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

研究成果: ジャーナルへの寄稿記事

抄録

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.

元の言語英語
ページ(範囲)1331-1340
ページ数10
ジャーナルClinical and Experimental Nephrology
23
発行部数11
DOI
出版物ステータス出版済み - 11 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)

これを引用

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.

:: Clinical and Experimental Nephrology, 巻 23, 番号 11, 01.11.2019, p. 1331-1340.

研究成果: ジャーナルへの寄稿記事

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. :: Clinical and Experimental Nephrology. 2019 ; 巻 23, 番号 11. pp. 1331-1340.
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title = "Development and validation of a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation",
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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U2 - 10.1007/s10157-019-01774-x

DO - 10.1007/s10157-019-01774-x

M3 - Article

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JO - Clinical and Experimental Nephrology

JF - Clinical and Experimental Nephrology

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