Yonsei nomogram: A predictive model of new-onset chronic kidney disease after on-clamp partial nephrectomy in patients with T1 renal tumors

Ali Abdel Raheem, Tae Young Shin, Ki Don Chang, Glen Denmer R. Santok, Mohamed Jayed Alenzi, Young Eun Yoon, Won Sik Ham, Woong Kyu Han, Young Deuk Choi, Koon Ho Rha

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Abstract

Objectives: To develop a predictive nomogram for chronic kidney disease-free survival probability in the long term after partial nephrectomy. Methods: A retrospective analysis was carried out of 698 patients with T1 renal tumors undergoing partial nephrectomy at a tertiary academic institution. A multivariable Cox regression analysis was carried out based on parameters proven to have an impact on postoperative renal function. Patients with incomplete data, <12 months follow up and preoperative chronic kidney disease stage III or greater were excluded. The study end-points were to identify independent risk factors for new-onset chronic kidney disease development, as well as to construct a predictive model for chronic kidney disease-free survival probability after partial nephrectomy. Results: The median age was 52 years, median tumor size was 2.5 cm and mean warm ischemia time was 28 min. A total of 91 patients (13.1%) developed new-onset chronic kidney disease at a median follow up of 60 months. The chronic kidney disease-free survival rates at 1, 3, 5 and 10 year were 97.1%, 94.4%, 85.3% and 70.6%, respectively. On multivariable Cox regression analysis, age (1.041, P = 0.001), male sex (hazard ratio 1.653, P < 0.001), diabetes mellitus (hazard ratio 1.921, P = 0.046), tumor size (hazard ratio 1.331, P < 0.001) and preoperative estimated glomerular filtration rate (hazard ratio 0.937, P < 0.001) were independent predictors for new-onset chronic kidney disease. The C-index for chronic kidney disease-free survival was 0.853 (95% confidence interval 0.815–0.895). Conclusion: We developed a novel nomogram for predicting the 5-year chronic kidney disease-free survival probability after on-clamp partial nephrectomy. This model might have an important role in partial nephrectomy decision-making and follow-up plan after surgery. External validation of our nomogram in a larger cohort of patients should be considered.

Original languageEnglish
Pages (from-to)690-697
Number of pages8
JournalInternational Journal of Urology
Volume25
Issue number7
DOIs
Publication statusPublished - 2018 Jul

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Nomograms
Nephrectomy
Chronic Renal Insufficiency
Kidney
Disease-Free Survival
Neoplasms
Regression Analysis
Warm Ischemia
Sex Ratio
Glomerular Filtration Rate
Decision Making
Diabetes Mellitus
Survival Rate
Confidence Intervals

All Science Journal Classification (ASJC) codes

  • Urology

Cite this

Abdel Raheem, Ali ; Shin, Tae Young ; Chang, Ki Don ; Santok, Glen Denmer R. ; Alenzi, Mohamed Jayed ; Yoon, Young Eun ; Ham, Won Sik ; Han, Woong Kyu ; Choi, Young Deuk ; Rha, Koon Ho. / Yonsei nomogram : A predictive model of new-onset chronic kidney disease after on-clamp partial nephrectomy in patients with T1 renal tumors. In: International Journal of Urology. 2018 ; Vol. 25, No. 7. pp. 690-697.
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title = "Yonsei nomogram: A predictive model of new-onset chronic kidney disease after on-clamp partial nephrectomy in patients with T1 renal tumors",
abstract = "Objectives: To develop a predictive nomogram for chronic kidney disease-free survival probability in the long term after partial nephrectomy. Methods: A retrospective analysis was carried out of 698 patients with T1 renal tumors undergoing partial nephrectomy at a tertiary academic institution. A multivariable Cox regression analysis was carried out based on parameters proven to have an impact on postoperative renal function. Patients with incomplete data, <12 months follow up and preoperative chronic kidney disease stage III or greater were excluded. The study end-points were to identify independent risk factors for new-onset chronic kidney disease development, as well as to construct a predictive model for chronic kidney disease-free survival probability after partial nephrectomy. Results: The median age was 52 years, median tumor size was 2.5 cm and mean warm ischemia time was 28 min. A total of 91 patients (13.1{\%}) developed new-onset chronic kidney disease at a median follow up of 60 months. The chronic kidney disease-free survival rates at 1, 3, 5 and 10 year were 97.1{\%}, 94.4{\%}, 85.3{\%} and 70.6{\%}, respectively. On multivariable Cox regression analysis, age (1.041, P = 0.001), male sex (hazard ratio 1.653, P < 0.001), diabetes mellitus (hazard ratio 1.921, P = 0.046), tumor size (hazard ratio 1.331, P < 0.001) and preoperative estimated glomerular filtration rate (hazard ratio 0.937, P < 0.001) were independent predictors for new-onset chronic kidney disease. The C-index for chronic kidney disease-free survival was 0.853 (95{\%} confidence interval 0.815–0.895). Conclusion: We developed a novel nomogram for predicting the 5-year chronic kidney disease-free survival probability after on-clamp partial nephrectomy. This model might have an important role in partial nephrectomy decision-making and follow-up plan after surgery. External validation of our nomogram in a larger cohort of patients should be considered.",
author = "{Abdel Raheem}, Ali and Shin, {Tae Young} and Chang, {Ki Don} and Santok, {Glen Denmer R.} and Alenzi, {Mohamed Jayed} and Yoon, {Young Eun} and Ham, {Won Sik} and Han, {Woong Kyu} and Choi, {Young Deuk} and Rha, {Koon Ho}",
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Yonsei nomogram : A predictive model of new-onset chronic kidney disease after on-clamp partial nephrectomy in patients with T1 renal tumors. / Abdel Raheem, Ali; Shin, Tae Young; Chang, Ki Don; Santok, Glen Denmer R.; Alenzi, Mohamed Jayed; Yoon, Young Eun; Ham, Won Sik; Han, Woong Kyu; Choi, Young Deuk; Rha, Koon Ho.

In: International Journal of Urology, Vol. 25, No. 7, 07.2018, p. 690-697.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Yonsei nomogram

T2 - A predictive model of new-onset chronic kidney disease after on-clamp partial nephrectomy in patients with T1 renal tumors

AU - Abdel Raheem, Ali

AU - Shin, Tae Young

AU - Chang, Ki Don

AU - Santok, Glen Denmer R.

AU - Alenzi, Mohamed Jayed

AU - Yoon, Young Eun

AU - Ham, Won Sik

AU - Han, Woong Kyu

AU - Choi, Young Deuk

AU - Rha, Koon Ho

PY - 2018/7

Y1 - 2018/7

N2 - Objectives: To develop a predictive nomogram for chronic kidney disease-free survival probability in the long term after partial nephrectomy. Methods: A retrospective analysis was carried out of 698 patients with T1 renal tumors undergoing partial nephrectomy at a tertiary academic institution. A multivariable Cox regression analysis was carried out based on parameters proven to have an impact on postoperative renal function. Patients with incomplete data, <12 months follow up and preoperative chronic kidney disease stage III or greater were excluded. The study end-points were to identify independent risk factors for new-onset chronic kidney disease development, as well as to construct a predictive model for chronic kidney disease-free survival probability after partial nephrectomy. Results: The median age was 52 years, median tumor size was 2.5 cm and mean warm ischemia time was 28 min. A total of 91 patients (13.1%) developed new-onset chronic kidney disease at a median follow up of 60 months. The chronic kidney disease-free survival rates at 1, 3, 5 and 10 year were 97.1%, 94.4%, 85.3% and 70.6%, respectively. On multivariable Cox regression analysis, age (1.041, P = 0.001), male sex (hazard ratio 1.653, P < 0.001), diabetes mellitus (hazard ratio 1.921, P = 0.046), tumor size (hazard ratio 1.331, P < 0.001) and preoperative estimated glomerular filtration rate (hazard ratio 0.937, P < 0.001) were independent predictors for new-onset chronic kidney disease. The C-index for chronic kidney disease-free survival was 0.853 (95% confidence interval 0.815–0.895). Conclusion: We developed a novel nomogram for predicting the 5-year chronic kidney disease-free survival probability after on-clamp partial nephrectomy. This model might have an important role in partial nephrectomy decision-making and follow-up plan after surgery. External validation of our nomogram in a larger cohort of patients should be considered.

AB - Objectives: To develop a predictive nomogram for chronic kidney disease-free survival probability in the long term after partial nephrectomy. Methods: A retrospective analysis was carried out of 698 patients with T1 renal tumors undergoing partial nephrectomy at a tertiary academic institution. A multivariable Cox regression analysis was carried out based on parameters proven to have an impact on postoperative renal function. Patients with incomplete data, <12 months follow up and preoperative chronic kidney disease stage III or greater were excluded. The study end-points were to identify independent risk factors for new-onset chronic kidney disease development, as well as to construct a predictive model for chronic kidney disease-free survival probability after partial nephrectomy. Results: The median age was 52 years, median tumor size was 2.5 cm and mean warm ischemia time was 28 min. A total of 91 patients (13.1%) developed new-onset chronic kidney disease at a median follow up of 60 months. The chronic kidney disease-free survival rates at 1, 3, 5 and 10 year were 97.1%, 94.4%, 85.3% and 70.6%, respectively. On multivariable Cox regression analysis, age (1.041, P = 0.001), male sex (hazard ratio 1.653, P < 0.001), diabetes mellitus (hazard ratio 1.921, P = 0.046), tumor size (hazard ratio 1.331, P < 0.001) and preoperative estimated glomerular filtration rate (hazard ratio 0.937, P < 0.001) were independent predictors for new-onset chronic kidney disease. The C-index for chronic kidney disease-free survival was 0.853 (95% confidence interval 0.815–0.895). Conclusion: We developed a novel nomogram for predicting the 5-year chronic kidney disease-free survival probability after on-clamp partial nephrectomy. This model might have an important role in partial nephrectomy decision-making and follow-up plan after surgery. External validation of our nomogram in a larger cohort of patients should be considered.

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