Identification of Patient Profiles with Better Glycemic Outcomes Using Machine Learning—Results from the International Diabetes Management Practices Study (IDMPS)

Optimal diabetes care requires medical management, regular assessment, and self-care. We conducted a retrospective exploratory analysis using data from the IDMPS (a global observational survey on the management of diabetes in the developing world) using a subgroup discovery algorithm (Q-finder) to identify factors (patient profiles [PaPr]) associated with glycemic outcomes (good, HbA 1c ≤7%; poor, HbA 1c >7%) in people with type 2 diabetes. In total, 49,309 people from 48 countries in Latin America, Africa, the Middle East, Eurasia and Asia Pacific were included in seven individual waves of data collection. Variables analyzed (n=340) included demography, co-morbidities, clinical parameters and glucose lowering therapy; 107 were common to all waves. The algorithm identified combinations of variables and groups of people in which glycemic outcomes were significantly different to the total study population. Learning was conducted on Waves 6 and 7 (n=4937 and n=5695, respectively) to generate PaPr. PaPr were validated using a dataset that varied depending on the learning wave (Wave 6 max = 43,614; Wave 7 max = 44,372), and was dictated by the level of variable documentation in each wave. Each subgroup (PaPr) was characterized by 1-3 descriptive variables, and comprised ≥10% of the total patient population. All results reaching statistical significance (adjusted for multiple testing) were replicated in all waves. We have validated 11 out of 30 PaPr for clinical relevance. PaPr that positively affect glycemic outcomes include healthy diet and lifestyle, controlled FPG and PPG (calculated thresholds of 130 mg/dL and 180 mg/dL, respectively), systolic blood pressure Good glycemic control is often associated with management of cardiometabolic risk factors and self-management; a system-wide approach is needed to realize these goals. Disclosure J.C.N. Chan: Consultant; Self; Bayer AG. Other Relationship; Self; Bayer AG. Consultant; Self; Sanofi. Other Relationship; Self; Sanofi, Eli Lilly and Company, Amgen Inc.. Consultant; Self; AstraZeneca, Merck & Co., Inc., Pfizer Inc.. Other Relationship; Self; Pfizer Inc.. Board Member; Self; Asia Diabetes Foundation. Stock/Shareholder; Self; GemVCare. Other Relationship; Self; Merck Sharp & Dohme Corp.. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Novartis AG, Eli Lilly and Company. J.J. Gagliardino: Other Relationship; Self; Sanofi. H.M. Ilkova: Advisory Panel; Self; Abbott, Eli Lilly and Company, Novartis AG, Novo Nordisk A/S, Boehringer Ingelheim GmbH, Servier, Merck Sharp & Dohme Corp.. Speaker9s Bureau; Self; AstraZeneca. Advisory Panel; Self; Medtronic, Roche Diabetes Care Health and Digital Solutions, Bilim Ilac. F.J. Lavalle-Gonzalez: Advisory Panel; Self; Sanofi. Speaker9s Bureau; Self; Sanofi. Research Support; Self; Janssen Pharmaceuticals, Inc.. Advisory Panel; Self; Janssen Pharmaceuticals, Inc.. Speaker9s Bureau; Self; Janssen Pharmaceuticals, Inc.. Consultant; Self; Novo Nordisk Inc.. Advisory Panel; Self; AstraZeneca. Speaker9s Bureau; Self; AstraZeneca. Research Support; Self; AstraZeneca. Advisory Panel; Self; Merck Sharp & Dohme Corp.. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Speaker9s Bureau; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Advisory Panel; Self; Eli Lilly and Company. Speaker9s Bureau; Self; Eli Lilly and Company. Advisory Panel; Self; Abbott. Speaker9s Bureau; Self; Abbott. A. Ramachandran: None. G. Kaddaha: Other Relationship; Self; Sanofi. J. Mbanya: Advisory Panel; Self; GlaxoSmithKline plc.. Speaker9s Bureau; Self; Novo Nordisk A/S, Sanofi, Servier. J. Chantelot: Employee; Self; Sanofi. Stock/Shareholder; Self; Sanofi. M.V. Shestakova: None. P. Aschner: Other Relationship; Self; Sanofi. F. Magnard: None. M. Rollot: None. A. Civet: None. F. Barbe: None.