Developing a simple and practical decision model to predict the risk of incident type 2 diabetes among the general population: The Di@bet.es Study.

Fecha de publicación: 01/08/2022 Fecha Ahead of Print: 13/05/2022

Autores de INCLIVA

Participantes ajenos a INCLIVA

Morales-Suarez-Varela, Maria M
Andres-Blasco, Irene
Peraita-Costa, Isabel

Grupos y Plataformas de I+D+i

Grupo de Investigación sobre Riesgo Cardiometabólico y Diabetes

Leading Researcher

Sergio Martinez Hervas
Unidad de Genómica y Diabetes

Established Researcher

Felipe Javier Chaves Martínez

Abstract

AIMS: To develop a simple multivariate predictor model of incident type 2 diabetes in general population. METHODS: Participants 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. RESULTS: 156 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. CONCLUSIONS: The 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.