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

Area of Science:

• Medical device safety
• Regulatory science
• Biostatistics

Background:

• Signal detection is crucial for identifying potential safety issues with medical devices.
• Change point analysis (CPA) is a statistical method for detecting changes in longitudinal data.
• Aortic stent grafts are medical devices requiring continuous safety monitoring.

Purpose of the Study:

• To investigate the temporal relationship between endoleak reports for aortic stent grafts and regulatory alerts.
• To evaluate the utility of CPA in identifying changes in medical device adverse event reports.

Main Methods:

• Analysis of device malfunction and adverse event reports for aortic stent grafts submitted to the PMDA (April 2008 - September 2022).
• Mapping reports to the Medical Device Problem Terminology.
• Application of CPA to identify temporal changes in endoleak report counts with a significance threshold of 90% confidence.

Main Results:

• A total of 20,678 reports were analyzed, with 10,779 related to endoleaks.
• CPA identified a significant increase in endoleak events in April 2015, two years before the PMDA alert.
• Significant change points were also detected in July 2008 and April 2016.

Conclusions:

• CPA may assist in prioritizing investigations of medical device malfunctions and adverse events.
• The study did not demonstrate earlier or superior signal detection compared to regulatory authorities.
• Further research is needed to assess CPA's applicability to other medical devices and malfunctions.