Diabetes/metabolism research and reviews · 2025
Development of a Prediction Model for Predicting 10-year Incidence of Type 2 Diabetes in Japanese People; Panasonic Cohort Study 7.
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Munekawa Chihiro, Horiguchi Go, Naito Akari, Hamaguchi Masahide, Kurogi Kazushiro, Murata Hiroaki, Ito Masato, Obora Akihiro, Kojima Takao, Okada Hiroshi, Teramukai Satoshi, Fukui Michiaki
Аннотация
AIMS: In Japan, several prediction models and scoring systems for type 2 diabetes have been reported; however, none have high utility. We developed a new clinical prediction model for the onset of type 2 diabetes.
MATERIALS AND METHODS: The development dataset was obtained from 72,124 Japanese employees who participated in a health check-up programme conducted by Panasonic Corporation (Osaka, Japan), were aged 40 years or older, were diabetes-free at baseline, and followed-up for up to 10 years. The external validation dataset was obtained from 12,885 participants of the NAGALA (Gifu City, Gifu Prefecture Longitudinal Analysis) cohort. A prediction model was developed to predict the 10-year risk of developing diabetes using information from the health checkup programme. The developed model was internally validated, and externally validated using the NAGALA cohort.
RESULTS: Using information on age, sex, body mass index, systolic blood pressure, log-triglycerides, high-density lipoprotein, log-alanine aminotransferase, fasting plasma glucose, weight gain, and smoking status obtained from a health checkup programme, we developed a novel, highly sensitive, and specific model for predicting the 10-year risk of developing diabetes. The prediction model showed excellent performance, with an optimism-corrected c-index of 0.877 and a c-index of 0.882 in the external validation cohort.
CONCLUSION: We developed a noninvasive diabetes risk-prediction model for the Japanese population and confirmed its utility for identifying individuals at high risk of type 2 diabetes over time.
MATERIALS AND METHODS: The development dataset was obtained from 72,124 Japanese employees who participated in a health check-up programme conducted by Panasonic Corporation (Osaka, Japan), were aged 40 years or older, were diabetes-free at baseline, and followed-up for up to 10 years. The external validation dataset was obtained from 12,885 participants of the NAGALA (Gifu City, Gifu Prefecture Longitudinal Analysis) cohort. A prediction model was developed to predict the 10-year risk of developing diabetes using information from the health checkup programme. The developed model was internally validated, and externally validated using the NAGALA cohort.
RESULTS: Using information on age, sex, body mass index, systolic blood pressure, log-triglycerides, high-density lipoprotein, log-alanine aminotransferase, fasting plasma glucose, weight gain, and smoking status obtained from a health checkup programme, we developed a novel, highly sensitive, and specific model for predicting the 10-year risk of developing diabetes. The prediction model showed excellent performance, with an optimism-corrected c-index of 0.877 and a c-index of 0.882 in the external validation cohort.
CONCLUSION: We developed a noninvasive diabetes risk-prediction model for the Japanese population and confirmed its utility for identifying individuals at high risk of type 2 diabetes over time.