastases after radical nephrectomy for patients with clinically localized renal cell carcinoma (RCC) to allow stratification of patients for potential adjuvant therapy trials.
  
  
  METHODS
  The authors identified 1671 sporadic patients with clinically localized, unilateral clear cell RCC who underwent radical nephrectomy between 1970 and 2000. The clinical features examined included age, gender, smoking history, recent onset hypertension, performance status, and presenting symptoms. The pathologic features examined included surgical margins, tumor stage, regional lymph node status, tumor size, nuclear grade, histologic tumor necrosis, sarcomatoid component, cystic architecture, and multifocality. Metastases free survival was estimated using the Kaplan-Meier method. A multivariate Cox proportional hazards regression model was fit to determine associations between the clinical and pathologic features and distant metastases.
  
  
  RESULTS
  The median follow-up was 5.4 years (range, 0-31 years). Metastases occurred in 479 patients at a median of 1.3 years (range, 0-25 years) after nephrectomy. The estimated metastases free survival rates were 86.9% at 1 year, 77.8% at 3 years, 74.1% at 5 years, 70.8% at 7 years, and 67.1% at 10 years. Multivariate analysis showed that the following features were associated with progression to metastases: tumor stage, regional lymph node status, tumor size, nuclear grade, and histologic tumor necrosis (P < 0.001 for all).
  
  
  CONCLUSIONS
  In patients with clear cell RCC, tumor stage, regional lymph node status, tumor size, nuclear grade, and histologic tumor necrosis showed statistically significant associations with progression to metastatic RCC. The authors present a scoring algorithm based on these features that can be used to predict disease progression after patients undergo radical nephrectomy for clinically localized clear cell RCC. Cancer 2003;97:1663-71.
authors.affiliation: Department of Urology, Mayo Medical School and Mayo Clinic, Rochester, Minnesota 55905, USA. leibovich.bradley@mayo.edu
authors.forename: Bradley C
authors.initials: BC
authors.lastname: Leibovich
authors.forename: Michael L
authors.initials: ML
authors.lastname: Blute
authors.forename: John C
authors.initials: JC
authors.lastname: Cheville
authors.forename: Christine M
authors.initials: CM
authors.lastname: Lohse
authors.forename: Igor
authors.initials: I
authors.lastname: Frank
authors.forename: Eugene D
authors.initials: ED
authors.lastname: Kwon
authors.forename: Amy L
authors.initials: AL
authors.lastname: Weaver
authors.forename: Alexander S
authors.initials: AS
authors.lastname: Parker
authors.forename: Horst
authors.initials: H
authors.lastname: Zincke
mesh_terms: D018262:Adenocarcinoma, Clear Cell / Q000473:pathology / Q000601:surgery*; D000328:Adult; D000368:Aged; D000465:Algorithms; D002986:Clinical Trials as Topic; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000473:pathology* / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D009362:Neoplasm Metastasis; D009392:Nephrectomy