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Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China

PURPOSE: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide. Risk assessment provides information about patient prognosis, contributing to the risk stratification of patients and the rational allocation of medical resources. We aimed to develop a model for indivi...

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Autores principales: Gao, Yue-Ming, Feng, Song-Tao, Yang, Yang, Li, Zuo-Lin, Wen, Yi, Wang, Bin, Lv, Lin-Li, Xing, Guo-Lan, Liu, Bi-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933626/
https://www.ncbi.nlm.nih.gov/pubmed/35313680
http://dx.doi.org/10.2147/DMSO.S352154
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author Gao, Yue-Ming
Feng, Song-Tao
Yang, Yang
Li, Zuo-Lin
Wen, Yi
Wang, Bin
Lv, Lin-Li
Xing, Guo-Lan
Liu, Bi-Cheng
author_facet Gao, Yue-Ming
Feng, Song-Tao
Yang, Yang
Li, Zuo-Lin
Wen, Yi
Wang, Bin
Lv, Lin-Li
Xing, Guo-Lan
Liu, Bi-Cheng
author_sort Gao, Yue-Ming
collection PubMed
description PURPOSE: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide. Risk assessment provides information about patient prognosis, contributing to the risk stratification of patients and the rational allocation of medical resources. We aimed to develop a model for individualized prediction of renal function decline in patients with type 2 DKD (T2DKD). PATIENTS AND METHODS: In a retrospective observational study, we followed 307 T2DKD patients and evaluated the determinants of 1) risk of doubling in serum creatinine (Scr), 2) risk of eGFR<15 mL/min/1.73m(2) using potential risk factors at baseline. A prediction model represented by a nomogram and a risk table was developed using Cox regression and externally validated in another cohort with 206 T2DKD patients. The discrimination and calibration of the prediction model were evaluated by the concordance index (C-index) and calibration curve, respectively. RESULTS: Four predictors were selected to establish the final model: Scr, urinary albumin/creatinine ratio, plasma albumin, and insulin treatment. The nomogram achieved satisfactory prediction performance, with a C-index of 0.791 [95% confidence interval (CI) 0.762–0.820] in the derivation cohort and 0.793 (95% CI 0.746–0.840) in the external validation cohort. Then, all predictors were scored according to their weightings. A risk table with the highest score of 11.5 was developed. The C-index of the risk table was 0.764 (95% CI: 0.731–0.797), which was similar to the external validation cohort (0.763; 95% CI: 0.714–0.812). Additionally, the patients were divided into two groups based on the risk table, and significant differences in the probability of outcome events were observed between the high-risk (score >2) and low-risk (score ≤2) groups in the derivation and external validation cohorts (P < 0.001). CONCLUSION: The nomogram and the risk table using readily available clinical parameters could be new tools for bedside prediction of renal function decline in T2DKD patients.
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spelling pubmed-89336262022-03-20 Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China Gao, Yue-Ming Feng, Song-Tao Yang, Yang Li, Zuo-Lin Wen, Yi Wang, Bin Lv, Lin-Li Xing, Guo-Lan Liu, Bi-Cheng Diabetes Metab Syndr Obes Original Research PURPOSE: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide. Risk assessment provides information about patient prognosis, contributing to the risk stratification of patients and the rational allocation of medical resources. We aimed to develop a model for individualized prediction of renal function decline in patients with type 2 DKD (T2DKD). PATIENTS AND METHODS: In a retrospective observational study, we followed 307 T2DKD patients and evaluated the determinants of 1) risk of doubling in serum creatinine (Scr), 2) risk of eGFR<15 mL/min/1.73m(2) using potential risk factors at baseline. A prediction model represented by a nomogram and a risk table was developed using Cox regression and externally validated in another cohort with 206 T2DKD patients. The discrimination and calibration of the prediction model were evaluated by the concordance index (C-index) and calibration curve, respectively. RESULTS: Four predictors were selected to establish the final model: Scr, urinary albumin/creatinine ratio, plasma albumin, and insulin treatment. The nomogram achieved satisfactory prediction performance, with a C-index of 0.791 [95% confidence interval (CI) 0.762–0.820] in the derivation cohort and 0.793 (95% CI 0.746–0.840) in the external validation cohort. Then, all predictors were scored according to their weightings. A risk table with the highest score of 11.5 was developed. The C-index of the risk table was 0.764 (95% CI: 0.731–0.797), which was similar to the external validation cohort (0.763; 95% CI: 0.714–0.812). Additionally, the patients were divided into two groups based on the risk table, and significant differences in the probability of outcome events were observed between the high-risk (score >2) and low-risk (score ≤2) groups in the derivation and external validation cohorts (P < 0.001). CONCLUSION: The nomogram and the risk table using readily available clinical parameters could be new tools for bedside prediction of renal function decline in T2DKD patients. Dove 2022-03-14 /pmc/articles/PMC8933626/ /pubmed/35313680 http://dx.doi.org/10.2147/DMSO.S352154 Text en © 2022 Gao et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Gao, Yue-Ming
Feng, Song-Tao
Yang, Yang
Li, Zuo-Lin
Wen, Yi
Wang, Bin
Lv, Lin-Li
Xing, Guo-Lan
Liu, Bi-Cheng
Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China
title Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China
title_full Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China
title_fullStr Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China
title_full_unstemmed Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China
title_short Development and External Validation of a Nomogram and a Risk Table for Prediction of Type 2 Diabetic Kidney Disease Progression Based on a Retrospective Cohort Study in China
title_sort development and external validation of a nomogram and a risk table for prediction of type 2 diabetic kidney disease progression based on a retrospective cohort study in china
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933626/
https://www.ncbi.nlm.nih.gov/pubmed/35313680
http://dx.doi.org/10.2147/DMSO.S352154
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