Robert J Ellis1,2,3,4, Sharon J Del Vecchio2,3,4, Kevin M J Gallagher5,6, Danielle N Aliano3,7, Neil Barber8, Damien M Bolton9,10, Etienne T S Chew6, Jeff S Coombes3, Michael D Coory10, Ian D Davis11,12, James F Donaldson2,5,6, Ross S Francis2,3, Graham G Giles10,11,13, Glenda C Gobe2,3,4, Carmel M Hawley2,3,4, David W Johnson2,3,4, Alexander Laird5,6, Steve Leung5,6, Manar Malki8, David J T Marco10,14, Alan S McNeill5,6, Rachel E Neale15,3,16, Keng L Ng2,3,8, Simon Phipps5,6, Grant D Stewart17,18, Victoria M White13,19, Simon T Wood2,3, Susan J Jordan15,3. 1. Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia r.ellis1@uq.edu.au. 2. Princess Alexandra Hospital, Metro South Health, Brisbane, Queensland, Australia. 3. Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia. 4. Kidney Disease Research Collaborative, Translational Research Institute, Brisbane, Queensland, Australia. 5. Department of Urology, Western General Hospital, Edinburgh, United Kingdom. 6. University of Edinburgh, Edinburgh, United Kingdom. 7. Logan Hospital, Logan, Queensland, Australia. 8. Urology Department, Frimley Park Hospital, Frimley, United Kingdom. 9. Austin Urology, Austin Health, Melbourne, Victoria, Australia. 10. Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia. 11. Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia. 12. Eastern Health, Melbourne, Victoria, Australia. 13. Cancer Council Victoria, Melbourne, Victoria, Australia. 14. Centre for Palliative Care, St. Vincent's Hospital, Melbourne, Victoria, Australia. 15. Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia. 16. Queensland University of Technology, Brisbane, Queensland, Australia. 17. Department of Surgery, University of Cambridge, Cambridge, United Kingdom. 18. Addenbrooke's Hospital, Cambridge, United Kingdom. 19. School of Psychology, Deakin University, Geelong, Victoria, Australia.
Abstract
BACKGROUND: Clinically significant CKD following surgery for kidney cancer is associated with increased morbidity and mortality, but identifying patients at increased CKD risk remains difficult. Simple methods to stratify risk of clinically significant CKD after nephrectomy are needed. METHODS: To develop a tool for stratifying patients' risk of CKD arising after surgery for kidney cancer, we tested models in a population-based cohort of 699 patients with kidney cancer in Queensland, Australia (2012-2013). We validated these models in a population-based cohort of 423 patients from Victoria, Australia, and in patient cohorts from single centers in Queensland, Scotland, and England. Eligible patients had two functioning kidneys and a preoperative eGFR ≥60 ml/min per 1.73 m2. The main outcome was incident eGFR <45 ml/min per 1.73 m2 at 12 months postnephrectomy. We used prespecified predictors-age ≥65 years old, diabetes mellitus, preoperative eGFR, and nephrectomy type (partial/radical)-to fit logistic regression models and grouped patients according to degree of risk of clinically significant CKD (negligible, low, moderate, or high risk). RESULTS: Absolute risks of stage 3b or higher CKD were <2%, 3% to 14%, 21% to 26%, and 46% to 69% across the four strata of negligible, low, moderate, and high risk, respectively. The negative predictive value of the negligible risk category was 98.9% for clinically significant CKD. The c statistic for this score ranged from 0.84 to 0.88 across derivation and validation cohorts. CONCLUSIONS: Our simple scoring system can reproducibly stratify postnephrectomy CKD risk on the basis of readily available parameters. This clinical tool's quantitative assessment of CKD risk may be weighed against other considerations when planning management of kidney tumors and help inform shared decision making between clinicians and patients.
BACKGROUND: Clinically significant CKD following surgery for kidney cancer is associated with increased morbidity and mortality, but identifying patients at increased CKD risk remains difficult. Simple methods to stratify risk of clinically significant CKD after nephrectomy are needed. METHODS: To develop a tool for stratifying patients' risk of CKD arising after surgery for kidney cancer, we tested models in a population-based cohort of 699 patients with kidney cancer in Queensland, Australia (2012-2013). We validated these models in a population-based cohort of 423 patients from Victoria, Australia, and in patient cohorts from single centers in Queensland, Scotland, and England. Eligible patients had two functioning kidneys and a preoperative eGFR ≥60 ml/min per 1.73 m2. The main outcome was incident eGFR <45 ml/min per 1.73 m2 at 12 months postnephrectomy. We used prespecified predictors-age ≥65 years old, diabetes mellitus, preoperative eGFR, and nephrectomy type (partial/radical)-to fit logistic regression models and grouped patients according to degree of risk of clinically significant CKD (negligible, low, moderate, or high risk). RESULTS: Absolute risks of stage 3b or higher CKD were <2%, 3% to 14%, 21% to 26%, and 46% to 69% across the four strata of negligible, low, moderate, and high risk, respectively. The negative predictive value of the negligible risk category was 98.9% for clinically significant CKD. The c statistic for this score ranged from 0.84 to 0.88 across derivation and validation cohorts. CONCLUSIONS: Our simple scoring system can reproducibly stratify postnephrectomy CKD risk on the basis of readily available parameters. This clinical tool's quantitative assessment of CKD risk may be weighed against other considerations when planning management of kidney tumors and help inform shared decision making between clinicians and patients.
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