title: Using hemoglobin A1C as a predicting model for time interval from pre-diabetes progressing to diabetes.
abstract: OBJECTIVE
  The early identification of subjects at high risk for diabetes is essential, thus, random rather than fasting plasma glucose is more useful. We aim to evaluate the time interval between pre-diabetes to diabetes with anti-diabetic drugs by using HbA1C as a diagnostic tool, and predicting it using a mathematic model.
  
  
  METHODS
  We used the Taipei Medical University Affiliated Hospital Patient Profile Database (AHPPD) from January-2007 to June-2011. The patients who progressed and were prescribed anti-diabetic drugs were selected from AHPPD. The mathematical model used to predict the time interval of HbA1C value ranged from 5.7% to 6.5% for diabetes progression.
  
  
  RESULTS
  We predicted an average overall time interval for all participants in between 5.7% to 6.5% during a total of 907 days (standard error, 103 days). For each group found among 5.7% to 6.5% we determined 1169.3 days for the low risk group (i.e. 3.2 years), 1080.5 days (i.e. 2.96 years) for the increased risk group and 729.4 days (i.e. 1.99 years) for the diabetes group. This indicates the patients will take an average of 2.49 years to reach 6.5%.
  
  
  CONCLUSIONS
  This prediction model is very useful to help prioritize the diagnosis at an early stage for targeting individuals with risk of diabetes. Using patients' HbA1C before anti-diabetes drugs are used we predicted the time interval from pre-diabetes progression to diabetes is 2.49 years without any influence of age and gender. Additional studies are needed to support this model for a long term prediction.
authors.affiliation: Division of Endocrinology and Metabolism, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan.
authors.forename: Chen-Ling
authors.initials: CL
authors.lastname: Huang
authors.affiliation: Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
authors.forename: Usman
authors.initials: U
authors.lastname: Iqbal
authors.affiliation: Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
authors.forename: Phung-Anh
authors.initials: PA
authors.lastname: Nguyen
authors.affiliation: School of Health Care Administration, Taipei Medical University, Taipei, Taiwan.
authors.forename: Zih-Fang
authors.initials: ZF
authors.lastname: Chen
authors.affiliation: Translational Medicine Program, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Clinciu
authors.affiliation: School of Health Care Administration, Taipei Medical University, Taipei, Taiwan.
authors.forename: Yi-Hsin Elsa
authors.initials: YH
authors.lastname: Hsu
authors.affiliation: Department of Nuclear Medicine, Taipei Medical University Hospital, Taipei, Taiwan.
authors.forename: Chung-Huei
authors.initials: CH
authors.lastname: Hsu
authors.affiliation: School of Health Care Administration, Taipei Medical University, Taipei, Taiwan.
authors.forename: Wen-Shan
authors.initials: WS
authors.lastname: Jian
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001786:Blood Glucose; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000175:diagnosis*; D018450:Disease Progression; D005260:Female; D006442:Glycated Hemoglobin; D006801:Humans; D008297:Male; D008875:Middle Aged; D011236:Prediabetic State / Q000097:blood*; D011379:Prognosis; D012307:Risk Factors; D013997:Time Factors
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin
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