High-Throughput Safety Signal Detection for Sodium-Glucose Cotransporter-2 Inhibitors in Type 2 Diabetes
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Objective
To systematically identify potential safety signals associated with sodium-glucose cotransporter-2 inhibitors (SGLT2i) in patients with type 2 diabetes (T2D) using a high-throughput target trial emulation pipeline applied to real-world data.
Methods
We utilized electronic health record (EHR) data from the OneFlorida+ Data Trust (2012–2023). Using a retrospective new-user cohort design, we compared SGLT2i initiators to initiators of other second-line glucose-lowering drugs (GLDs). We evaluated risk across all ICD-10-CM 4-digit diagnosis codes. A semi-Bayesian shrinkage method was employed to adjust hazard ratios (HR) and p-values to account for multiple testing and stabilize estimates for rare outcomes.
Results
The analysis identified several statistically significant safety signals. Validating our method, we observed known adverse events such as candidiasis of the vulva and vagina (HR=1.64) and other urogenital fungal infections. We also detected potential signals for conditions such as viral conjunctivitis and melanocytic nevi.
Conclusion
This high-throughput screening effectively identified both known and potential new safety signals for SGLT2i. The use of semi-Bayesian shrinkage provides a robust framework for post-marketing surveillance in large healthcare databases.
