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Abstract: SA-PO157

A Predictive Model for Kidney Failure After Nephrectomy for Localized Kidney Cancer: The Kidney Cancer Risk Equation

Session Information

Category: Onconephrology

  • 1600 Onconephrology

Authors

  • Harasemiw, Oksana, University of Manitoba Max Rady College of Medicine, Winnipeg, Manitoba, Canada
  • Nayak, Jasmir G., University of Manitoba Max Rady College of Medicine, Winnipeg, Manitoba, Canada
  • Grubic, Nicholas, Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
  • Ferguson, Thomas W., University of Manitoba Max Rady College of Medicine, Winnipeg, Manitoba, Canada
  • Sood, Manish M., University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada
  • Tangri, Navdeep, University of Manitoba Max Rady College of Medicine, Winnipeg, Manitoba, Canada
Background

Nephrectomy is the mainstay treatment for individuals with localized kidney cancer. However, surgery can potentially result in functional kidney impairment leading to kidney failure requiring dialysis or transplantation. There are currently no clinical tools available for clinicians to pre-operatively identify which patients are at risk of kidney failure, and therefore, the aim of our study was to develop and validate a prediction equation for kidney failure after nephrectomy for kidney cancer.

Methods

A population-level cohort study was conducted with adults (≥ 18 years old; n=1,026) from Manitoba, Canada who were diagnosed with non-metastatic kidney cancer between January 1, 2004 and December 31, 2016, were treated with either a partial or radical nephrectomy, and had at least 1 estimated glomerular filtration rate (eGFR) measurement available pre and post nephrectomy. Demographic, clinical, and laboratory data were used to develop the prediction models using Cox proportional hazards regression methods. We subsequently externally validated the models using data from 12,043 individuals from Ontario, Canada. The primary outcome was dialysis, transplantation, or an eGFR < 15 mL/min/1.73m2 during the follow-up period.

Results

Among individuals in the development cohort (mean age 61.2 ± 11.7; mean eGFR 79.5 ± 22.8 mL/min/1.73m2; 39.0% partial nephrectomy/61.2% radical), 10.4% reached kidney failure during the follow-up period. The final model included 6 variables: age, sex, baseline eGFR, urine albumin-to-creatinine ratio, nephrectomy type, diabetes mellitus. The 5-year C-statistic was 0.83 (74.8, 91.4) in the development cohort and 0.86 (0.84, 0.88) in the validation cohort.

Conclusion

We developed and externally validated a simple equation that incorporates easily accessible data and can accurately predict kidney failure in individuals undergoing nephrectomy for treatment of localized kidney cancer. This tool can help inform pre-operative discussion about kidney failure risk in patients facing surgical options for localized kidney cancer.

Funding

  • Private Foundation Support