Development of a database and processing method for detecting hematotoxicity adverse drug events.

Area of Science:

• Pharmacovigilance
• Medical Informatics
• Hematology

Background:

• Monitoring patient status and blood tests is crucial for adverse event detection.
• Identifying all adverse events solely through physician recognition presents challenges.
• Electronic medical record systems offer a valuable data source for adverse event surveillance.

Purpose of the Study:

• To develop and validate a system for detecting hematotoxicity adverse drug events using blood test results from electronic medical records.
• To assess the occurrence rate of serious adverse events (CTCAE Grades 3 or 4) related to paclitaxel.

Main Methods:

• Blood test results were graded using Common Terminology Criteria for Adverse Events (CTCAE).
• Variations in blood test grades (Up, Down, Flat) were assessed.
• A database integrated blood test changes and drug injection data to identify drug-related adverse events.
• The system was applied to identify serious adverse events (WBC, ALT, creatinine) associated with paclitaxel at Osaka University Hospital.

Main Results:

• The system successfully detected hematotoxicity adverse events.
• The occurrence rates for decreased White Blood Cell (WBC) count, increased Alanine Aminotransferase (ALT) level, and increased creatinine level were 36.0%, 0.6%, and 0.4%, respectively.
• Serious adverse events related to paclitaxel were identified and quantified.

Conclusions:

• The developed system is effective for detecting and estimating the incidence of hematotoxicity adverse drug events.
• This method enhances the ability to identify adverse events that might be missed by individual physician recognition.
• The findings highlight the utility of leveraging electronic medical record data for pharmacovigilance.