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Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule
AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Pros...
Autores principales: | , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Springer-Verlag
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2797626/ https://www.ncbi.nlm.nih.gov/pubmed/19908023 http://dx.doi.org/10.1007/s00125-009-1585-3 |
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author | Vergouwe, Y. Soedamah-Muthu, S. S. Zgibor, J. Chaturvedi, N. Forsblom, C. Snell-Bergeon, J. K. Maahs, D. M. Groop, P.-H. Rewers, M. Orchard, T. J. Fuller, J. H. Moons, K. G. M. |
author_facet | Vergouwe, Y. Soedamah-Muthu, S. S. Zgibor, J. Chaturvedi, N. Forsblom, C. Snell-Bergeon, J. K. Maahs, D. M. Groop, P.-H. Rewers, M. Orchard, T. J. Fuller, J. H. Moons, K. G. M. |
author_sort | Vergouwe, Y. |
collection | PubMed |
description | AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Prospective Complications Study (n = 1115) were used to develop the prediction rule (development set). Multivariable logistic regression analysis was used to assess the association between potential predictors and progression to microalbuminuria within 7 years. The performance of the prediction rule was assessed with calibration and discrimination (concordance statistic [c-statistic]) measures. The rule was validated in three other diabetes studies (Pittsburgh Epidemiology of Diabetes Complications [EDC] study, Finnish Diabetic Nephropathy [FinnDiane] study and Coronary Artery Calcification in Type 1 Diabetes [CACTI] study). RESULTS: Of patients in the development set, 13% were microalbuminuric after 7 years. Glycosylated haemoglobin, AER, WHR, BMI and ever smoking were found to be the most important predictors. A high-risk group (n = 87 [8%]) was identified with a risk of progression to microalbuminuria of 32%. Predictions showed reasonable discriminative ability, with c-statistic of 0.71. The rule showed good calibration and discrimination in EDC, FinnDiane and CACTI (c-statistic 0.71, 0.79 and 0.79, respectively). CONCLUSIONS/INTERPRETATION: We developed and validated a clinical prediction rule that uses relatively easily obtainable patient characteristics to predict microalbuminuria in patients with type 1 diabetes. This rule can help clinicians to decide on more frequent check-ups for patients at high risk of microalbuminuria in order to prevent long-term chronic complications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-009-1585-3) contains a list of the members of the EURODIAB, EDC, FinnDiane and CACTI Study Groups and other contributors to the study, which is available to authorised users. |
format | Text |
id | pubmed-2797626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-27976262009-12-29 Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule Vergouwe, Y. Soedamah-Muthu, S. S. Zgibor, J. Chaturvedi, N. Forsblom, C. Snell-Bergeon, J. K. Maahs, D. M. Groop, P.-H. Rewers, M. Orchard, T. J. Fuller, J. H. Moons, K. G. M. Diabetologia Article AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Prospective Complications Study (n = 1115) were used to develop the prediction rule (development set). Multivariable logistic regression analysis was used to assess the association between potential predictors and progression to microalbuminuria within 7 years. The performance of the prediction rule was assessed with calibration and discrimination (concordance statistic [c-statistic]) measures. The rule was validated in three other diabetes studies (Pittsburgh Epidemiology of Diabetes Complications [EDC] study, Finnish Diabetic Nephropathy [FinnDiane] study and Coronary Artery Calcification in Type 1 Diabetes [CACTI] study). RESULTS: Of patients in the development set, 13% were microalbuminuric after 7 years. Glycosylated haemoglobin, AER, WHR, BMI and ever smoking were found to be the most important predictors. A high-risk group (n = 87 [8%]) was identified with a risk of progression to microalbuminuria of 32%. Predictions showed reasonable discriminative ability, with c-statistic of 0.71. The rule showed good calibration and discrimination in EDC, FinnDiane and CACTI (c-statistic 0.71, 0.79 and 0.79, respectively). CONCLUSIONS/INTERPRETATION: We developed and validated a clinical prediction rule that uses relatively easily obtainable patient characteristics to predict microalbuminuria in patients with type 1 diabetes. This rule can help clinicians to decide on more frequent check-ups for patients at high risk of microalbuminuria in order to prevent long-term chronic complications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-009-1585-3) contains a list of the members of the EURODIAB, EDC, FinnDiane and CACTI Study Groups and other contributors to the study, which is available to authorised users. Springer-Verlag 2009-11-04 2010 /pmc/articles/PMC2797626/ /pubmed/19908023 http://dx.doi.org/10.1007/s00125-009-1585-3 Text en © The Author(s) 2009 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Article Vergouwe, Y. Soedamah-Muthu, S. S. Zgibor, J. Chaturvedi, N. Forsblom, C. Snell-Bergeon, J. K. Maahs, D. M. Groop, P.-H. Rewers, M. Orchard, T. J. Fuller, J. H. Moons, K. G. M. Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule |
title | Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule |
title_full | Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule |
title_fullStr | Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule |
title_full_unstemmed | Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule |
title_short | Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule |
title_sort | progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2797626/ https://www.ncbi.nlm.nih.gov/pubmed/19908023 http://dx.doi.org/10.1007/s00125-009-1585-3 |
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