1088-P: Can Machine Learning Support Decision for Insulin Initiation in Patients with Type 2 Diabetes?

Abstract

We examined the ability of machine learning models to predict insulin initiation by specialists and examined whether the machine learning approach could support decision-making by general physicians for insulin initiation in patients with type 2 diabetes. Prescription data from diabetes specialists’ patient registries on antidiabetic agents from 2009 to 2015 were used for 4,860 patients who received initial monotherapy with either insulin (293 patients) or non-insulin (4,567 patients) and had laboratory data. Neural network output was insulin initiation ranging from 0 to 1 with a cutoff >0.5 for the dichotomous classification. Accuracy, recall and area under the receiver operation characteristic curves (AUCs) were calculated to compare the ability of machine-learning decisions on insulin initiation to decisions by logistic regression and 22 general physicians. Then, in comparing the ability of machine-learning and logistic regression decisions to decisions made by general physicians, the gold standard was defined as 80% agreement among 9 diabetes specialists based on patients’ information. AUCs and accuracy according to logistic regression were higher than those of machine learning (AUC of logistic regression, 0.89-0.90; AUC of machine learning, 0.67-0.74). Recall (accuracy of the cases receiving insulin) in machine learning was similar to that of logistic regression analysis (recall of logistic regression, 0.05-0.68; recall of machine learning, 0.11-0.52). The accuracy of logistic regression and the machine learning model was 1.00 and 0.86, respectively, for down sampling ratios of 1:8, which was higher than that of general physicians (0.43) for 7 gold standard cases. In conclusion, machine learning had higher accuracy in prediction of insulin initiation compared with that of general physicians defined by diabetes specialists’ choice of the gold standard. Assistance by machine learning may be beneficial to any general physician in deciding upon insulin initiation. Disclosure K. Fujihara: None. H. Sone: Research Support; Self; Astellas Pharma Inc., Eisai Co., Ltd., Kyowa Kirin Co., Ltd., Novo Nordisk, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co. Funding Japan Society for the Promotion of Science (19H04028)