Graduate assistant University of Florida Gainesville, United States
Background: Previous studies have reported conflicting results on the association between metformin and risk of dementia which might be caused by varied drug responses of metformin in different population subgroups.
Objectives: We aimed to examine the heterogeneous treatment effects (HTEs) of metformin on dementia risk in the population with type 2 diabetes (T2D).
Methods: Using 2005-2021 data from the National Alzheimer’s Coordinating Center (NACC), we identified individuals with diabetes (≥50 years old, ≥2 clinic visits) and normal cognition at baseline. The primary outcome was incident dementia. We applied a causal machine learning approach - doubly robust learning - to estimate the risk difference (RD) with 95% confidence interval (CI) in the overall cohort and the HTE subgroups based on the identified important features using a summary decision tree model.
Results: Of 1,505 individuals with T2D, 822 (55%) were taking metformin at baseline and 683 (45%) were not. 109 participants (7.2%) developed dementia over a median follow-up of 4.0 years. In the overall cohort, metformin was associated with a lower risk of dementia (RD, -2.9%; 95% CI, -5.9% to -0.002%). We identified four subgroups with varied risks for dementia in those on metformin therapy, defined by neuropsychiatric disorders, alcohol abuse, and antidepressant use. Metformin was significantly associated with a lower risk of dementia in the subgroup with no neuropsychiatric disorders and no alcohol abuse (-5.9%; -9.6% to -2.3%); however, it was associated with a greater risk in those with neuropsychiatric disorders and no antidepressant use (7.4%; 0.8% to 14.0%).
Conclusions: Metformin use was significantly associated with a lower risk of dementia in individuals with T2D, with significant variability among subgroups. Data-driven subgroup analyses may guide personalized treatment for diabetes care.
