Effect of trajectories of glycemic control on mortality in type 2 diabetes: a semiparametric joint modeling approach. Am J Epidemiol 2010 May 15;171(10):1090-8
Date
04/30/2010Pubmed ID
20427326Pubmed Central ID
PMC2877473DOI
10.1093/aje/kwq070Scopus ID
2-s2.0-77952326968 (requires institutional sign-in at Scopus site) 26 CitationsAbstract
Data on the effect of trajectories in long-term glycemia and all-cause mortality are lacking. The authors studied the effect of trajectories in long-term glycemic control on all-cause mortality in patients with type 2 diabetes. A cohort of 8,812 veterans with type 2 diabetes was assembled retrospectively using Veterans Affairs registry data. For each veteran in the cohort, a 3-month person-period data set was created from April 1997 to May 2006. The average duration of follow-up was 4.5 years. The overall mortality rate was 15.3%. Using a novel approach for joint modeling of time to death and longitudinal measurements of hemoglobin A1c (HbA1c) level, after adjustment for all significant baseline covariates, baseline HbA1c was found to be significantly associated with mortality (hazard ratio = 2.1, 95% confidence interval: 1.3, 3.6) (i.e., a 1% increase in baseline HbA1c level was associated with an average 2-fold increase in mortality risk). Similarly, the slope of the HbA1c trajectory was marginally significantly associated with mortality (hazard ratio = 7.3, 95% confidence interval: 0.9, 57.1) after adjustment for baseline covariates (i.e., a 1% increase in HbA1c level over 3 months was associated with a 22% increase in mortality risk). The authors conclude that a positive trajectory of long-term hyperglycemia is associated with increased mortality.
Author List
Gebregziabher M, Egede LE, Lynch CP, Echols C, Zhao YAuthor
Leonard E. Egede MD Center Director, Chief, Professor in the Medicine department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AgedAlgorithms
Cohort Studies
Confidence Intervals
Diabetes Mellitus, Type 2
Female
Humans
Kaplan-Meier Estimate
Male
Middle Aged
Models, Statistical
Proportional Hazards Models
Regression Analysis
Retrospective Studies
Risk Factors
South Carolina
Time Factors
Veterans
