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Indian Journal of Medical and Paediatric Oncology
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ORIGINAL ARTICLE
Year : 2018  |  Volume : 39  |  Issue : 4  |  Page : 436-442  

Assessment of potential drug–drug interactions in an oncology unit of a tertiary care teaching hospital


1 Department of Pharmacy Practice, NGSM Institute of Pharmaceutical Sciences, Deralakatte, Mangaluru, Karnataka, India
2 Department of Radiology and Oncology, K.S. Hegde Medical Academy, Justice K.S. Hegde Charitable Hospital, Nitte University, Paneer, Deralakatte, Mangaluru, Karnataka, India

Date of Web Publication15-Nov-2018

Correspondence Address:
Dr. Uday Venkat Mateti
Department of Pharmacy Practice, NGSM Institute of Pharmaceutical Sciences, Nitte University, Paneer, Deralakatte, Mangaluru - 575 018, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijmpo.ijmpo_93_17

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  Abstract 

Context: Drug interactions are more common in cancer patients because they consume several medicines such as hormonal substances, anticancer drugs, and adjuvant drugs to treat comorbidities. Objectives: To assess the pattern of potential drug–drug interactions (pDDIs) in an oncology unit of a tertiary care teaching hospital. Materials and Methods: A prospective observational study was carried out for 8 months (August 2016 to March 2017). Data on drugs were collected by reviewing the patients' medical records. The drug interactions fact software version such as Micromedex electronic database system, drugs.com interaction checker, and Medscape multidrug interaction checker tool were used to identify and analyze the pattern of pDDIs. Results: A total of 180 patients were enrolled during the study period. Among them, 152 study patients had 84.44% of pDDIs. Male predominance (64.4%) was noted over female (35.6%). According to the severity of classification of pDDIs, majority of them were moderate (63.1%) followed by major (26.1%) and minor (10.1%) interactions. The interactions that potentially cause QT interval prolongation and irregular heartbeat were the common outcomes of pDDIs. Conclusions: The incidence of pDDIs among cancer patients was 84.44%. The most common interacting drug pair in the study population was found to be dexamethasone + aprepitant [41 (26.9%)] followed by cisplatin + dexamethasone [32 (21.05%)] and other interacting pairs. To avoid harmful effects, screening of pDDIs should take place before administering the therapy.

Keywords: Antineoplastic agents, chemotherapy, drug interactions


How to cite this article:
Vayalil RK, Shetty K J, Mateti UV. Assessment of potential drug–drug interactions in an oncology unit of a tertiary care teaching hospital. Indian J Med Paediatr Oncol 2018;39:436-42

How to cite this URL:
Vayalil RK, Shetty K J, Mateti UV. Assessment of potential drug–drug interactions in an oncology unit of a tertiary care teaching hospital. Indian J Med Paediatr Oncol [serial online] 2018 [cited 2018 Dec 15];39:436-42. Available from: http://www.ijmpo.org/text.asp?2018/39/4/436/245515


  Introduction Top


Drug interactions are more common in cancer patients because they consume several medications such as hormonal substances, anticancer drugs, and adjuvant drugs to treat comorbidities.[1],[2] The risk of drug–drug interactions (DDIs) increases in elderly patients due to their increased age, physiological changes, and comorbidities.[3] Cytotoxic drugs have narrow therapeutic index, so increases or decreases in the cytotoxic activity result in toxic effect.[4]

Approximately, 60% of the patients undergoing treatment for cancer may develop at least one DDI, of which 30% require medical intervention. QT prolongation, gastrointestinal (GI) toxicity, and central nervous system depression are the most common results of pharmacodynamic DDIs. Most of these potential drug–drug interactions (pDDIs) are left unnoticed or not given proper intervention due to the lack of healthy professional relationship between medical oncologists, pharmacists, and general practitioners.[5]

Before starting chemotherapy, it is necessary to check the pDDIs for the successful usage of drug therapy and to improve the quality of life of the patient. Clinical pharmacists require good knowledge in monitoring DDIs and should advise patients regarding the proper use of drugs. Hence, the present study was aimed to assess the patterns of pDDIs in the oncology unit of a tertiary care teaching hospital.


  Materials and Methods Top


A prospective observational study was carried out for 8-month period (from August 2016 to March 2017) in the inpatient unit of oncology unit at Justice K.S. Hegde Charitable Hospital, Mangaluru. Before starting the study, the study protocol was approved by the Institutional Ethical Committee (Ref no: NIST. EC/EC/65/2016-2017). Either patients of gender with >18 years and diagnosed with solid tumor or hematological malignancy were included in the study. Patients who referred to oncology department for consultation, patients who are not willing to participate, pregnant and lactating women were excluded from the study.

The data were collected from patients' treatment chart. Patient medication details were collected on the daily basis and recorded in the drug interactions' documentation form. The pDDIs were those not observed in the patients but they give a signal for the detection of interactions. Micromedex electronic database system, drugs.com interaction checker, and Medscape multidrug interaction checker tool were used to identify the pattern of pDDIs.[6],[7] Micromedex contains a separate section on DDIs known as the Drug-REAX System, Denver, Colorado State, US. On entering the drugs one by one, the program lists the possible interactions and categorizes interactions according to their interaction effect, severity (major, moderate, and minor), onset (rapid and delayed), and documentation status (excellent, good and fair). Medscape and drugs.com contain a separate tool for detecting interactions known as the multidrug interaction checker tool. On entering the drugs one by one, the program lists the possible interactions and categorizes interactions according to their interaction effect, severity (major, moderate, and minor), and management. The required guidance to manage particular pDDI was provided to the physician by referring information provided in drug interaction tools.

Statistical analysis

Descriptive statistics were used to describe the demographic characteristic of patients, cancer type, treatment, comorbidities, number of drugs prescribed per patient, and classification of drug interactions. Data analysis was carried out using the Statistical Package for Social Studies (SPSS) version 16 (SPSS Inc., South Asia, Bengaluru).


  Results Top


A total of 180 patients were included during the study period. Among them, 152 study patients had 84.44% of pDDIs. Male predominance (64.4%) was noted over female (35.6%). The mean age of the study population was 53.6 ± 12.4 years. Most of the patients were in the age group of 50–59 years (33.3%) followed by 60–69 years (23.9%). Majority of the patients had no family history of cancer (81.7%) and there was no history of comorbidities (83.8%). Hypertension [11 (7.2%)] was found to be the most common comorbidity observed in cancer patients with pDDIs followed by diabetes mellitus 9 (5.9%).

Out of 180 patients, 18.3% of patients had a history of smoking followed by alcohol and tobacco usage. Majority of the patients were hospitalized for 1–9 days. The median duration of the hospital stay was found to be 9 days. Out of 180 patients, breast cancer [24 (15.7%)] with pDDIs was the most common cancer type in the study population. The median number of medications received by the study population was found to be eight per day. Most of the pDDIs were observed in patients who had undergone 6–10 cycles of chemotherapy [70 (67.3%)], followed by 11–15 cycles [26 (14.4%)]. Patient characteristics and statistical significance of the results are summarized in [Table 1].
Table 1: Demographics of the study population

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Among anticancer agents that cause pDDIs, alkylating agent + corticosteroids [32 (21.05%)] were found to be the most common interacting group in cancer patients followed by corticosteroids + mitotic inhibitors [31 (20.3%)], alkylating + mitotic inhibitors [26 (17.1%)] and the other interacting groups are summarized in [Table 2]. Similarly, in supportive care agents, corticosteroids + aprepitant [34 (22.3%)] were found to be the common interacting pair in cancer patients followed by histamine H2 antagonist + analgesics, 19 (12.5%), and the other interacting groups are described in [Table 3].
Table 2: Frequency of potential drug-drug interactions involving anticancer drugs (n=152)

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Table 3: Frequency of potential drug-drug interactions involving supportive care drugs (n=152)

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Out of 152 patients, 659 pDDIs were observed in the study. The most common interacting drug pair in the study population was found to be dexamethasone + aprepitant [41 (26.9%)] followed by cisplatin + dexamethasone [32 (21.05%)] the other interacting pairs are summarized in [Table 4] and [Table 5]. QT interval prolongation [62 (40.1%)] was found to be the most common pDDI outcome in cancer patients.
Table 4: Interacting pair of anticancer drugs with outcome and severity (n=152)

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Table 5: Interacting pair of supportive care drugs with outcome and severity (n=152)

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According to the severity of drug interactions, 416 (63.1%) of pDDIs were moderate followed by major [172 (26.1%)] and minor [67 (10.1%)]. Among the 659 interactions, 563 (85.4%) of pDDIs did not specify their onset [23 (3.4%)] were delayed onset, and 73 (11%) were rapid onset. The documentation levels of significance of pDDIs were fair [556 (84.3%)] followed by good [66 (10%)] and rapid [37 (5.6%)].


  Discussion Top


Drug–drug interactions (DDIs) occur when one drug increases or decreases the efficacy of another drug, when both are administered together. When the interaction causes an increase in the effect of one or both of the drugs, that interaction is called synergistic effect. The opposite effect to synergetic effect is termed antagonism.[8]

The current study analyzed the pattern of pDDIs and their assessment among cancer patients. In this study, it was noticed that male (64.4%) patients constituted a major proportion of the study population than females (35.6%). Similar result was shown in the study conducted by Leeuwen et al.[9] where it was reported that males (55%) were higher than females (45%). However, contradictory results were shown in the study conducted by Ussai et al.,[10] in which female (69%) patients constituted the major proportion of the study population than male patients (31%).

Majority of the pDDIs were seen in patients in the age group of 50–59 years (33.5%) in our study. The study conducted by Riechelmann et al.[11] showed the similar results, where the drug interactions were common in the age group of 58 years. Our study results are in contrast to the study conducted by Ko et al.,[12] in which the maximum number of drug interactions in the age group was >65 years. This may be because organ dysfunction and comorbid conditions are more likely to be associated with older age. This further increases their risk for developing pDDIs.

In the present study, the most common tumor was found to be breast cancer (14.4%). A comparable result was shown in the study conducted by van Leeuwen et al.,[13] where it was found to be 17.2%. However, Mouzon et al.[14] concluded that higher incidence was observed with gastrointestinal cancer (27.9%). These findings were contradictory to the current study results.

The median number of medications received per patient in the present study was found to be 8 (range 1–21). A comparable result of median value of 9 in the range of 2–22 drugs was observed in the study conducted by van Leeuwen et al.[13] However, comparatively lesser median value of 5 was reported by Riechelmann et al.,[11] making it not comparable with the present study results.

In this study, the most frequently prescribed anticancer agents were cisplatin (14.5%) and docetaxel (1.9%). The study results were comparable to the conducted by Mouzon et al.,[14] where it was found to be cisplatin (22.1%) and docetaxel (13%).

In the current study, cisplatin [49 (32.2%)] was the most frequently drug involved in pDDIs. A comparable result was found in the study conducted by Mouzon et al.,[14] where it was found that cisplatin (22.1%) was the most frequently involved anticancer drug in pDDIs.

Another important finding in the study was the incidence of pDDIs that may result in adverse events which include QT interval prolongation (40.1%) and GI toxicity (9.2%). A comparable result was found in the study conducted by Leeuwen et al.,[9] where it was found to be QT interval prolongation (16.1%) and GI toxicity (11.2%).

In the present study, pain related to the cancer was treated with nonsteroidal anti-inflammatory drugs and opioids. These findings were consistent with the study conducted by Espinosa et al.[15] and van Leeuwen et al.[13]

The incidence of pDDIs in our hospital during the study period was 84.4%. Contradictory results were shown in the study conducted by Riechelmann et al.,[11] where it was reported to be 31.34%. This is due to that the patients involved in the study had more comorbidities; therefore, a large number of drugs were administered.

According to the severity of pDDIs, the study showed that 63.1% were moderate followed by major (26.1%) and minor interactions (10.1%). These findings were comparable to the study conducted by Leeuwen et al.,[9] where it was reported that most of the interactions were major (33%) followed by moderate (60.3%) and minor (6%).


  Conclusion Top


The present study shows that cancer patients are at a high risk of pDDIs. The incidence of pDDIs among cancer patients was 84.44%. The most common interacting drug pair in the study population was found to be dexamethasone + aprepitant [41 (26.9%)] followed by cisplatin + dexamethasone [32 (21.05)] and other interacting pairs. According to the severity of classification of pDDIs, majority of them were moderate (63.1%) followed by major (26.1%) and minor (10.1%) interactions. QT interval prolongation (40.1%) and irregular heartbeat (24.3%) were the most common outcomes of the pDDIs in cancer patients. To avoid harmful effects, screening of pDDIs should take place before administering the therapy. The physician and pharmacist must collaborate for the early detection and prevention of DDIs and their related harmful effects. Screening of pDDIs should take place before starting the therapy to avoid potential drug interactions. Clinical pharmacist in health-care team has a certain role in detecting interactions and making recommendations, to reduce medication-related problem and effective drug therapy to improve the quality of life in these patients.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
Köhler GI, Bode-Böger SM, Busse R, Hoopmann M, Welte T, Böger RH. Drug-drug interactions in medical patients: Effects of in-hospital treatment and relation to multiple drug use. Int J Clin Pharmacol Ther 2000;38:504-13.  Back to cited text no. 1
    
2.
Yancik R, Ries LA. Aging and cancer in America. Demographic and epidemiologic perspectives. Hematol Oncol Clin North Am 2000;14:17-23.  Back to cited text no. 2
    
3.
Hines LE, Murphy JE. Potentially harmful drug-drug interactions in the elderly: A review. Am J Geriatr Pharmacother 2011;9:364-77.  Back to cited text no. 3
    
4.
Scripture CD, Figg WD. Drug interactions in cancer therapy. Nat Rev Cancer 2006;6:546-58.  Back to cited text no. 4
    
5.
Ekincioglu AB, Demirkan K, Keskin B, Aslantas O, Ozdemir E. Potential drug interactions and side effects in an outpatient oncology clinic: A retrospective descriptive study. Eur J Hosp Sci Pract 2014;21:216-21.  Back to cited text no. 5
    
6.
7.
Medscape Multidrug Interaction Checker. Available from: http://www.reference.medscape.com/drug-interactionchecker. [Last accessed on 2017 Mar 18].  Back to cited text no. 7
    
8.
Riechelmann RP, Del Giglio A. Drug interactions in oncology: How common are they? Ann Oncol 2009;20:1907-12.  Back to cited text no. 8
    
9.
Leeuwen RW, Jansman FG, Deeman F, Piran F, Vencenten I, Rijnevld AW, et al. Drug-drug interactions in patients treated for cancer: A prospective study on clinical interventions. Ann Oncol 2010;25:146-64.  Back to cited text no. 9
    
10.
Ussai S, Petelin R, Giordano A, Malinconico M, Cirillo D, Pentimalli F, et al. A pilot study on the impact of known drug-drug interactions in cancer patients. J Exp Clin Cancer Res 2015;34:89.  Back to cited text no. 10
    
11.
Riechelmann RP, Tannock IF, Wang L, Saad ED, Taback NA, Krzyzanowska MK. Potential drug interactions and duplicate prescriptions among cancer patients. J Natl Cancer Inst 2007;99:592-600.  Back to cited text no. 11
    
12.
Ko Y, Tan SL, Chan A, Wong YP, Yong WP, Ng RC, et al. Prevalence of the coprescription of clinically important interacting drug combinations involving oral anticancer agents in Singapore: A retrospective database study. Clin Ther 2012;34:1696-704.  Back to cited text no. 12
    
13.
van Leeuwen RW, Brundel DH, Neef C, van Gelder T, Mathijssen RH, Burger DM, et al. Prevalence of potential drug-drug interactions in cancer patients treated with oral anticancer drugs. Br J Cancer 2013;108:1071-8.  Back to cited text no. 13
    
14.
Mouzon A, Kerger J, D'Hondt L, Spinewine A. Potential interactions with anticancer agents: A cross-sectional study. Chemotherapy 2013;59:85-92.  Back to cited text no. 14
    
15.
Espino MF, Carrasco D, Salinas S. Potential drug-drug interactios in hospitalised haematological patients. Int J Clin Pharma 2016;3:512-620.  Back to cited text no. 15
    



 
 
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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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