Urology
Volume 75, Issue 2 , Pages 315-320, February 2010

A Population-based Assessment of Perioperative Mortality After Nephroureterectomy for Upper-tract Urothelial Carcinoma

  • Claudio Jeldres

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
    • Department of Urology, University of Montréal, Montreal, Canada
  • ,
  • Maxine Sun

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
  • ,
  • Hendrik Isbarn

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
    • Martini-Clinic, Prostate Cancer Center Hamburg-Eppendorf, Hamburg, Germany
  • ,
  • Giovanni Lughezzani

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
    • Department of Urology, Vita-Salute San Raffaele, Milan, Italy
  • ,
  • Lars Budäus

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
    • Martini-Clinic, Prostate Cancer Center Hamburg-Eppendorf, Hamburg, Germany
  • ,
  • Ahmed Alasker

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
    • Department of Urology, University of Montréal, Montreal, Canada
  • ,
  • Shahrohk F. Shariat

      Affiliations

    • Department of Urology, University of Texas Southwestern Medical Center, Dallas, Texas
  • ,
  • Jean-Baptiste Lattouf

      Affiliations

    • Department of Urology, University of Montréal, Montreal, Canada
  • ,
  • Hugues Widmer

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
  • ,
  • Daniel Pharand

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
  • ,
  • Philippe Arjane

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
  • ,
  • Markus Graefen

      Affiliations

    • Martini-Clinic, Prostate Cancer Center Hamburg-Eppendorf, Hamburg, Germany
  • ,
  • Francesco Montorsi

      Affiliations

    • Department of Urology, Vita-Salute San Raffaele, Milan, Italy
  • ,
  • Paul Perrotte

      Affiliations

    • Martini-Clinic, Prostate Cancer Center Hamburg-Eppendorf, Hamburg, Germany
  • ,
  • Pierre I. Karakiewicz

      Affiliations

    • Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center, Montreal, Quebec, Canada
    • Department of Urology, University of Montréal, Montreal, Canada
    • Corresponding Author InformationReprint requests: Pierre I. Karakiewicz, M.D., F.R.C.S.C., Cancer Prognostics and Health Outcomes Unit, University of Montréal Health Center (CHUM), 1058, Rue St-Denis, Montréal, QC, Canada, H2X 3J4

Received 17 July 2009; accepted 4 October 2009. published online 07 December 2009.

Objectives

To examine the perioperative mortality rates at 90 days (90 dM) after nephroureterectomy (NU) and to devise a model capable of identifying individuals at an elevated 90 dM risk. NU represents the surgical standard of care for patients with invasive, nonmetastatic upper-tract urothelial carcinoma. However, this major abdominal surgery may be associated with a nonnegligible rate of perioperative mortality.

Methods

We identified 6078 upper-tract urothelial carcinoma patients treated with NU from 17 registries of the Surveillance, Epidemiology, and End Results database, between 1988 and 2006. Stratified analyses quantified 90 dM rates according to age, gender, race, year of diagnosis, tumor location, surgery type, T stage, tumor grade, and lymph node status. Subsequently, multivariable logistic regression models identified predictors of 90 dM within the development cohort (n = 3039). The accuracy and calibration of the model were tested in an independent validation cohort (n = 3039).

Results

The overall 90 dM rate was 4.4%. Continuously coded age and T and N stages achieved an independent predictor status in multivariable logistic regression models and represented key variables for prediction of individual 90 dM risk after NU, with 73.4% accuracy. Excellent correlation between predicted and observed 90 dM rates after NU was recorded.

Conclusions

In this large-scale population-based analysis of perioperative mortality after NU, age and T and N stages emerged as the most informative predictor of 90 dM. We recommend the use of this tool in individual decision-making and in informed consent considerations.

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 Pierre I. Karakiewicz is partially supported by the University of Montréal Health Center Urology Associates, Fonds de la Recherche en Santé du Quebec, the University of Montréal Department of Surgery and the University of Montréal Health Center (CHUM) Foundation.

 Claudio Jeldres and Maxine Sun have contributed equally for the preparation of this manuscript.

PII: S0090-4295(09)02703-4

doi:10.1016/j.urology.2009.10.004

Urology
Volume 75, Issue 2 , Pages 315-320, February 2010