title: A scoring algorithm to predict survival for patients with metastatic clear cell renal cell carcinoma: a stratification tool for prospective clinical trials.
abstract: OBJECTIVE
  We developed a clinically useful scoring algorithm to predict cancer specific survival for patients with clear cell metastatic renal cell carcinoma (RCC).
  
  
  METHODS
  We studied 727 patients treated with radical nephrectomy for clear cell RCC from 1970 to 2000 who had distant metastases at nephrectomy (285) or in whom metastases subsequently developed (442). A scoring algorithm to predict cancer specific survival was developed using the regression coefficients from a Cox proportional hazards model.
  
  
  RESULTS
  There were 606 deaths from clear cell RCC at a median of 1.0 years (range 0 to 14) following metastatic RCC. Constitutional symptoms at nephrectomy (+2), metastases to the bone (+2) or liver (+4), metastases in multiple simultaneous sites (+2), metastases at nephrectomy (+1) or within 2 years of nephrectomy (+3), complete resection of all metastatic sites (-5), tumor thrombus level I to IV (+3), and the primary pathological features of nuclear grade 4 (+3) and histological tumor necrosis (+2) were significantly associated with death from RCC. All patients started with a score of 0 and points were added or subtracted as indicated in parentheses. Cancer specific survival rates at 1 year were 85.1%, 72.1%, 58.8%, 39.0%, and 25.1%, respectively, for patients with scores of -5 to -1, scores of 0 to 2, scores of 3 to 6, scores of 7 or 8, and scores of 9 or more.
  
  
  CONCLUSIONS
  This scoring algorithm can be used to predict cancer specific survival for patients with metastatic clear cell RCC.
authors.affiliation: Department of Urology, Mayo Medical School, Rochester, Minnesota, USA. leibovich.bradley@mayo.edu
authors.forename: Bradley C
authors.initials: BC
authors.lastname: Leibovich
authors.forename: John C
authors.initials: JC
authors.lastname: Cheville
authors.forename: Christine M
authors.initials: CM
authors.lastname: Lohse
authors.forename: Horst
authors.initials: H
authors.lastname: Zincke
authors.forename: Igor
authors.initials: I
authors.lastname: Frank
authors.forename: Eugene D
authors.initials: ED
authors.lastname: Kwon
authors.forename: Jaime R
authors.initials: JR
authors.lastname: Merchan
authors.forename: Michael L
authors.initials: ML
authors.lastname: Blute
mesh_terms: D018262:Adenocarcinoma, Clear Cell / Q000401:mortality* / Q000556:secondary / Q000601:surgery; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000465:Algorithms; D002292:Carcinoma, Renal Cell / Q000401:mortality* / Q000556:secondary / Q000601:surgery; D002423:Cause of Death; D002986:Clinical Trials as Topic; D005260:Female; D006801:Humans; D015994:Incidence; D007680:Kidney Neoplasms / Q000401:mortality* / Q000473:pathology / Q000601:surgery; D008297:Male; D008875:Middle Aged; D009362:Neoplasm Metastasis; D009367:Neoplasm Staging; D009392:Nephrectomy / Q000379:methods; D011237:Predictive Value of Tests; D011336:Probability; D011379:Prognosis; D011446:Prospective Studies; D012042:Registries; D012189:Retrospective Studies; D018570:Risk Assessment; D017678:Sex Distribution; D016019:Survival Analysis