Cargando…
Development and validation of a cardiovascular risk prediction model in type 1 diabetes
AIMS/HYPOTHESIS: We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes. METHODS: A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382639/ https://www.ncbi.nlm.nih.gov/pubmed/34106282 http://dx.doi.org/10.1007/s00125-021-05478-4 |
_version_ | 1783741575440891904 |
---|---|
author | McGurnaghan, Stuart J. McKeigue, Paul M. Read, Stephanie H. Franzen, Stefan Svensson, Ann-Marie Colombo, Marco Livingstone, Shona Farran, Bassam Caparrotta, Thomas M. Blackbourn, Luke A. K. Mellor, Joseph Thoma, Ioanna Sattar, Naveed Wild, Sarah H. Gudbjörnsdottir, Soffia Colhoun, Helen M. |
author_facet | McGurnaghan, Stuart J. McKeigue, Paul M. Read, Stephanie H. Franzen, Stefan Svensson, Ann-Marie Colombo, Marco Livingstone, Shona Farran, Bassam Caparrotta, Thomas M. Blackbourn, Luke A. K. Mellor, Joseph Thoma, Ioanna Sattar, Naveed Wild, Sarah H. Gudbjörnsdottir, Soffia Colhoun, Helen M. |
author_sort | McGurnaghan, Stuart J. |
collection | PubMed |
description | AIMS/HYPOTHESIS: We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes. METHODS: A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552 person-years of follow-up were ascertained using hospital admissions and death registers. A Poisson regression model of CVD was developed and then validated in the Swedish National Diabetes Register (n = 33,183). We compared the percentage with a high 10 year CVD risk (i.e., ≥10%) using the model with the percentage eligible for statins using current guidelines by age. RESULTS: The age-standardised rate of CVD per 100,000 person-years was 4070 and 3429 in men and women, respectively, with type 1 diabetes in Scotland, and 4014 and 3956 in men and women in Sweden. The final model was well calibrated (Hosmer–Lemeshow test p > 0.05) and included a further 22 terms over a base model of age, sex and diabetes duration (C statistic 0.82; 95% CI 0.81, 0.83). The model increased the base model C statistic from 0.66 to 0.80, from 0.60 to 0.75 and from 0.62 to 0.68 in those aged <40, 40–59 and ≥ 60 years, respectively (all p values <0.005). The model required minimal calibration in Sweden and had a C statistic of 0.85. Under current guidelines, >90% of those aged 20–39 years and 100% of those ≥40 years with type 1 diabetes were eligible for statins, but it was not until age 65 upwards that 100% had a modelled risk of CVD ≥10% in 10 years. CONCLUSIONS/INTERPRETATION: A prediction tool such as that developed here can provide individualised risk predictions. This 10 year CVD risk prediction tool could facilitate patient discussions regarding appropriate statin prescribing. Apart from 10 year risk, such discussions may also consider longer-term CVD risk, the potential for greater benefits from early vs later statin intervention, the potential impact on quality of life of an early CVD event and evidence on safety, all of which could influence treatment decisions, particularly in younger people with type 1 diabetes. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-021-05478-4. |
format | Online Article Text |
id | pubmed-8382639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-83826392021-09-09 Development and validation of a cardiovascular risk prediction model in type 1 diabetes McGurnaghan, Stuart J. McKeigue, Paul M. Read, Stephanie H. Franzen, Stefan Svensson, Ann-Marie Colombo, Marco Livingstone, Shona Farran, Bassam Caparrotta, Thomas M. Blackbourn, Luke A. K. Mellor, Joseph Thoma, Ioanna Sattar, Naveed Wild, Sarah H. Gudbjörnsdottir, Soffia Colhoun, Helen M. Diabetologia Article AIMS/HYPOTHESIS: We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes. METHODS: A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552 person-years of follow-up were ascertained using hospital admissions and death registers. A Poisson regression model of CVD was developed and then validated in the Swedish National Diabetes Register (n = 33,183). We compared the percentage with a high 10 year CVD risk (i.e., ≥10%) using the model with the percentage eligible for statins using current guidelines by age. RESULTS: The age-standardised rate of CVD per 100,000 person-years was 4070 and 3429 in men and women, respectively, with type 1 diabetes in Scotland, and 4014 and 3956 in men and women in Sweden. The final model was well calibrated (Hosmer–Lemeshow test p > 0.05) and included a further 22 terms over a base model of age, sex and diabetes duration (C statistic 0.82; 95% CI 0.81, 0.83). The model increased the base model C statistic from 0.66 to 0.80, from 0.60 to 0.75 and from 0.62 to 0.68 in those aged <40, 40–59 and ≥ 60 years, respectively (all p values <0.005). The model required minimal calibration in Sweden and had a C statistic of 0.85. Under current guidelines, >90% of those aged 20–39 years and 100% of those ≥40 years with type 1 diabetes were eligible for statins, but it was not until age 65 upwards that 100% had a modelled risk of CVD ≥10% in 10 years. CONCLUSIONS/INTERPRETATION: A prediction tool such as that developed here can provide individualised risk predictions. This 10 year CVD risk prediction tool could facilitate patient discussions regarding appropriate statin prescribing. Apart from 10 year risk, such discussions may also consider longer-term CVD risk, the potential for greater benefits from early vs later statin intervention, the potential impact on quality of life of an early CVD event and evidence on safety, all of which could influence treatment decisions, particularly in younger people with type 1 diabetes. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-021-05478-4. Springer Berlin Heidelberg 2021-06-09 2021 /pmc/articles/PMC8382639/ /pubmed/34106282 http://dx.doi.org/10.1007/s00125-021-05478-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article McGurnaghan, Stuart J. McKeigue, Paul M. Read, Stephanie H. Franzen, Stefan Svensson, Ann-Marie Colombo, Marco Livingstone, Shona Farran, Bassam Caparrotta, Thomas M. Blackbourn, Luke A. K. Mellor, Joseph Thoma, Ioanna Sattar, Naveed Wild, Sarah H. Gudbjörnsdottir, Soffia Colhoun, Helen M. Development and validation of a cardiovascular risk prediction model in type 1 diabetes |
title | Development and validation of a cardiovascular risk prediction model in type 1 diabetes |
title_full | Development and validation of a cardiovascular risk prediction model in type 1 diabetes |
title_fullStr | Development and validation of a cardiovascular risk prediction model in type 1 diabetes |
title_full_unstemmed | Development and validation of a cardiovascular risk prediction model in type 1 diabetes |
title_short | Development and validation of a cardiovascular risk prediction model in type 1 diabetes |
title_sort | development and validation of a cardiovascular risk prediction model in type 1 diabetes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382639/ https://www.ncbi.nlm.nih.gov/pubmed/34106282 http://dx.doi.org/10.1007/s00125-021-05478-4 |
work_keys_str_mv | AT mcgurnaghanstuartj developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT mckeiguepaulm developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT readstephanieh developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT franzenstefan developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT svenssonannmarie developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT colombomarco developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT livingstoneshona developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT farranbassam developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT caparrottathomasm developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT blackbournlukeak developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT mellorjoseph developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT thomaioanna developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT sattarnaveed developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT wildsarahh developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT gudbjornsdottirsoffia developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT colhounhelenm developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes AT developmentandvalidationofacardiovascularriskpredictionmodelintype1diabetes |