Comparison of drug-drug interaction checking databases for interactions involving BCR-ABL tyrosine kinase inhibitors


GÜNAY A., DEMİRPOLAT E., AYCAN M. B., ÜNAL A.

ISTANBUL JOURNAL OF PHARMACY, cilt.54, sa.1, ss.32-39, 2024 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 54 Sayı: 1
  • Basım Tarihi: 2024
  • Doi Numarası: 10.26650/istanbuljpharm.2024.1207607
  • Dergi Adı: ISTANBUL JOURNAL OF PHARMACY
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.32-39
  • Anahtar Kelimeler: Drug -drug interactions, chronic myeloid leukemia, tyrosine kinase inhibitors, TKIs, CML
  • Erciyes Üniversitesi Adresli: Evet

Özet

Background and Aims: BCR-ABL tyrosine kinase inhibitors (TKIs) are used for the treatment of chronic myeloid leukemia and are commonly involved in clinically significant drug-drug interactions (DDIs). In this study, we aimed to evaluate the consensus of DDI checking databases for interactions involving BCR-ABL TKIs. Methods: We checked DDIs of 100 drugs with six BCR-ABL TKIs-dasatinib, imatinib, nilotinib, ponatinib, bosutinib, and asciminib-in two subscription-based databases (UpToDate and Micromedex) and two open-access databases (Drugs.com and Medscape). Databases were compared in terms of severity ratings, literature support ratings, and general interaction mechanism definitions using Fleiss' and Cohen's kappa statistics. Results: A total of 410 interactions were found. Nilotinib was the most interacted TKI, with 88 interactions. Drugs.com detected the highest number of interactions (n = 355). The overall agreement levels of databases for the severity ratings and general mechanisms were calculated as 0.13 (p = 0) and 0.28 (p = 0), respectively. The Micromedex- UpToDate pair showed the highest agreement level in terms of severity ratings and general mechanism definitions, with kappa values of 0.23 and 0.45, respectively. Conclusion: The differences among databases for DDIs involving BCR-ABL TKIs were statistically significant. Therefore, healthcare practitioners should check DDIs in multiple databases.