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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2022
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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. |
format | Online Article Text |
id | pubmed-8933626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Dove |
record_format | MEDLINE/PubMed |
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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