A cross-sectional observational study of the prevalence and characterization of potential QT-prolonging drug‒drug interactions in oncological outpatients
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Akash Agnihotri
,
Biswadeep Das
Abstract
Objectives
This study aims to assess the prevalence, characteristics, and risk factors of potential QT-prolonging drug–drug interactions (pQT-DDIs) in cancer patients, including identifying drug combinations contributing to QT prolongation and key predictors.
Methods
In this hospital-based, cross-sectional observational study, all types of cancer patients, irrespective of age or sex, were included over 1 year. pQT-DDIs were identified using four drug interaction checker software tools. Predictors were analyzed using univariate logistic regression.
Results
A total of 1,331 cancer patients were included. The prevalence of pQT-DDIs was 67.6 %. Of these, 606 (45.5 %) had 1–2 pQT-DDIs, 126 (9.5 %) had 3–4, and 78 (5.9 %) had 5–6. Overall, 163 drug combinations were identified as causing QT prolongation; 122 were detected by Drugs.com. Significant predictors included >8 drugs prescribed (OR=6.46; CI=4.87–8.56; p<0.0001), >2 anticancer drugs (OR=1.68; CI=1.14–2.46; p=0.008), >6 adjuvant drugs (OR=6.83; CI=5.17–9.03; p<0.0001), solid cancers (OR=6.59; CI=4.59–8.80; p<0.0001), and cytotoxic drug use (OR=2.40; CI=1.52–3.77; p=0.0001).
Conclusions
There is a high prevalence of pQT-DDIs in cancer patients. Those receiving multiple anticancer and adjuvant drugs are at higher risk. Routine interaction screening is recommended before chemotherapy.
Acknowledgments
We would like to express our sincere gratitude to Dr. Uttam Kumar Nath (Head, Medical Oncology and Hematology, AIIMS Rishikesh) and Mr Nishant (Nursing Officer-Oncology) for his invaluable assistance in the data collection process.
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Research ethics: The study received research and Ethical Approval from the Institutional Ethics Committee of the All-India Institute of Medical Sciences (AIIMS), Rishikesh, Uttarakhand, India, as documented in the approval letter AIIMS/IEC/20/610 dated September 12, 2020.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: No large language models, AI, or machine learning tools were used to generate the content of this manuscript.
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Conflict of interest: Authors state no conflict of interest.
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Research funding: No funding has been taken for this study.
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Data availability: Not applicable.
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