Prostaglandin analogs signal detection by data mining in the FDA Adverse Event Reporting System database.

Abstract

Abstract Background: Adverse Events (AEs) which are not mentioned in the safety information label the any drug, are considered “unexpected” and must be regarded and analyzed as a safety signal. Prostaglandins cause effects on different cell types around the body, triggering diverse actions, and due to the analogy of an endogenous prostamida of the prostaglandin’s analogs, it is essential to identify the possible association that could cause the use of these drugs in ophthalmologic practice. This study aims to identify safety signals of ophthalmic prostaglandin analogs (PGAs) through data mining the Food and Drug Administration Adverse Event Reporting System (FAERS) database. Methods: A data mining search by proportional reporting ratio, reporting odds ratio, Bayesian confidence propagation neural network, information component 0.25, and Chi-squared for safety signals detection was conducted to the FAERS database for the following ophthalmic medications: latanoprost, travoprost, tafluprost, and bimatoprost for the identification AE with statistical associations. Results: Twelve preferred terms were statistically associated: diabetes mellitus, n=2; hypoacusis, n=2; malignant mediastinal neoplasm, n=1; blood immunoglobulin E increased, n=1; cataract, n=1; blepharospasm, n=1; full blood count abnormal, n=1; skin exfoliation, n=1; chest discomfort, n=1; and dry mouth, n=1. Conclusions: Of the twelve PTs analyzed, eight of them found information on the possible relationship due to the biological plausibility derived from information from previous research; for this reason, it is relevant to continue investigating the possible drug-event association, whether to refute the safety signal or identify a new risk with its consequent minimization.