Development and validation of a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation

Japan Academic Consortium of Kidney Transplantation (JACK) Investigators

Research output: Contribution to journalArticle

Abstract

Background: Recently, living-donor kidney transplantation from marginal donors has been increasing. However, a simple prediction model for graft function including preoperative marginal factors is limited. Here, we developed and validated a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. Methods: We retrospectively investigated 343 patients who underwent living-donor kidney transplantation at Kyushu University Hospital (derivation cohort). Low graft function was defined as an estimated glomerular filtration rate of < 45 mL/min/1.73 m2 at 1 year. A prediction model was developed using a multivariable logistic regression model, and verified using data from 232 patients who underwent living-donor kidney transplantation at Tokyo Women's Medical University Hospital (validation cohort). Results: In the derivation cohort, 89 patients (25.9%) had low graft function at 1 year. Donor age, donor-estimated glomerular filtration rate, donor hypertension, and donor/recipient body weight ratio were selected as predictive factors. This model demonstrated modest discrimination (c-statistic = 0.77) and calibration (Hosmer–Lemeshow test, P = 0.83). Furthermore, this model demonstrated good discrimination (c-statistic = 0.76) and calibration (Hosmer–Lemeshow test, P = 0.54) in the validation cohort. Furthermore, donor age, donor-estimated glomerular filtration rate, and donor hypertension were strongly associated with glomerulosclerosis and atherosclerotic vascular changes in the “zero-time” biopsy. Conclusions: This model using four pre-operative variables will be a simple, but useful guide to estimate graft function at 1 year after kidney transplantation, especially in marginal donors, in the clinical setting.

Original languageEnglish
Pages (from-to)1331-1340
Number of pages10
JournalClinical and Experimental Nephrology
Volume23
Issue number11
DOIs
Publication statusPublished - Nov 1 2019

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Living Donors
Kidney Transplantation
Tissue Donors
Transplants
Glomerular Filtration Rate
Calibration
Logistic Models
Hypertension
Tokyo
Blood Vessels
Body Weight
Biopsy

All Science Journal Classification (ASJC) codes

  • Physiology
  • Nephrology
  • Physiology (medical)

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Development and validation of a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. / Japan Academic Consortium of Kidney Transplantation (JACK) Investigators.

In: Clinical and Experimental Nephrology, Vol. 23, No. 11, 01.11.2019, p. 1331-1340.

Research output: Contribution to journalArticle

Japan Academic Consortium of Kidney Transplantation (JACK) Investigators. / Development and validation of a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. In: Clinical and Experimental Nephrology. 2019 ; Vol. 23, No. 11. pp. 1331-1340.
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abstract = "Background: Recently, living-donor kidney transplantation from marginal donors has been increasing. However, a simple prediction model for graft function including preoperative marginal factors is limited. Here, we developed and validated a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. Methods: We retrospectively investigated 343 patients who underwent living-donor kidney transplantation at Kyushu University Hospital (derivation cohort). Low graft function was defined as an estimated glomerular filtration rate of < 45 mL/min/1.73 m2 at 1 year. A prediction model was developed using a multivariable logistic regression model, and verified using data from 232 patients who underwent living-donor kidney transplantation at Tokyo Women's Medical University Hospital (validation cohort). Results: In the derivation cohort, 89 patients (25.9{\%}) had low graft function at 1 year. Donor age, donor-estimated glomerular filtration rate, donor hypertension, and donor/recipient body weight ratio were selected as predictive factors. This model demonstrated modest discrimination (c-statistic = 0.77) and calibration (Hosmer–Lemeshow test, P = 0.83). Furthermore, this model demonstrated good discrimination (c-statistic = 0.76) and calibration (Hosmer–Lemeshow test, P = 0.54) in the validation cohort. Furthermore, donor age, donor-estimated glomerular filtration rate, and donor hypertension were strongly associated with glomerulosclerosis and atherosclerotic vascular changes in the “zero-time” biopsy. Conclusions: This model using four pre-operative variables will be a simple, but useful guide to estimate graft function at 1 year after kidney transplantation, especially in marginal donors, in the clinical setting.",
author = "{Japan Academic Consortium of Kidney Transplantation (JACK) Investigators} and Yuta Matsukuma and Kosuke Masutani and Shigeru Tanaka and akihiro tsuchimoto and Toshiaki Nakano and Yasuhiro Okabe and Yoichi Kakuta and Masayoshi Okumi and Kazuhiko Tsuruya and Masafumi Nakamura and Takanari Kitazono and Kazunari Tanabe",
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T1 - Development and validation of a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation

AU - Japan Academic Consortium of Kidney Transplantation (JACK) Investigators

AU - Matsukuma, Yuta

AU - Masutani, Kosuke

AU - Tanaka, Shigeru

AU - tsuchimoto, akihiro

AU - Nakano, Toshiaki

AU - Okabe, Yasuhiro

AU - Kakuta, Yoichi

AU - Okumi, Masayoshi

AU - Tsuruya, Kazuhiko

AU - Nakamura, Masafumi

AU - Kitazono, Takanari

AU - Tanabe, Kazunari

PY - 2019/11/1

Y1 - 2019/11/1

N2 - Background: Recently, living-donor kidney transplantation from marginal donors has been increasing. However, a simple prediction model for graft function including preoperative marginal factors is limited. Here, we developed and validated a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. Methods: We retrospectively investigated 343 patients who underwent living-donor kidney transplantation at Kyushu University Hospital (derivation cohort). Low graft function was defined as an estimated glomerular filtration rate of < 45 mL/min/1.73 m2 at 1 year. A prediction model was developed using a multivariable logistic regression model, and verified using data from 232 patients who underwent living-donor kidney transplantation at Tokyo Women's Medical University Hospital (validation cohort). Results: In the derivation cohort, 89 patients (25.9%) had low graft function at 1 year. Donor age, donor-estimated glomerular filtration rate, donor hypertension, and donor/recipient body weight ratio were selected as predictive factors. This model demonstrated modest discrimination (c-statistic = 0.77) and calibration (Hosmer–Lemeshow test, P = 0.83). Furthermore, this model demonstrated good discrimination (c-statistic = 0.76) and calibration (Hosmer–Lemeshow test, P = 0.54) in the validation cohort. Furthermore, donor age, donor-estimated glomerular filtration rate, and donor hypertension were strongly associated with glomerulosclerosis and atherosclerotic vascular changes in the “zero-time” biopsy. Conclusions: This model using four pre-operative variables will be a simple, but useful guide to estimate graft function at 1 year after kidney transplantation, especially in marginal donors, in the clinical setting.

AB - Background: Recently, living-donor kidney transplantation from marginal donors has been increasing. However, a simple prediction model for graft function including preoperative marginal factors is limited. Here, we developed and validated a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. Methods: We retrospectively investigated 343 patients who underwent living-donor kidney transplantation at Kyushu University Hospital (derivation cohort). Low graft function was defined as an estimated glomerular filtration rate of < 45 mL/min/1.73 m2 at 1 year. A prediction model was developed using a multivariable logistic regression model, and verified using data from 232 patients who underwent living-donor kidney transplantation at Tokyo Women's Medical University Hospital (validation cohort). Results: In the derivation cohort, 89 patients (25.9%) had low graft function at 1 year. Donor age, donor-estimated glomerular filtration rate, donor hypertension, and donor/recipient body weight ratio were selected as predictive factors. This model demonstrated modest discrimination (c-statistic = 0.77) and calibration (Hosmer–Lemeshow test, P = 0.83). Furthermore, this model demonstrated good discrimination (c-statistic = 0.76) and calibration (Hosmer–Lemeshow test, P = 0.54) in the validation cohort. Furthermore, donor age, donor-estimated glomerular filtration rate, and donor hypertension were strongly associated with glomerulosclerosis and atherosclerotic vascular changes in the “zero-time” biopsy. Conclusions: This model using four pre-operative variables will be a simple, but useful guide to estimate graft function at 1 year after kidney transplantation, especially in marginal donors, in the clinical setting.

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