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Title: The First Asian Kidney Transplantation Prediction Models for Long-term Patient and Allograft Survival
Authors: Suwasin Udomkarnjananun
Natavudh Townamchai
Stephen J. Kerr
Adis Tasanarong
Kajohnsak Noppakun
Adisorn Lumpaopong
Surazee Prommool
Thanom Supaporn
Yingyos Avihingsanon
Kearkiat Praditpornsilpa
Somchai Eiam-Ong
Keywords: Medicine
Issue Date: 1-Jan-2020
Abstract: © 2019 Wolters Kluwer Health, Inc. All rights reserved. Background. Several kidney transplantation (KT) prediction models for patient and graft outcomes have been developed based on Caucasian populations. However, KT in Asian countries differs due to patient characteristics and practices. To date, there has been no equation developed for predicting outcomes among Asian KT recipients. Methods. We developed equations for predicting 5- A nd 10-year patient survival (PS) and death-censored graft survival (DCGS) based on 6662 patients in the Thai Transplant Registry. The cohort was divided into training and validation data sets. We identified factors significantly associated with outcomes by Cox regression. In the validation data set, we also compared our models with another model based on KT in the United States. Results. Variables included for developing the DCGS and PS models were recipient and donor age, background kidney disease, dialysis vintage, donor hepatitis C virus status, cardiovascular diseases, panel reactive antibody, donor types, donor creatinine, ischemic time, and immunosuppression regimens. The C statistics of our model in the validation data set were 0.69 (0.66-0.71) and 0.64 (0.59-0.68) for DCGS and PS. Our model performed better when compared with a model based on US patients. Compared with tacrolimus, KT recipients aged ≤44 years receiving cyclosporine A had a higher risk of graft loss (adjusted hazard ratio = 1.26; P = 0.046). The risk of death was higher in recipients aged >44 years and taking cyclosporine A (adjusted hazard ratio = 1.44; P = 0.011). Conclusions. Our prediction model is the first based on an Asian population, can be used immediately after transplantation. The model can be accessed at
ISSN: 00411337
Appears in Collections:CMUL: Journal Articles

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