Potential drug interactions and side effects in an outpatient oncology clinic: a retrospective descriptive study

Assessment of drug-drug interactions among patients with hematologic malignancy: A clinical pharmacist-led study

INTRODUCTION

Patients with hematologic malignancies often receive multiple medications, leading to potential drug-drug interactions (DDIs). Identifying and managing these DDIs is crucial for ensuring patient safety and effective care. This study aimed to identify and describe DDIs and associated factors in hematologic malignancy patients.

METHODS

This prospective interventional study was conducted at a referral center and included hospitalized patients with hematologic malignancies who were receiving at least four concurrent medications. A pharmacist initially compiled a comprehensive list of all medications through patient interviews and medication reviews, and subsequently, identified and categorized potential DDIs using the Lexi-interact® and Micromedex® databases. The clinical pharmacist then evaluated the clinical impact of the identified DDIs in every individual patient and provided appropriate interventions to resolve them.

RESULTS

A total of 200 patients met the inclusion criteria for the study, with 1281 DDIs identified across 337 distinct types. The majority of identified DDIs exhibited major severity (52.1%) and pharmacokinetic mechanisms (50.3%), with an unspecified onset (79.4%) and fair evidence (67%). Of the identified DDIs, 81.1% were considered clinically significant, prompting 1059 pharmacotherapy interventions by the clinical pharmacist. Additionally, a significant relationship was observed between the number of drugs used during hospitalization and the occurrence of DDIs (P < 0.001, r = 0.633).

CONCLUSION

DDIs are highly prevalent among hospitalized patients with hematologic malignancies, with their occurrence increasing alongside the number of medications administrated. The intervention of a clinical pharmacist is crucial to evaluate the clinical impact of these DDIs and implement effective interventions for their management.

Mechanisms of lipopolysaccharide protection in tumor drug-induced macrophage damage

Malignant tumors contribute significantly to human mortality. Chemotherapy is a commonly used treatment for tumors. However, due to the low selectivity of chemotherapeutic drugs, immune cells can be damaged during antitumor treatment, resulting in toxicity. Lipopolysaccharide (LPS) can stimulate immune cells to respond to foreign substances. Here, we found that 10 ng/mL LPS could induce tolerance to antitumor drugs in macrophages without altering the effect of the drugs on tumor cells. Differentially expressed genes (DEGs) were identified between cells before and after LPS administration using transcriptome sequencing and found to be mainly associated with ATP-binding cassette (ABC)-resistant transporters and glutathione S-transferase (GST). LPS was shown by qRT-PCR and western blotting to promote the expression of ABCC1, GSTT1, and GSTP1 by 38.3 %, 194.8 %, and 27.0 %. Furthermore, three inhibitors (inhibitors of GST, glutathione synthesis, and ABCC1) were used for further investigation, showing that these inhibitors reduced macrophage survival rates by 44.0 %, 52.3 %, and 43.3 %, while the intracellular adriamycin content increased by 28.9 %, 42.9 %, and 51.3 %, respectively. These findings suggest that the protective mechanism of LPS on macrophages is associated with increased GST activity, the consumption of glutathione, and increased expression of ABCC1 protein. Therefore, LPS has a potential role in enhancing immunity.

Potential Drug Interactions in Hospitalized Hematologic Cancer Patients: New Update with New Chemotherapy Regimens

Objective

This cross-sectional study aimed to assess the frequency of potential drug-drug interactions (DDIs) and demographic correlates of moderate and major DDIs among patients with hematologic cancer at a referral hematology hospital in Iran.

Methods

In this study, for 6 months, all patients suffering from hematologic cancers admitted to the tertiary oncology hospital, Omid, Isfahan, were considered. Data from all medications prescribed to patients during hospitalization were analyzed using the online Lexicomp® drug interaction checker, recording all interactions classified by risk level: C, D, or X.

Findings

A total of 674 DDIs were detected in 109 patients. The prevalence of treatments with at least one clinically relevant interaction was 95%, being 57.9% for those at level C and 31.5% for levels D and X. According to the frequency, the main interaction was between aprepitant and corticosteroids, followed by the interaction between aprepitant and vincristine. The most common interaction between antineoplastic agents was between doxorubicin and cyclophosphamide. In terms of mechanism, most of DDIs (54.9%) were pharmacodynamics. Only the number of administered medications was associated with DDI occurrence.

Conclusion

Potential DDIs of moderate to major severity are common among patients with hematologic malignancies. This underscores the importance of implementing different strategies to mitigate this clinically significant risk.

The Prevalence of Drug-Drug Interactions and Reported Therapy Related Side Effects in Oncology Out-Patients

Objective: The use of multiple medications in cancer patients is unavoidable; thus, adverse drug-drug interactions are frequent. This study aims to assess the prevalence of potential drug interactions in oncology patients visiting the outpatient chemotherapy unit. Method: Demographic and health-related information of patients visiting an outpatient chemotherapy unit was recorded using a pre-prepared form. A comprehensive list of all concurrently used medications was compiled and checked for interactions with the Micromedex online drug interaction tool. Results: A total of 179 adult patients were included. We recorded an average of 9.3 drugs per patient with 79 patients using more than 10 drugs. A total of 1671 drugs including 303 chemotherapeutic agents were assessed for drug-drug interactions. A total of 374 interactions, of which 203 were significant, were recorded in 118 (65.9%) patients with an average of 3.2 interactions per patient. Only 46 major interactions were recorded for anticancer agents. Cyclophosphamide (n=13) and cisplatin (n=12) were involved in most interactions. The number of interactions correlated with the number of drugs used (p=.001) and the presence of comorbidities (p=.002). The presence of comorbidities increased the risk of interaction by 1.21 (p=.04). Recorded side effects were not correlated to drug interactions. Conclusion: Medication review in cancer patients is essential in establishing all medications used by patients. Routine assessment in terms of potential drug interactions and evaluation of these interactions by a qualified pharmacist may help in optimizing patient outcomes.

The Prevalence of Polypharmacy and Potential Drug-Drug Interactions among Iranian Cancer Patients: which Patients Were at Risk?

INTRODUCTION

Drug-Drug interactions (DDIs) are one of the considerable consequences of polypharmacy. Due to the influence of polypharmacy and drug interactions on cancer treatment and patients` health outcomes, the present study aimed to determine the prevalence of polypharmacy and potential DDIs among adult cancer patients in Kerman province, southeast of Iran.

METHODS

In this cross-sectional study, 315 cancer patients who referred to Kerman city oncology clinics were assessed in 2018. Data were collected through face-to-face interviews and medical charts were reviewed. Polypharmacy was defined as the use of at least five drugs simultaneously. Potential DDIs were checked using the "Drugs.com" online database. A bivariable and a multivariable logistic regression were used to determine the associated factors of outcome variables, polypharmacy status and potential DDI in SPSS software version 23.

RESULTS

Of 315 cancer patients, 191 patients (60.6%; 95% CI:54.9, 66) used at least five drugs during chemotherapy courses. The prevalence of potential DDIs was 59.6% (n = 140, 95% CI: 53.6-66.0. Experience co-morbid diseases (OR:6.60; 95%CI: 3.82, 11.42; P-value ≤0.0001), and positive metastatic status (OR:2.80; 95%CI: 1.62, 4.82; P-value ≤0.0001) could predict the polypharmacy during chemotherapy courses. Patients who suffered gastrointestinal cancers (OR:5.55; 95%CI: 2.26, 13.62; P-value ≤0.0001) and the number of prescribed or Over The Counter (OTC) drugs (OR:1.29; 95%CI: 1.12, 1.48; P-value <0.0001) predicted the occurrence of potential DDIs among cancer patients.

CONCLUSION

Regarding the high prevalence of polypharmacy and potential drug interactions among Iranian cancer patients during chemotherapy courses, it is advisable for physicians, nurses, and pharmacists to be vigilant to improve prescribing patterns. In addition, with intensive monitoring, alternative treatment strategies can be replaced.

Potential drug interactions between targeted oral antineoplastic agents and concomitant medication in clinical practice

OBJECTIVES

Our objective was to analyze potential drug interactions (PDIs) between targeted OAAs and concomitant therapy in clinical practice.

METHODS

A cross-sectional observational study was performed in cancer outpatients who started treatment with a targeted OAA between 1 December 2015 and 31 May 2019. PDIs were analyzed using the Lexicomp® and the database About Herbs®. PDIs were classified according to severity, risk, and reliability ratings and their underlying mechanism. Univariate and multivariate analysis were performed to identify risk factors associated with PDIs.

RESULTS

A total of 881 patients were included, of whom 50.9% had at least 1 PDI between the OAA and the concomitant medication. The factors associated with a higher risk of PDIs were polypharmacy (≥5 concomitant medicines) (OR = 3.64 (2.54-5.20), p < 0.001), type of tumor (prostate cancer [OR = not available, p < 0.001], chronic myelogenous leukemia [OR = 5.10 (1.08-24.05), p = 0.040], sarcoma [OR = 4.97 (1.05-23.55), p = 0.043]), and treatment with hormone therapies (OR = not available, p < 0.001).

CONCLUSION

A search of PDIs should be prioritized, especially in patients receiving targeted OAAs with risk factors, such as polymedication, prostate cancer, chronic myelogenous leukemia, sarcoma, and treatment with hormone therapies.

Cordia lutea L. Flowers: A Promising Medicinal Plant as Chemopreventive in Induced Prostate Carcinogenesis in Rats

The objective of this study was to evaluate the chemopreventive effect of the ethanolic extract of Cordia lutea flowers (EECL) on N-methyl-N-nitrosourea- (MNU), cyproterone-, and testosterone-induced prostate cancer in rats. 40 Holtzman male rats were used and assigned to 5 groups (n = 8). In Group I, rats received normal saline (10 mL/Kg); Group II: rats were induced for prostate cancer with cyproterone, testosterone, and NMU; Groups III, IV, and V: rats received EECL daily, at doses of 50, 250, and 500 mg/kg body weight, respectively. After the period of treatment, animals were sacrificed by an overdose of pentobarbital and blood samples were collected for determination of prostate-specific antigen (PSA). The prostate was dissected and weighed accurately. The ventral lobe of the prostate was processed for histopathology analysis. The somatic prostate index decreased with EECL at dependent dose, from 0.34 ± 0.04 to 0.23 ± 0.05 (P < 0.05). The PSA levels also decreased significantly at doses of 250 and 500 mg/kg. Histopathological analysis showed a decrease in the number of prostatic layers with high-grade prostatic intraepithelial neoplasia (HG-PIN) and low-grade prostatic intraepithelial neoplasia (LG-PIN) at the dose of 500 mg/kg. The ethanolic extract of Cordia lutea flowers had a chemopreventive effect on induced prostate cancer in rats.

Drug-related problems with targeted/immunotherapies at an oncology outpatient clinic

Background

Some studies in the literature describe drug-related problems in patients with cancer, although few studies focused on patients receiving targeted chemotherapy and/or immunotherapy. To identify the incidence of drug-related problems in patients receiving targeted chemotherapy and/or immunotherapy, and demonstrate the impact of a clinical pharmacist in an outpatient oncology care setting.

Methods

Prospective study was conducted in a hospital outpatient oncology clinic between October 2015 and March 2016. Patients greater than 18 years old receiving cetuximab, nivolumab, ipilimumab, or pembrolizumab were included in the study and monitored over a three-month period by a clinical pharmacist. Drug-related problems were analyzed using the Pharmaceutical Care Network Europe classification system. The main outcome measures were the frequency and causes of drug-related problems and the degree of resolution achieved through the involvement of a clinical pharmacist.

Results

A total of 54 patients (mean age: 57 ± 12 years) were included. There were 105 drug-related problems and 159 associated causes. Among the planned interventions (n = 149), 92 interventions were at the patient-level with 88 (96%) being accepted by the doctors. This resulted in 68 (65%) drug-related problems being completely resolved and 9 (8.6%) being partially resolved. The most common drug-related problem identified was “adverse drug event” (n = 38, 36%). Of the 105 drug-related problems, 63 (60%) related to targeted chemotherapy and/or immunotherapy with 34 (54%) classified as an “adverse drug event.”

Conclusion

Adverse drug events were the most common drug-related problems in patients with cancer. The involvement of a clinical pharmacist improved the identification of drug-related problems and helped optimize treatment outcomes in patients receiving targeted chemotherapy/immunotherapy.

Potential drug-drug interactions in hospitalised haematological patients

Background Frequently, haematological patients undergo highly complex and intensive treatment protocols, so a high risk of drug-drug interactions could be expected. Objectives To determine prevalence of clinically relevant drug-drug interactions, to identify the most frequent drug-drug interactions and associated risk factors. Methods A prospective, observational and descriptive study was carried out from November 2012 to February 2013. Twice a week, every patient's treatment sheet was collected. Each medication list was screened through two databases: Thomson MicromedexTM and Drug Interaction FactsTM. All identified potential drug-drug interactions with a moderate or higher severity rating were recorded. Summary statistics were used to describe patient and disease characteristics, most often prescribed drugs, and frequency, types and classification of drug-drug interactions. Multiple logistic regression models were used to identify risk factors associated with drug-drug interactions. Results A total of 2061 drug-drug interactions were detected in 317 treatment sheets from 58 patients. The prevalence of treatment sheets with drug-drug interactions by Micromedex and Drug Interaction Facts databases were 74.1% and 56.8%, respectively. Azole antifungals, immunosuppressive drugs, antiemetics, antidepressants, acid suppressants and corticosteroids were the most frequent involved drugs. In multivariate analysis, the main risk factor associated with increased odds for drug-drug interactions was a higher number of non-antineoplastic drugs. Conclusions The prevalence of drug-drug interactions was common, with immunosuppressant and azole antifungal agents being the most commonly involved drugs. The factor having the greatest influence on drug-drug interactions was a higher number of non-antineoplastic drugs.

Pharmacotherapy follow-up of key points in the safety of oral antineoplastic agents

We assessed the impact of a pharmacotherapy follow-up programme on key safety points [adverse events (AE) and drug administration] in outpatients treated with oral antineoplastic agents (OAA). We performed a comparative, interventional, quasi-experimental study of outpatients treated with OAA in a Spanish hospital to compare pre-intervention group patients (not monitored by pharmacists during 2011) with intervention group patients (prospectively monitored by pharmacists during 2013). AE data were collected from medical records. Follow-up was 6 months, and 249 patients were included (pre-intervention, 115; intervention, 134). After the first month, AE were detected in 86.5% of patients in the pre-intervention group and 80.6% of patients in the intervention group, P = 0.096. During the remaining months, 79.0% patients had at least one AE in the pre-intervention group compared with 78.0% in the intervention group, P = 0.431. AE were more prevalent with sorafenib and sunitinib. In total, 173 drug interactions were recorded (pre-intervention, 80; intervention, 93; P = 0.045). Drug interactions were more frequent with erlotinib and gefitinib; food interactions were more common with sorafenib and pazopanib. Our follow-up of cancer outpatients revealed a reduction in severe AE and major drug interactions, thus helping health professionals to monitor the safety of OAA.

Oncology nurses awareness of drug interactions

Objective:

The aim of this study was to determine oncology nurses awareness of drug interactions.

Methods:

This descriptive study was conducted with nurses working in the oncology clinics who are a member of Oncology Nursing Association of Turkey. A total of 115 nurses (response rate %20) were responded to the online survey that consists of 28 questions.

Results:

The mean age of the nurses was 33 ± 6.8. The majority of nurses work in university hospital (60%) as a clinical nurse (62.6%) and have a Bachelor Degree in Nursing (63.5%). The mean working years in oncology was 4 years. Half of them stated receiving information on drug interactions mostly through in-service education and courses/congresses in last 5 years. The majority of them (84.3%) indicated that they are considering the possibility of drug interactions when they are scheduling the medication administration time. More than half of the responders (59.1%) encountered drug interactions; however, few explored drug interactions with food, drinks, and nutritional supplements. Their practices to assess possibility of drug interactions were reviewing the drug prospectus (78.3%); consulting with their colleagues (58.3%) and searching on the available website (42.6%) and looking at the drug interaction (39.1%). More than half (65.2%) stated lack of any system to identify drug interactions in their workplace. Nearly half of them indicated to including the drug interaction into patient education mostly for food-drug (73.9%) and drug-drug (63.5%) interactions.

Conclusions:

Almost all indicated the needs for further education on drug interactions and suggested to have guideline/packet guide.