Factors Influencing Regulatory Decision-Making in Signal Management: Analysis Based on the Signals Identified from the FAERS.

Purpose: This study aimed to identify factors that influence the decision to take safety regulatory actions in routine signal management based on spontaneous reports. For this purpose, we analyzed the safety signals identified from the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and related information.

Method: From the signals that the FDA identified in the FAERS between 2008 1Q and 2014 4Q, we selected 216 signals for which regulatory action was or was not taken.

Significance of data mining in routine signal detection: Analysis based on the safety signals identified by the FDA.

Purpose: Data mining has been introduced as one of the most useful methods for signal detection by spontaneous reports, but data mining is not always effective in detecting all safety issues. To investigate appropriate situations in which data mining is effective in routine signal detection activities, we analyzed the characteristics of signals that the US Food and Drug Administration (FDA) identified from the FDA Adverse Event Reporting System (FAERS).

Methods: Among the signals that the FDA identified from the FAERS between 2008 1Q and 2014 4Q, we selected 233 signals to evaluate in this study.

Association between infection and severe drug adverse reactions: an analysis using data from the Japanese Adverse Drug Event Report database.

Purpose: It has been reported recently that immune reactions are involved in the pathogenesis of certain types of adverse drug reactions (ADRs). We aimed to determine the associations between infections and drug-induced interstitial lung disease (DILD), rhabdomyolysis, Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), or drug-induced liver injury (DILI) using a spontaneous adverse drug event reporting database in Japan.

Methods: The reported cases were classified into three categories (anti-infectious drug group, concomitant infection group, and non-infection group) based on the presence of anti-infectious drugs (either as primary suspected drug or concomitant drug) and infectious disease.

Effect of database profile variation on drug safety assessment: an analysis of spontaneous adverse event reports of Japanese cases.

Background: The use of a statistical approach to analyze cumulative adverse event (AE) reports has been encouraged by regulatory authorities. However, data variations affect statistical analyses (eg, signal detection). Further, differences in regulations, social issues, and health care systems can cause variations in AE data.

Association between acute myelogenous leukemia and thrombopoietin receptor agonists in patients with immune thrombocytopenia.

Objective: The development of myeloid malignancies is a concern when administering thrombopoietin receptor (or the myeloproliferative leukemia virus proto-oncogene product, MPL) agonists. Progression from myelodysplastic syndrome (MDS) to acute myelogenous leukemia [AML, 9 (6.12%) AML patients among 147 MDS subjects] was reported in a clinical trial.