Application of natural language processing and network analysis techniques to post-market reports for the evaluation of dose-related anti-thymocyte globulin safety patterns

Taxiarchis Botsis, Matthew Foster, Nina Arya, Kory Kreimeyer, Abhishek Pandey, Deepa Arya

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To evaluate the feasibility of automated dose and adverse event information retrieval in supporting the identification of safety patterns. Methods: We extracted all rabbit Anti-Thymocyte Globulin (rATG) reports submitted to the United States Food and Drug Administration Adverse Event Reporting System (FAERS) from the product’s initial licensure in April 16, 1984 through February 8, 2016. We processed the narratives using the Medication Extraction (MedEx) and the Event-based Text-mining of Health Electronic Records (ETHER) systems and retrieved the appropriate medication, clinical, and temporal information. When necessary, the extracted information was manually curated. This process resulted in a high quality dataset that was analyzed with the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA) to explore the association of rATG dosing with post-transplant lymphoproliferative disorder (PTLD). Results: Although manual curation was necessary to improve the data quality, MedEx and ETHER supported the extraction of the appropriate information. We created a final dataset of 1,380 cases with complete information for rATG dosing and date of administration. Analysis in PANACEA found that PTLD was associated with cumulative doses of rATG >8 mg/kg, even in periods where most of the submissions to FAERS reported low doses of rATG. Conclusion: We demonstrated the feasibility of investigating a dose-related safety pattern for a particular product in FAERS using a set of automated tools.

Original languageEnglish (US)
Pages (from-to)396-411
Number of pages16
JournalApplied clinical informatics
Volume8
Issue number2
DOIs
StatePublished - 2017
Externally publishedYes

Keywords

  • Data visualization
  • Information retrieval
  • Natural language processing
  • Network analysis
  • Postmarketing product surveillance

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Health Information Management

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