title: Development and external validation of a nomogram predicting disease specific survival after nephrectomy for papillary renal cell carcinoma.
abstract: OBJECTIVE
  We developed and externally validated a prognostic nomogram specifically for papillary renal cell carcinoma.
  
  
  METHODS
  We retrospectively studied 435 patients who underwent radical or partial nephrectomy for papillary renal cell carcinoma at 3 institutions. Slides were reviewed by 1 uropathologist per institution. We constructed a nomogram predicting 5-year disease specific survival as a graphic representation of significant variables on multivariate Cox proportional hazards regression analysis using data on 258 patients from 2 of the 3 institutions. Nomogram discrimination and calibration were assessed by bootstrapping to obtain relatively unbiased estimates. External validation was done in 177 patients from a third institution.
  
  
  RESULTS
  At a median 50.8-month followup 77 papillary renal cell carcinoma related deaths had occurred. In the multivariate Cox proportional hazards model incidental detection, T classification, M classification, vascular invasion and tumor necrosis extent were retained as independent prognostic factors of disease specific survival and formed the basis of the nomogram. The nomogram predicted well with a 93.6% bootstrapped corrected concordance index and showed good calibration. External independent validation revealed 94.2% predictive accuracy.
  
  
  CONCLUSIONS
  We developed a highly accurate tool specifically for papillary renal cell carcinoma using basic clinical and pathological information to predict disease specific survival. This tool should be helpful to identify papillary renal cell carcinoma with aggressive clinical behavior and may contribute to the ability to individualize postoperative surveillance and therapy.
authors.affiliation: Department of Urology, Medical University of Vienna, Vienna, Austria.
authors.forename: Tobias
authors.initials: T
authors.lastname: Klatte
authors.forename: Mesut
authors.initials: M
authors.lastname: Remzi
authors.forename: Richard E
authors.initials: RE
authors.lastname: Zigeuner
authors.forename: Sebastian
authors.initials: S
authors.lastname: Mannweiler
authors.forename: Jonathan W
authors.initials: JW
authors.lastname: Said
authors.forename: Fairooz F
authors.initials: FF
authors.lastname: Kabbinavar
authors.forename: Andrea
authors.initials: A
authors.lastname: Haitel
authors.forename: Matthias
authors.initials: M
authors.lastname: Waldert
authors.forename: Michela
authors.initials: M
authors.lastname: de Martino
authors.forename: Michael
authors.initials: M
authors.lastname: Marberger
authors.forename: Arie S
authors.initials: AS
authors.lastname: Belldegrun
authors.forename: Allan J
authors.initials: AJ
authors.lastname: Pantuck
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002138:Calibration; D002291:Carcinoma, Papillary / Q000401:mortality* / Q000601:surgery*; D002292:Carcinoma, Renal Cell / Q000401:mortality* / Q000601:surgery*; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000401:mortality* / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D009336:Necrosis; D009361:Neoplasm Invasiveness; D009392:Nephrectomy; D049451:Nomograms; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D016019:Survival Analysis