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Risk Prediction of Cardiovascular Disease in Type 2 Diabetes

Cederholm, Jan ; Eeg-Olofsson, Katarina ; Eliasson, Bjoern ; Zethelius, Bjoern ; Nilsson, Peter LU and Gudbjornsdottir, Soffia (2008) In Diabetes Care 31(10). p.2038-2043
Abstract
OBJECTIVE - Risk prediction models obtained in samples from the general population do mot perform well in type 2 diabetic patients. Recently, 5-year risk estimates were proposed as being more accurate than 10-year risk estimates. This study presents a diabetes-specific equation for estimation of the absolute 5-year risk of first incident fatal/nonfatal cardiovascular disease (CVD) in type 2 diabetic patients with the use of A1C and clinical characteristics. RESEARCH DESIGN AND METHODS - The study was based on 11,646 female and male patients, aged 18-70 years, from the Swedish National Diabetes Register with 1,482 first incident CVD events based on 58,342 person-years with mean follow-up) of 5.64 years. RESULTS - This risk equation... (More)
OBJECTIVE - Risk prediction models obtained in samples from the general population do mot perform well in type 2 diabetic patients. Recently, 5-year risk estimates were proposed as being more accurate than 10-year risk estimates. This study presents a diabetes-specific equation for estimation of the absolute 5-year risk of first incident fatal/nonfatal cardiovascular disease (CVD) in type 2 diabetic patients with the use of A1C and clinical characteristics. RESEARCH DESIGN AND METHODS - The study was based on 11,646 female and male patients, aged 18-70 years, from the Swedish National Diabetes Register with 1,482 first incident CVD events based on 58,342 person-years with mean follow-up) of 5.64 years. RESULTS - This risk equation incorporates A1C, as in the UK Prospective Diabetes Study risk engine, and several clinical characteristics: onset age of diabetes, diabetes duration, sex, BMI, smoking, systolic blood pressure, and antihypertensive and lipid-reducing drugs. All predictors included were associated with the Outcome (P < 0.0001, except for BMI P = 0.0016) with Cox regression analysis. Calibration was excellent when assessed by comparing observed and predicted risk. Discrimination was sufficient, with a receiver operator curve statistic of 0.70. Mean 5-year risk of CVD in all patients was 12.0 +/- 7.5%, whereas 54% of the patients had a 5-year risk >= 10%. CONCLUSIONS - This more simplified risk equation enables 5-year risk prediction of CVD based on easily available nonlaboratory predictors in clinical practice and A1C and was elaborated in a large observational study obtained from the normal patient population aged up to 70 years. (Less)
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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Diabetes Care
volume
31
issue
10
pages
2038 - 2043
publisher
American Diabetes Association
external identifiers
  • wos:000260043600023
  • scopus:56149114346
  • pmid:18591403
ISSN
1935-5548
DOI
10.2337/dc08-0662
language
English
LU publication?
yes
id
152637f6-699d-4f9c-8e09-6df3dd6b305d (old id 1285806)
date added to LUP
2016-04-01 14:42:51
date last changed
2025-04-04 15:26:39
@article{152637f6-699d-4f9c-8e09-6df3dd6b305d,
  abstract     = {{OBJECTIVE - Risk prediction models obtained in samples from the general population do mot perform well in type 2 diabetic patients. Recently, 5-year risk estimates were proposed as being more accurate than 10-year risk estimates. This study presents a diabetes-specific equation for estimation of the absolute 5-year risk of first incident fatal/nonfatal cardiovascular disease (CVD) in type 2 diabetic patients with the use of A1C and clinical characteristics. RESEARCH DESIGN AND METHODS - The study was based on 11,646 female and male patients, aged 18-70 years, from the Swedish National Diabetes Register with 1,482 first incident CVD events based on 58,342 person-years with mean follow-up) of 5.64 years. RESULTS - This risk equation incorporates A1C, as in the UK Prospective Diabetes Study risk engine, and several clinical characteristics: onset age of diabetes, diabetes duration, sex, BMI, smoking, systolic blood pressure, and antihypertensive and lipid-reducing drugs. All predictors included were associated with the Outcome (P &lt; 0.0001, except for BMI P = 0.0016) with Cox regression analysis. Calibration was excellent when assessed by comparing observed and predicted risk. Discrimination was sufficient, with a receiver operator curve statistic of 0.70. Mean 5-year risk of CVD in all patients was 12.0 +/- 7.5%, whereas 54% of the patients had a 5-year risk &gt;= 10%. CONCLUSIONS - This more simplified risk equation enables 5-year risk prediction of CVD based on easily available nonlaboratory predictors in clinical practice and A1C and was elaborated in a large observational study obtained from the normal patient population aged up to 70 years.}},
  author       = {{Cederholm, Jan and Eeg-Olofsson, Katarina and Eliasson, Bjoern and Zethelius, Bjoern and Nilsson, Peter and Gudbjornsdottir, Soffia}},
  issn         = {{1935-5548}},
  language     = {{eng}},
  number       = {{10}},
  pages        = {{2038--2043}},
  publisher    = {{American Diabetes Association}},
  series       = {{Diabetes Care}},
  title        = {{Risk Prediction of Cardiovascular Disease in Type 2 Diabetes}},
  url          = {{http://dx.doi.org/10.2337/dc08-0662}},
  doi          = {{10.2337/dc08-0662}},
  volume       = {{31}},
  year         = {{2008}},
}