Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data.
OBJECTIVE: Predicting the risk of future events is an essential part of health economic simulation models. In pursuit of this goal, the current study aims to predict the risk of developing first and second acute myocardial infarction, heart failure, non-acute ischaemic heart disease, and stroke afte...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2013-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3650043?pdf=render |
id |
doaj-0d335ab6a05046768b4574311752467c |
---|---|
record_format |
Article |
spelling |
doaj-0d335ab6a05046768b4574311752467c2020-11-25T01:19:17ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0185e6265010.1371/journal.pone.0062650Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data.Aliasghar Ahmad KiadaliriUlf-G GerdthamPeter NilssonBjörn EliassonSoffia GudbjörnsdottirKatarina Steen CarlssonOBJECTIVE: Predicting the risk of future events is an essential part of health economic simulation models. In pursuit of this goal, the current study aims to predict the risk of developing first and second acute myocardial infarction, heart failure, non-acute ischaemic heart disease, and stroke after diagnosis in patients with type 2 diabetes, using data from the Swedish National Diabetes Register. MATERIAL AND METHODS: Register data on 29,034 patients with type 2 diabetes were analysed over five years of follow up (baseline 2003). To develop and validate the risk equations, the sample was randomly divided into training (75%) and test (25%) subsamples. The Weibull proportional hazard model was used to estimate the coefficients of the risk equations, and these were validated in both the training and the test samples. RESULTS: In total, 4,547 first and 2,418 second events were observed during the five years of follow up. Experiencing a first event substantially elevated the risk of subsequent events. There were heterogeneities in the effects of covariates within as well as between events; for example, while for females the hazard ratio of having a first acute myocardial infarction was 0.79 (0.70-0.90), the hazard ratio of a second was 1.21 (0.98-1.48). The hazards of second events decreased as the time since first events elapsed. The equations showed adequate calibration and discrimination (C statistics range: 0.70-0.84 in test samples). CONCLUSION: The accuracy of health economic simulation models of type 2 diabetes can be improved by ensuring that they account for the heterogeneous effects of covariates on the risk of first and second cardiovascular events. Thus it is important to extend such models by including risk equations for second cardiovascular events.http://europepmc.org/articles/PMC3650043?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Aliasghar Ahmad Kiadaliri Ulf-G Gerdtham Peter Nilsson Björn Eliasson Soffia Gudbjörnsdottir Katarina Steen Carlsson |
spellingShingle |
Aliasghar Ahmad Kiadaliri Ulf-G Gerdtham Peter Nilsson Björn Eliasson Soffia Gudbjörnsdottir Katarina Steen Carlsson Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data. PLoS ONE |
author_facet |
Aliasghar Ahmad Kiadaliri Ulf-G Gerdtham Peter Nilsson Björn Eliasson Soffia Gudbjörnsdottir Katarina Steen Carlsson |
author_sort |
Aliasghar Ahmad Kiadaliri |
title |
Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data. |
title_short |
Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data. |
title_full |
Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data. |
title_fullStr |
Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data. |
title_full_unstemmed |
Towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from Swedish register data. |
title_sort |
towards renewed health economic simulation of type 2 diabetes: risk equations for first and second cardiovascular events from swedish register data. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2013-01-01 |
description |
OBJECTIVE: Predicting the risk of future events is an essential part of health economic simulation models. In pursuit of this goal, the current study aims to predict the risk of developing first and second acute myocardial infarction, heart failure, non-acute ischaemic heart disease, and stroke after diagnosis in patients with type 2 diabetes, using data from the Swedish National Diabetes Register. MATERIAL AND METHODS: Register data on 29,034 patients with type 2 diabetes were analysed over five years of follow up (baseline 2003). To develop and validate the risk equations, the sample was randomly divided into training (75%) and test (25%) subsamples. The Weibull proportional hazard model was used to estimate the coefficients of the risk equations, and these were validated in both the training and the test samples. RESULTS: In total, 4,547 first and 2,418 second events were observed during the five years of follow up. Experiencing a first event substantially elevated the risk of subsequent events. There were heterogeneities in the effects of covariates within as well as between events; for example, while for females the hazard ratio of having a first acute myocardial infarction was 0.79 (0.70-0.90), the hazard ratio of a second was 1.21 (0.98-1.48). The hazards of second events decreased as the time since first events elapsed. The equations showed adequate calibration and discrimination (C statistics range: 0.70-0.84 in test samples). CONCLUSION: The accuracy of health economic simulation models of type 2 diabetes can be improved by ensuring that they account for the heterogeneous effects of covariates on the risk of first and second cardiovascular events. Thus it is important to extend such models by including risk equations for second cardiovascular events. |
url |
http://europepmc.org/articles/PMC3650043?pdf=render |
work_keys_str_mv |
AT aliasgharahmadkiadaliri towardsrenewedhealtheconomicsimulationoftype2diabetesriskequationsforfirstandsecondcardiovasculareventsfromswedishregisterdata AT ulfggerdtham towardsrenewedhealtheconomicsimulationoftype2diabetesriskequationsforfirstandsecondcardiovasculareventsfromswedishregisterdata AT peternilsson towardsrenewedhealtheconomicsimulationoftype2diabetesriskequationsforfirstandsecondcardiovasculareventsfromswedishregisterdata AT bjorneliasson towardsrenewedhealtheconomicsimulationoftype2diabetesriskequationsforfirstandsecondcardiovasculareventsfromswedishregisterdata AT soffiagudbjornsdottir towardsrenewedhealtheconomicsimulationoftype2diabetesriskequationsforfirstandsecondcardiovasculareventsfromswedishregisterdata AT katarinasteencarlsson towardsrenewedhealtheconomicsimulationoftype2diabetesriskequationsforfirstandsecondcardiovasculareventsfromswedishregisterdata |
_version_ |
1725139107538010112 |