Impact of Cardiovascular Medications on Non-Traumatic Amputation Rates in Type 2 Diabetes: Insights from a Large-Scale Retrospective Real-World Data Analysis

OBJECTIVES: This study investigates the impact of cardiovascular medications on the incidence of non-traumatic amputation in patients with Type 2 Diabetes Mellitus (T2DM). This study leverages retrospective, real-world data (RWD) to bridge the gap between clinical trial findings and actual clinical outcomes, offering critical insights on these medications in diverse, real-world patient populations.

METHODS: A retrospective study was conducted using large-scale real-world data from 1.2 billion patients, focusing on T2DM patients over 18 years. Data from IQVIA™ US and Japan, formatted in the Observational Medical Outcomes Partnership (OMOP) common data model, were used, encompassing claims, hospital, and EMR data. The study period spanned from January 1, 2015, to December 31, 2022. The analysis focused on patients prescribed statins, fenofibrates, anti-hypertensives, aspirin, and GLP-1/SGLT2 inhibitors, without concurrent use of other study drugs.

RESULTS: The analysis revealed a statistically significant reduction in incidence proportion of non-traumatic amputation when patients were prescribed to statins (0.32-4.91) and fenofibrates (0.37-5.65) compared to anti-hypertensives (0.68-4.59), aspirin (0.88-2.67) and GLP-1/SGLT2i's (0.40-3.38). Assessing different types of RWD in the US, our results show that incidence rates across all drugs were considerably higher for in Hospital EMRs (0.66-2.78) compared to the Claims (0.33-1.29) and Outpatient databases (0.16-0.35).

CONCLUSIONS: This study underscores the value of RWD in enhancing our understanding of the real-world implications of medication use in T2DM management. Continued research, employing rigorous experimental designs and advanced statistical techniques like propensity score matching and negative controls, are needed for more definitive comparative analysis. Additionally, the variance in incidence rates across different data sources underscores the importance of considering the context of healthcare settings in evaluating drug effectiveness.