Pharmacy records and electronic patient charts were reviewed for patients who began AA treatment between January 2010 through April 2014, at the Odette Cancer Centre in Toronto, Ontario, Canada. Patient drug lists were analyzed by Lexicomp and Micromedex, two of the commonly applied commercial databases used to investigate potential DDIs. Eighty-four patients met the inclusion criteria (median age 74 years, range 47-91 years). All patients had at least one co-medication while on AA therapy, with a median of 5 (1-24) co-medications per patient. Of the 476 co-medications identified, cardiovascular, analgesic, and laxative classifications were most commonly administered (in 24%, 19%, and 11% of patients, respectively).
Overall, 83% (n=70) of patients presented 184 distinct cases of potential DDIs; 77% (n=65) of patients were flagged by Lexicomp, and 52% (n=44) by Micromedex for one or more potential DDIs. No potential DDIs of the highest risk category were identified (i.e. Lexicomp “Level X”, Micromedex “Contraindicated”). Lexicomp revealed 61% (n=51) of patients with a “Level C” risk (i.e. treatment monitoring is advised), and 23% (n=19) with a “Level D” risk (treatment modification is suggested). Analyses using Micromedex showed 40% (n=34) of patients with a “Moderate Risk” of interaction, and 20% (n=17) with a “Major Risk”. Of note, there was no single instance of complete agreement between Lexicomp and Micromedex (i.e. DDIs identified by both databases and identical level of risk assignment).
“Level D”/ “Major Risk” was most commonly associated with opioids (oxycodone, morphine sulfate), metoprolol, and clopidogrel. While AA might increase the levels of oxycodone, morphine sulfate and metoprolol, it may prevent the conversion of clopidogrel to its active metabolite and thus inhibit clopidogrel’s anti-aggregatory function.
The hepatic metabolism of AA depends largely on CYP3A4. As none of our patients were undergoing treatment with a strong CYP3A4 inhibitor, while on AA, we were unable to evaluate if CYP3A4 inhibition results in an increased frequency of AA-associated AEs.
Our study has a number of shortcomings worth mentioning, including its retrospective nature, and the relatively small sample size. Additionally, we were able to retrieve incomplete information only regarding medication changes, specifically prior to the start of AA therapy due to concerns about DDIs, or medication changes during AA therapy in order to address potential AEs. Hence, we could not verify if postulated DDIs resulted in AEs.
In conclusion, DDIs are recognized as a concern in cancer therapy overall, and specifically in elderly patients administered oral anticancer therapies, such as AA. Yet, there are only few dedicated pharmacokinetic studies using ‘model’ drugs to document whether postulated DDIs may translate into clinically significant risks for patients. In the absence of specific pharmacokinetic information for commonly prescribed drug combinations, DDI databases may present differing recommendations. Safe drug administration depends on awareness of DDIs, potential use of alternative medications with varying pharmacokinetic properties, and close collaboration between prescribing physicians, pharmacists, and other health care providers.
Authors: Vanessa S. Arciero1, Erica McDonald1, Urban Emmenegger1,2,3
Affiliations: 1Sunnybrook Odette Cancer Centre, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada, 2Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada, 3Institute of Medical Science, University of Toronto, 1 King’s College Circle, Toronto, ON M5S 1A8, Canada
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