Authors
Mareena Biju, HeeJae Choi, Shilpa Madari, Annie Carlisle, Ashish Sharma, Christina Kunz, Fenglei Huang
Published in
Clinical and translational science. Volume 19. Issue 10. Pages e70734.
Abstract
Lung cancer predominantly affects older adults who already experience comorbidities and are at increased risk of drug-drug interactions (DDIs) due to polypharmacy. Traditional DDI assessments often do not fully capture complex co-medication patterns observed in real-world practice due to the risk of introducing confounding factors. This study used U.S. Optum claims data from 2019 to 2024 to characterize co-medication patterns in predominately non-small cell lung cancer (NSCLC) patients and map enzyme- and transporter-mediated liabilities across commonly used medications, chemotherapy agents, and biomarker-driven therapies. Potential DDI liabilities were further prioritized using a semi-quantitative clinical framework based on perpetrator strength, substrate sensitivity, narrow therapeutic index status, and available evidence. Frequently used medications included disease-specific supportive therapies such as ondansetron and dexamethasone, as well as treatments for common U.S. comorbidities such as cardiovascular and endocrine disorders. Many of the co-medications were substrates, inhibitors, and inducers of pathways critical for NSCLC treatments such as CYP3A, CYP2D6, P-gp, and OATP1B and additional risks were identified when giving treatments with acid-reducing agents or QT-prolonging drugs. These findings demonstrate how integrating real-world data (RWD) can strengthen DDI assessment by improving clinical trial design, informing risk-mitigation strategies, and supporting more patient-centric drug development.
PMID:
42813501
Bibliographic data and abstract were imported from PubMed on 30 Sep 2026.
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