1521-P: An Efficacy Evaluation on Prediabetes Management Using a Machine Learning-Based Risk Stratification Approach

Abstract

The progression of prediabetes towards diabetes was heterogeneous, suggesting a demand for individualized management. We aim to investigate whether stratifying participants with prediabetes according to their progression risk could affect the response to interventions. We developed a 1-year diabetes progression risk evaluating model with a panel of diabetes risk factors using a machine learning method (i.e., Bagging algorithm with 300 decision trees) in prediabetes participants in Pinggu Study (a prospective population-based survey in suburban Beijing, n=622). The model training phase was conducted on 2/3 randomly selected participants and the validation phase was conducted on other 1/3. This model successfully predicted the 1-year progression of prediabetes participants in Pinggu study (internal ROC AUC 1.000, external ROC AUC 0.883). In Beijing Prediabetes Reversion Program (BPRP, a multi-central RCT to evaluate the efficacy of lifestyle and/or pioglitazone on prediabetes reversion, n=1897), subjects were divided into tertiles as high, medium and low risk groups according to their progression probability predicted by the model. Pioglitazone plus intensive lifestyle significantly increased reversion and reduced diabetes progression only in high risk group. This study suggests personalized treatment on prediabetes according to their progression risk is necessary. Disclosure X. Zou: None. Z. Zhu: None. Y. Luo: None. Y. Li: None. X. Zhou: None. L. Ji: Advisory Panel; Self; AstraZeneca. Consultant; Self; AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Bristol-Myers Squibb Company, Eli Lilly and Company, Merck KGaA, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi, Takeda Pharmaceutical Company Limited. Research Support; Self; AstraZeneca, Bristol-Myers Squibb Company, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Roche Pharma, Sanofi. Funding The Major Chronic Non-Communicable Disease Prevention and Control Research of China; Beijing Science and Technology Committee; National Natural Science Foundation of China