title: [Value of the postoperative Störkel score. Predict disease-free survival of patients with surgically resected renal cell carcinoma].
abstract: OBJECTIVE
  To determine the value of clinical and pathological parameters defining the Störkel score in order to predict outcomes of patients with surgically treated renal cell carcinoma (RCC).
  
  
  METHODS
  A total of 834 consecutive patients having radical or partial nephrectomy were retrospectively reviewed. For each patient with RCC, the prognostic Störkel score was calculated according to the following variables: Robson stage, Thoenes nuclear grading, histological type, pattern of growth, and age. Based on the Störkel score, patients were divided into groups: those with good prognosis (GP), intermediate prognosis (IP), and poor prognosis (PP). Cancer-specific survival (CSS) and overall survival (OS) were estimated using the Kaplan-Meier method. The accuracy of prediction of CSS and OS with the Störkel score was analyzed using Kaplan-Meier analysis, proportional hazards regression, and graphic representation [(Kaplan-Meier curves, area under the curve (AUC)]. In 564 patients who were still alive, the median follow-up was 79 months (mean 84.8 months).
  
  
  RESULTS
  In the GP, IP, and PP groups, CSS after 8 years was 86.7%, 75.6%, and 13.7%, respectively (p<0.001). In the multiple analysis, only the Robson stage and Thoenes nuclear grading independently predicted CSS. Accordingly, the prognostic accuracy of the Störkel score (CSS prediction: AUC=0.744, 95% CI=0.70-0.79) was not better than with a reduced model that included the Robson stage and grading only (CSS prediction: AUC=0.765, 95%CI=0.72-0.81).
  
  
  CONCLUSIONS
  Of all parameters included in the Störkel score, only the Robson stage and nuclear grading are significant prognostic factors. Hence, we recommend an accordant modification of the score with additional variables.
authors.affiliation: Klinik für Urologie, Carl-Thiem-Klinikum, Thiemstrasse 111, 03048 Cottbus. Matthias.May1@web.de
authors.forename: M
authors.initials: M
authors.lastname: May
authors.forename: S
authors.initials: S
authors.lastname: Brookman-Amissah
authors.forename: S
authors.initials: S
authors.lastname: Pflanz
authors.forename: N
authors.initials: N
authors.lastname: Knoll
authors.forename: J
authors.initials: J
authors.lastname: Roigas
authors.forename: S
authors.initials: S
authors.lastname: Gunia
authors.forename: B
authors.initials: B
authors.lastname: Hoschke
authors.forename: F
authors.initials: F
authors.lastname: Kendel
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002292:Carcinoma, Renal Cell / Q000175:diagnosis / Q000453:epidemiology* / Q000601:surgery*; D018572:Disease-Free Survival; D005260:Female; D005858:Germany / Q000453:epidemiology; D006801:Humans; D007680:Kidney Neoplasms / Q000175:diagnosis / Q000453:epidemiology* / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D009392:Nephrectomy / Q000401:mortality*; D017063:Outcome Assessment, Health Care / Q000379:methods*; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016019:Survival Analysis; D015996:Survival Rate; D016896:Treatment Outcome