title: Predictive Power for Type 2 Diabetes Mellitus using Dynamic Change of Metabolic Syndrome, Dynamic Change of Fasting Plasma Glucose, Metabolic Syndrome and Fasting Plasma Glucose.
abstract: BACKGROUND
  The aim was to compare the predictive power for Type 2 Diabetes mellitus (T2DM) using dynamic change (Difference) of metabolic syndrome (MS), Difference of fasting plasma glucose (FPG), baseline MS and FPG in cohort study.
  
  
  METHODS
  Overall, 3461 subjects were recruited from Prevention of Multiple Metabolic disorders and MS in Jiangsu of China Study with 3.8 years follow-up. Cox proportional-hazards regression and receiver operating characteristic were used to evaluate the predictive power for T2DM using Difference MS, Difference of FPG, baseline MS and FPG.
  
  
  RESULTS
  Adjusted relative risk (aRR 5.24, 95% CI 4.28-6.42) of Difference of FPG to T2DM was highest than other. Difference of FPG owns the largest AUC (0.89, P<0.05), the highest sensitivity (96.25%) and specificity (80.49%) demonstrating that Difference of FPG can provide strongest predictive information to T2DM, Difference of MS comes second. Between FPG related tools, sensitivity of Difference of FPG almost was twice than baseline FPG(96.25% vs. 54.38%) suggesting that using baseline FPG would missed found 46% T2DM patients. Among MS related indicators, sensitivity of Difference of MS almost was twice than baseline MS (sensitivity 66.25% vs. 39.38%) suggesting that using baseline would missed found 61% T2DM patients.
  
  
  CONCLUSIONS
  Dynamic change of FPG had the highest predictive power for T2DM in Chinese than Dynamic Change of MS, baseline MS and FPG.
authors.affiliation: 1. School of Public Health, Medical College of Soochow University , SuZhou, China ; 2. The Center for Disease Control and Prevention of Suzhou Industry Park , SuZhou, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Zhou
authors.affiliation: 3. Center for Disease Control of Xiangcheng District in Suzhou City, Suzhou , Jiangsu, China.
authors.forename: Chen
authors.initials: C
authors.lastname: Yang
authors.affiliation: 1. School of Public Health, Medical College of Soochow University , SuZhou, China.
authors.forename: Chen
authors.initials: C
authors.lastname: Dong
authors.affiliation: 1. School of Public Health, Medical College of Soochow University , SuZhou, China.
authors.forename: Zhirong
authors.initials: Z
authors.lastname: Guo
authors.affiliation: 4. Health Bureau of JiangSu Province , NanJing, China.
authors.forename: Xiaoshu
authors.initials: X
authors.lastname: Hu
authors.affiliation: 1. School of Public Health, Medical College of Soochow University , SuZhou, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Xu
authors.affiliation: 5. Changshu Center for Disease Control and Prevention , ChangShu, China.
authors.forename: Zhengyuan
authors.initials: Z
authors.lastname: Zhou
keywords: Cohort study; Dynamic change; Metabolic syndrome (MS); Type 2 diabetes (T2DM)