• Sergio Martínez-Hervás, María M Morales-Suarez-Varela, Irene Andrés-Blasco, Francisco Lara-Hernández, Isabel Peraita-Costa, José T Real, Ana-Bárbara García-García, and F Javier Chaves.
• Department of Medicine, University of Valencia, Avenida Blasco Ibañez 15, Valencia 46010, Spain; Service of Endocrinology and Nutrition, Valencia University Clinical Hospital, Avenida Blasco Ibañez 17, Val... more encia 46010, Spain; INCLIVA Biomedical Research Institute, Menendez Pelayo 4acc, Valencia 46010, Spain; CIBER of Diabetes and Associated Metabolic Diseases CIBERDEM, Monforte de Lemos 3-5, Madrid 28029, Spain. less
• Eur. J. Intern. Med. 2022 Aug 1; 102: 80-87.

AimsTo develop a simple multivariate predictor model of incident type 2 diabetes in general population.MethodsParticipants were recruited from the Spanish Di@bet.es cohort study with 2570 subjects meeting all criteria to be included in the at-risk sample studied here. Information was collected using an interviewer-administered structured questionnaire, followed by physical and clinical examination. CHAID algorithm, which collects the information of individuals with and without type 2 diabetes, was used to develop a decision tree based type 2 diabetes prediction model.Results156 individuals were identified as having developed type 2 diabetes (6.5% incidence). Fasting plasma glucose (FPG) at the beginning of the study was the main predictive variable for incident type 2 diabetes: FPG ≤ 92 mg/dL (ref.), 92-106 mg/dL (OR = 3.76, 95%CI = 2.36-6.00), > 106 mg/dL (OR = 13.21; 8.26-21.12). More than 25% of subjects starting follow-up with FPG levels > 106 mg/dL developed type 2 diabetes. When FPG <106 mg/dL, other variables (fasting triglycerides (FTGs), BMI or age) were needed. For levels ≤ 92 mg/dL, higher FTGs levels increased risk of incident type 2 diabetes (FTGs > 180 mg/dL, OR = 14.57; 4.89-43.40) compared with the group of FTGs ≤ 97 mg/dL (FTGs  = 97-180 mg/dL, OR = 3.12; 1.05-9.24). This model correctly classified 93.5% of individuals.ConclusionsThe type 2 diabetes prediction model is based on FTGs, FPG, age, gender, and BMI values. Utilizing commonly available clinical data and a simple blood test, a simple tree diagram helps identify subjects at risk of developing type 2 diabetes, even in apparently low risk subjects with normal FPG.Copyright © 2022 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

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