Signal Detection Using Change Point Analysis to Identify Safety Signals from Spontaneous Reports in Aortic Stent Grafts in Japan.

Signal detection is essential for identifying potential safety issues with drugs and medical devices. Change point analysis (CPA) detects changes in longitudinal data for a medical device without incorporating comparisons with other devices. This study investigated the temporal relationship between endoleak reports for aortic stent grafts identified using CPA and the issuance of the "Pharmaceuticals and Medical Devices Agency (PMDA) Alert for Proper Use of Medical Devices" in Japan. Device malfunction and adverse event reports for aortic stent grafts submitted to the PMDA between April 2008 and September 2022 were analyzed. The reports were mapped to the Medical Device Problem Terminology from the Japan Federation of Medical Devices Associations. CPA was used to identify temporal changes in report counts, with change points having confidence levels ≥ 90% being considered significant. A total of 20,678 reports were analyzed, including 23,541 device malfunctions and 30,500 adverse events. Endoleaks accounted for 10,779 events. CPA identified a significant increase in endoleak events in April 2015 (2 years before the regulatory alert). Confidence levels exceeded 90% in 76 out of 174 evaluated time points, first in July 2008 (9 years before the alert) and next in April 2016 (1 year before the alert). Based on these findings, CPA may help prioritize investigations of medical-device-related malfunctions and adverse events. However, the results do not indicate earlier or superior signal detection relative to regulatory authorities. Further research is needed to assess CPA's applicability to other medical devices and malfunctions.