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Active-comparator restricted disproportionality analysis for pharmacovigilance signal detection studies of chronic
Wajd Alkabbani1, John-Michael Gamble1
1School of Pharmacy, University of Waterloo, Kitchener, ON, Canada.
Aims:
Disproportionality analysis is a common pharmacovigilance tool to detect safety signals of type 2 diabetes medications from spontaneous drug reporting databases. The aim was to demonstrate the impact of using active-comparator restricted disproportionality analysis (ACR-DA), wherein the reference group is restricted to reports with a clinically appropriate active comparator.
Methods:
Using reports from the Food and Drug Administration Adverse Event Reporting System, we assessed if sodium/glucose cotransporter 2 (SGLT2) inhibitors are associated with higher reporting of 5 potential adverse events: acute kidney injury, genitourinary tract infections, diabetic ketoacidosis, fractures, and amputations. For each adverse event, we calculated the proportional reporting ratio (PRR) and adjusted reporting odds ratio (aROR [95% confidence interval, CI]) using 3 types of reference groups: no SGLT2 inhibitor (background risk reference), other diabetes drugs (therapeutic class reference), and dipeptidyl peptidase 4 inhibitors (active comparator reference).
Results:
Based on ACR-DA, we did not detect a safety signal for acute kidney injury (PRR 0.92 [0.81-1.04]; aROR 0.78 [95% CI 0.72-0.85]) or fractures (PRR 0.44[95% CI 0.17-1.15]; aROR 0.74 [95% CI 0.61-0.91]) associated with SGLT2 inhibitors compared to dipeptidyl peptidase 4 inhibitors. However, we detected safety signals for genitourinary tract infections (PRR 2.75[2.02-3.76]; aROR 2.54[2.26-2.86], diabetic ketoacidosis (PRR 63.85[39.37-103.53; aROR 91.49[70.66-118.48]), and amputations (PRR 52.60 [19.66-140.75]; aROR 22.64 [15.32-33.42].
Conclusion:
The use of the proposed ACR-DA to detect safety signals of type 2 diabetes medications may reduce false positive safety signals through careful selection of the comparator which is expected to reduce channelling bias.
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