Literature DB >> 18332288

Development and validation of an all-cause mortality risk score in type 2 diabetes.

Xilin Yang, Wing Yee So, Peter C Y Tong, Ronald C W Ma, Alice P S Kong, Christopher W K Lam, Chung Shun Ho, Clive S Cockram, Gary T C Ko, Chun-Chung Chow, Vivian C W Wong, Juliana C N Chan.   

Abstract

BACKGROUND: Diabetes reduces life expectancy by 10 to 12 years, but whether death can be predicted in type 2 diabetes mellitus remains uncertain.
METHODS: A prospective cohort of 7583 type 2 diabetic patients enrolled since 1995 were censored on July 30, 2005, or after 6 years of follow-up, whichever came first. A restricted cubic spline model was used to check data linearity and to develop linear-transforming formulas. Data were randomly assigned to a training data set and to a test data set. A Cox model was used to develop risk scores in the test data set. Calibration and discrimination were assessed in the test data set.
RESULTS: A total of 619 patients died during a median follow-up period of 5.51 years, resulting in a mortality rate of 18.69 per 1000 person-years. Age, sex, peripheral arterial disease, cancer history, insulin use, blood hemoglobin levels, linear-transformed body mass index, random spot urinary albumin-creatinine ratio, and estimated glomerular filtration rate at enrollment were predictors of all-cause death. A risk score for all-cause mortality was developed using these predictors. The predicted and observed death rates in the test data set were similar (P > .70). The area under the receiver operating characteristic curve was 0.85 for 5 years of follow-up. Using the risk score in ranking cause-specific deaths, the area under the receiver operating characteristic curve was 0.95 for genitourinary death, 0.85 for circulatory death, 0.85 for respiratory death, and 0.71 for neoplasm death.
CONCLUSIONS: Death in type 2 diabetes mellitus can be predicted using a risk score consisting of commonly measured clinical and biochemical variables. Further validation is needed before clinical use.

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Year:  2008        PMID: 18332288     DOI: 10.1001/archinte.168.5.451

Source DB:  PubMed          Journal:  Arch Intern Med        ISSN: 0003-9926


  43 in total

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4.  Estimation of Mortality Risk in Type 2 Diabetic Patients (ENFORCE): An Inexpensive and Parsimonious Prediction Model.

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5.  Low LDL cholesterol, albuminuria, and statins for the risk of cancer in type 2 diabetes: the Hong Kong diabetes registry.

Authors:  Xilin Yang; Wing Yee So; Ronald C W Ma; Gary T C Ko; Alice P S Kong; Hailu Zhao; Andrea O Y Luk; Christopher W K Lam; Chung Shun Ho; Peter C Y Tong; Juliana C N Chan
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6.  From design to implementation--the Joint Asia Diabetes Evaluation (JADE) program: a descriptive report of an electronic web-based diabetes management program.

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7.  Associations of hyperglycemia and insulin usage with the risk of cancer in type 2 diabetes: the Hong Kong diabetes registry.

Authors:  Xilin Yang; Gary T C Ko; Wing Yee So; Ronald C W Ma; Linda W L Yu; Alice P S Kong; Hailu Zhao; Chun-Chung Chow; Peter C Y Tong; Juliana C N Chan
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8.  Effect of interactions between C peptide levels and insulin treatment on clinical outcomes among patients with type 2 diabetes mellitus.

Authors:  Gary T C Ko; Wing-Yee So; Peter C Tong; Wing-Bun Chan; Xilin Yang; Ronald C Ma; Alice P Kong; Risa Ozaki; Chun-Yip Yeung; Chun-Chung Chow; Juliana C Chan
Journal:  CMAJ       Date:  2009-04-28       Impact factor: 8.262

9.  Phenotype-genotype interactions on renal function in type 2 diabetes: an analysis using structural equation modelling.

Authors:  X Y Song; S Y Lee; R C W Ma; W Y So; J H Cai; C Tam; V Lam; W Ying; M C Y Ng; J C N Chan
Journal:  Diabetologia       Date:  2009-05-29       Impact factor: 10.122

10.  Additive interaction between the renin-angiotensin system and lipid metabolism for cancer in type 2 diabetes.

Authors:  Xilin Yang; Hailu Zhao; Yi Sui; Ronald C W Ma; Wing Yee So; Gary T C Ko; Alice P S Kong; Risa Ozaki; Chun Yip Yeung; Gang Xu; Peter C Y Tong; Juliana C N Chan
Journal:  Diabetes       Date:  2009-04-28       Impact factor: 9.461

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