title: Decision tree-based modelling for identification of potential interactions between type 2 diabetes risk factors: a decade follow-up in a Middle East prospective cohort study.
abstract: The current study was undertaken for use of the decision tree (DT) method for development of different prediction models for incidence of type 2 diabetes (T2D) and for exploring interactions between predictor variables in those models.
  
  
  
  Prospective cohort study.
  
  
  
  Tehran Lipid and Glucose Study (TLGS).
  
  
  
  A total of 6647 participants (43.4% men) aged >20 years, without T2D at baselines ((1999-2001) and (2002-2005)), were followed until 2012. 2 series of models (with and without 2-hour postchallenge plasma glucose (2h-PCPG)) were developed using 3 types of DT algorithms. The performances of the models were assessed using sensitivity, specificity, area under the ROC curve (AUC), geometric mean (G-Mean) and F-Measure.
  
  
  
  T2D was primary outcome which defined if fasting plasma glucose (FPG) was ≥7 mmol/L or if the 2h-PCPG was ≥11.1 mmol/L or if the participant was taking antidiabetic medication.
  
  
  
  During a median follow-up of 9.5 years, 729 new cases of T2D were identified. The Quick Unbiased Efficient Statistical Tree (QUEST) algorithm had the highest sensitivity and G-Mean among all the models for men and women. The models that included 2h-PCPG had sensitivity and G-Mean of (78% and 0.75%) and (78% and 0.78%) for men and women, respectively. Both models achieved good discrimination power with AUC above 0.78. FPG, 2h-PCPG, waist-to-height ratio (WHtR) and mean arterial blood pressure (MAP) were the most important factors to incidence of T2D in both genders. Among men, those with an FPG≤4.9 mmol/L and 2h-PCPG≤7.7 mmol/L had the lowest risk, and those with an FPG>5.3 mmol/L and 2h-PCPG>4.4 mmol/L had the highest risk for T2D incidence. In women, those with an FPG≤5.2 mmol/L and WHtR≤0.55 had the lowest risk, and those with an FPG>5.2 mmol/L and WHtR>0.56 had the highest risk for T2D incidence.
  
  
  
  Our study emphasises the utility of DT for exploring interactions between predictor variables.
authors.affiliation: Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Science, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
authors.forename: Azra
authors.initials: A
authors.lastname: Ramezankhani
authors.affiliation: Industrial Engineering Department, Amirkabir University of Technology, Tehran, Iran.|Department of Industrial Engineering, Birjand University of Technology, Birjand, Iran.
authors.forename: Esmaeil
authors.initials: E
authors.lastname: Hadavandi
authors.affiliation: Department of Community Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
authors.forename: Omid
authors.initials: O
authors.lastname: Pournik
authors.affiliation: Industrial Engineering Department, Amirkabir University of Technology, Tehran, Iran.
authors.forename: Jamal
authors.initials: J
authors.lastname: Shahrabi
authors.affiliation: Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
authors.forename: Fereidoun
authors.initials: F
authors.lastname: Azizi
authors.affiliation: Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Science, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
authors.forename: Farzad
authors.initials: F
authors.lastname: Hadaegh
mesh_terms: D000328:Adult; D000465:Algorithms; D019540:Area Under Curve; D062186:Arterial Pressure; D001786:Blood Glucose / Q000378:metabolism; D001827:Body Height; D001835:Body Weight; D003663:Decision Trees; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D015994:Incidence; D007492:Iran / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011446:Prospective Studies; D012372:ROC Curve; D012307:Risk Factors; D012737:Sex Factors
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents
keywords: Data Mining; Decision tree; Diabetes; Interaction; Prediction