484P - Drug-drug interactions in patients treated for cancer: A prospective study on clinical interventions

Date 27 September 2014
Event ESMO 2014
Session Poster Display session
Topics Anti-Cancer Agents & Biologic Therapy
Pharmacology
Presenter Roelof van Leeuwen
Citation Annals of Oncology (2014) 25 (suppl_4): iv146-iv164. 10.1093/annonc/mdu331
Authors R.W. van Leeuwen1, F.G.A. Jansman2, P.M.L.A. van den Bemt1, F. De Man1, F. Piran1, I. Vincenten1, A. Jager3, A.W. Rijneveld4, R. Mathijssen3, T. van Gelder5
  • 1Department Of Pharmacy, Erasmus University Medical Center, 3015 CE - Rotterdam/NL
  • 2Department Of Clinical Pharmacy, Deventer Hospital, Deventer/NL
  • 3Medical Oncology, Erasmus MC – Cancer Institute, 3015CE - Rotterdam/NL
  • 4Hematology, Erasmus MC – Cancer Institute, 3015CE - Rotterdam/NL
  • 5Department Of Pharmacy And Internal Medicine, Erasmus University Medical Center, 3015 CE - Rotterdam/NL

Abstract

Aim

Drug-drug interactions (DDIs) are of major concern in oncology, since cancer patients typically take many concomitant medications (Van Leeuwen et al, Lancet Oncol, in press). Some retrospective studies have been conducted to determine the prevalence of potential DDIs (PDDIs). However, prospective studies on DDIs needing interventions in cancer patients have not yet been performed. Therefore we investigated DDIs leading to an intervention proposed by a clinical pharmacologist in ambulatory cancer patients receiving oral and/or intravenous anticancer treatment. Potential determinants for performing interventions were also studied.

Methods

Patients starting with a new I.V. or oral anticancer treatment regimen were asked to participate. Data on demographic characteristics, use of co-medication, over-the-counter (OTC) drugs and co-morbidities were collected by the clinical pharmacologist during a structured interview with the patient. Subsequently, the patients' medication was checked for PDDIs by using drug interaction software. An expert team of 3 clinical pharmacologists evaluated the relevance of these identified PDDIs. If a PDDI was qualified as clinically relevant, an intervention was proposed to the treating physician. Several variables were studied as potential determinants for performing an intervention, e.g. number of drugs and number of comorbidities. Descriptive statistics and uni- and multivariate logistic regression analyses were performed.

Results

In this study 302 patients were included. The drug interaction software identified 603 PDDIs. Next to the intervention proposed by the (hemato)oncologists, an additional intervention was proposed by the expert team for 42 patients (14%). The number of comorbidities (adjusted odds ratio (OR): 1.4 (95% Confidence Interval (CI): 1.0-2.0)) and the number of OTC-drugs (adjusted OR: 1.4 (95% CI 1.1-1.8)) were identified as determinants.

Conclusions

Additional interventions due to DDIs are necessary in 14% of patients on anticancer therapy. More specific screening tools (e.g. one electronic medication prescribing system) are necessary in order to increase the efficiency of clinical pharmacologist DDI screening.

Disclosure

All authors have declared no conflicts of interest.