Prevalence of potential drug-drug interactions in bone marrow transplant patients

Prevalence and clinical significance of potential drug-drug interactions among lung transplant patients

Background: Drug-drug interactions (DDIs) are a major but preventable cause of adverse drug reactions. There is insufficient information regarding DDIs in lung transplant recipients. Objective: This study aimed to determine the prevalence of potential DDIs (pDDIs) in intensive care unit (ICU) lung transplant recipients, identify the real DDIs and the most frequently implicated medications in this vulnerable population, and determine the risk factors associated with pDDIs. Methods: This retrospective cross-sectional study included lung transplant recipients from January 2018 to December 2021. Pertinent information was retrieved from medical records. All prescribed medications were screened for pDDIs using the Lexicomp® drug interaction software. According to this interaction software, pDDIs were classified as C, D, or X (C = monitor therapy, D = consider therapy modification, X = avoid combination). The Drug Interaction Probability Scale was used to determine the causation of DDIs. All statistical analysis was performed in SPSS version 26.0. Results: 114 patients were qualified for pDDI analysis, and total pDDIs were 4051. The most common type of pDDIs was category C (3323; 82.0%), followed by D (653; 16.1%) and X (75; 1.9%). Voriconazole and posaconazole were the antifungal medicine with the most genuine DDIs. Mean tacrolimus concentration/dose (Tac C/D) before or after co-therapy was considerably lower than the Tac C/D during voriconazole or posaconazole co-therapy (p < 0.001, p = 0.027). Real DDIs caused adverse drug events (ADEs) in 20 patients. Multivariable logistic regression analyses found the number of drugs per patient (OR, 1.095; 95% CI, 1.048-1.145; p < 0.001) and the Acute Physiology and Chronic Health Evaluation II (APACHE Ⅱ) score (OR, 1.097; 95% CI, 1.021-1.179; p = 0.012) as independent risk factors predicting category X pDDIs. Conclusion: This study revealed a high incidence of both potential and real DDIs in ICU lung transplant recipients. Immunosuppressive drugs administered with azole had a high risk of causing clinically significant interactions. The number of co-administered drugs and APACHE Ⅱ score were associated with an increased risk of category × drug interactions. Close monitoring of clinical and laboratory parameters is essential for ensuring successful lung transplantation and preventing adverse drug events associated with DDIs.

Evaluation of the quality of life of adult patients admitted to the bone marrow transplantation unit

INTRODUCTION

The complexity of treatment and extended therapy duration associated with bone marrow transplantation directly affect the psychological well-being of the patients, create anxiety, and reduce their quality of life. The aim of our study was to evaluate the quality of life of patients admitted to the bone marrow transplantation unit.

METHODS

This prospective and descriptive study was conducted between January and June 2021 in an adult BMT unit in Turkey. The sociodemographic characteristics of the patients were recorded. The patient's quality of life was measured twice using the Functional Assessment of Cancer Therapy-Bone Marrow Transplantation (FACT-BMT) scale at the beginning of the study and 30 days later. SPSS 15 was used for the analysis.

RESULTS

A total of 40 patients were included in the study. The mean age was 46 years. Most of the patients were diagnosed with multiple myeloma and 58% had at least one comorbid disease. Most of the patients (78%) were receiving myeloablative therapy. High dose melphalan regimen was the most commonly applied regimen (25%). Thrombocytopenia was the most common side effect (14%). Although there was no change in the quality of life, it was found that the social/family well-being scores increased (p < 0.05).

CONCLUSIONS

In our study, it was observed that the number of comorbid diseases was higher in patients with bone marrow transplantation. The incidence of side effects may be high in these patients. We believe that clinical pharmacists have an important role in monitoring adverse effects and improving the quality of life in bone marrow transplantation units.

Comprehensive Physiologically Based Pharmacokinetic Model to Assess Drug-Drug Interactions of Phenytoin

Regulatory agencies worldwide expect that clinical pharmacokinetic drug-drug interactions (DDIs) between an investigational new drug and other drugs should be conducted during drug development as part of an adequate assessment of the drug's safety and efficacy. However, it is neither time nor cost efficient to test all possible DDI scenarios clinically. Phenytoin is classified by the Food and Drug Administration as a strong clinical index inducer of CYP3A4, and a moderate sensitive substrate of CYP2C9. A physiologically based pharmacokinetic (PBPK) platform model was developed using GastroPlus® to assess DDIs with phenytoin acting as the victim (CYP2C9, CYP2C19) or perpetrator (CYP3A4). Pharmacokinetic data were obtained from 15 different studies in healthy subjects. The PBPK model of phenytoin explains the contribution of CYP2C9 and CYP2C19 to the formation of 5-(4'-hydroxyphenyl)-5-phenylhydantoin. Furthermore, it accurately recapitulated phenytoin exposure after single and multiple intravenous and oral doses/formulations ranging from 248 to 900 mg, the dose-dependent nonlinearity and the magnitude of the effect of food on phenytoin pharmacokinetics. Once developed and verified, the model was used to characterize and predict phenytoin DDIs with fluconazole, omeprazole and itraconazole, i.e., simulated/observed DDI AUC ratio ranging from 0.89 to 1.25. This study supports the utility of the PBPK approach in informing drug development.

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.

Real clinical impact of drug-drug interactions of immunosuppressants in transplant patients

The main objective was to determine the prevalence of real drug-drug interactions (DDIs) of immunosuppressants in transplant patients. We conducted a prospective, observational 1-year study at a tertiary hospital, including all transplanted patients. We evaluated data from monitoring blood concentrations of immunosuppressive drugs and adverse drug events (ADEs) caused by DDIs. The DDIs were classified as C, D, or X according to their Lexi-Interact rating (C = monitor therapy, D = consider therapy modification, X = avoid combination). The clinical importance of real DDIs was expressed in terms of patient outcomes. The causality of DDIs was determined using Drug Interaction Probability Scale. The data were analyzed using Statistical Package for Social Sciences v. 25.0. A total of 309 transplant patients were included. Their mean age was 52.0 ± 14.7 years (18-79) and 69.9% were male. The prevalence of real DDIs was 21.7%. Immunosuppressive drugs administered with antifungal azoles and tacrolimus (TAC) with nifedipine have a great clinical impact. Real DDIs caused ADEs in 22 patients. The most common clinical outcome was nephrotoxicity (1.6%; n = 5), followed by hypertension (1.3%; n = 4). Suggestions for avoiding category D and X DDIs included: changing the immunosuppressant dosage, using paracetamol instead of non-steroidal anti-inflammatory drugs, and interrupting atorvastatin. The number of drugs prescribed and having been prescribed TAC was associated with an increased risk of real DDIs. There are many potential DDIs described in the literature but only a small percentage proved to be real DDIs, based on the patients´ outcomes.

Predicting the presence and mechanism of busulfan drug-drug interactions in hematopoietic stem cell transplantation using pharmacokinetic interaction network-based molecular structure similarity and network pharmacology

PURPOSE

This study aimed to predict the presence and mechanism of busulfan drug-drug interactions (DDIs) in hematopoietic stem cell transplantation (HSCT) using pharmacokinetic interaction (PKI) network-based molecular structure similarity and network pharmacology.

METHODS

Logistic function models were established to predict busulfan DDIs based on the assumption that an approved drug tends to interact with the drug used in HSCT (DH) if structurally similar to the drugs in the PKI network of the DH. The PKI network of the DH represented the association between drugs and the proteins related to the PK of the DH. The most appropriate model was applied to predict busulfan DDIs in HSCT. Candidate targets for busulfan DDIs and their interacting were identified by network pharmacology.

RESULTS

Six of the top ten predicted busulfan DDIs were clinically relevant and involved voriconazole, fludarabine, itraconazole, cyclophosphamide, metronidazole, and melphalan. Candidate targets for these DDIs were CYP450s (3A4, 2B6, 2C9, and 2C19), GSTs (GSTA1, GSTP1, GSTT1, and GSTM1), and ABC transporters (ABCB1, ABCC1, ABCC2, and ABCC3), in the targets of drug-induced liver injury (DILI). The networks of interacting proteins and candidate targets indicated the regulatory potential of pregnane X receptor (PXR), as a nuclear receptor. Enrichment analysis showed the metabolism of drugs and xenobiotics, glutathione metabolism, and bile secretion associated with busulfan DDIs and DILI.

CONCLUSIONS

This study has successfully predicted busulfan DDIs in HSCT through PKI-based molecular structure similarity. The mechanism of busulfan DDI and DILI was attributed mostly to CYP450s, GSTs, and ABC transporters, and PXR was identified as a potential target.

Potential drug-drug interactions associated with adverse clinical outcomes and abnormal laboratory findings in patients with malaria

BACKGROUND

Hospitalized patients with malaria often present with comorbidities or associated complications for which a variety of drugs are prescribed. Multiple drug therapy often leads to drug-drug interactions (DDIs). Therefore, the current study investigated the prevalence, levels, risk factors, clinical relevance, and monitoring parameters/management guidelines of potential DDIs (pDDIs) among inpatients with malaria.

METHODS

A retrospective cohort study was carried out at two tertiary care hospitals. A total of 398 patients' profiles were evaluated for pDDIs using the Micromedex Drug-Reax^®. Odds ratios were calculated to identify the strength of association between presence of DDIs and potential risk factors via logistic regression analysis. Further, the clinical relevance of frequent pDDIs was investigated.

RESULTS

Of 398 patients, pDDIs were observed in 37.2% patients, while major-pDDIs in 19.3% patients. A total of 325 interactions were found, of which 45.5% were of major- and 34.5% moderate-severity. Patients with the most common pDDIs were found with signs/symptoms and abnormalities in laboratory findings representing nephrotoxicity, hepatotoxicity, QT interval prolongation, and reduced therapeutic efficacy. The following drug pairs reported the highest frequency of adverse events associated with the interactions; calcium containing products-ceftriaxone, isoniazid-rifampin, pyrazinamide-rifampin, isoniazid-acetaminophen, and ciprofloxacin-metronidazole. The adverse events were more common in patients prescribed with the higher doses of interacting drugs. Multivariate regression analysis showed statistically significant association of pDDIs with 5-6 prescribed medicines (p = 0.01), > 6 prescribed medicines (p < 0.001), > 5 days of hospital stay (p = 0.03), and diabetes mellitus (p = 0.04).

CONCLUSIONS

PDDIs are commonly observed in patients with malaria. Healthcare professional's knowledge about the most common pDDIs could help in preventing pDDIs and their associated negative effects. Pertinent clinical parameters, such as laboratory findings and signs/symptoms need to be checked, particularly in patients with polypharmacy, longer hospital stay, and diabetes mellitus.

Clinical pharmacy in onco-hematology and bone marrow transplant: A valuable contribution to improving patient safety

INTRODUCTION

It is known that clinical pharmacists intercept prescribing errors and contribute to patient safety in several medical specialties. The aim of this study was to identify, quantify and classify prescribing errors and pharmacist interventions carried out in onco-hematology and bone marrow transplant inpatient units.

METHODS

This was a prospective and quantitative study, conducted from February 2018 to July 2018 in onco-hematology and bone marrow transplant inpatient units of a tertiary teaching hospital in Brazil. A pharmacist detected prescribing errors and performed interventions. The type and incidence of prescribing errors, error severity, type of pharmacist interventions, potential impact of interventions in patient care, and intervention acceptance rates were evaluated.

RESULTS

A total of 1172 prescriptions were evaluated, 9% of them contained errors (total of 135 errors), and the most common error was related to prescribing the wrong dose (31.8%). Wrong dose and omission of drug were the two most frequent errors in onco-hematology, while wrong dose followed by inappropriate dilution were the most frequent in bone marrow transplantation. The pharmacist performed 135 interventions and the most common intervention was related to the treatment regimen (41.5%). Serious errors and very significant pharmacist interventions were the most frequent in both inpatient units. The acceptance rate of pharmacist interventions was high (90%).

CONCLUSIONS

Clinical pharmacy improves patient safety and quality of care in onco-hematology and bone marrow transplant inpatient units.

Potential drug-drug Interactions in hospitalized cancer patients: A report from the Middle-East

INTRODUCTION

Patients suffering from solid tumors use a wide range of cytotoxic drugs. In this study, we aimed to detect, document, and descriptively analyze the potential drug-drug interactions in hospitalized solid tumor's patients in a Middle Eastern referral oncology-hematology University-affiliated hospital.

MATERIALS AND METHODS

In this cross-sectional study, the medical record of solid tumor's patients who were admitted to the referral oncological center in Isfahan, Iran, during the six months period (2018) were considered. We included all patients who had received at least two chemotherapy or nonchemotherapy drugs simultaneously. The potential drug-drug interactions between chemotherapy and nonchemotherapy drugs were evaluated with Lexi-Interact ver.1.1 online software.

RESULTS

During the study period, a total of 141 cancer patients were recruited, and their drug therapy regiment was thoroughly analyzed. We detected 227 drug-drug interactions with moderate or major severity out of included patients in which 96, 71, 32, and 28 interactions were in the category of C, D, B, and X, respectively. One hundred and fourteen patients (80.8%) encountered at least one potential drug-drug interactions during their hospitalization. Mechanistically, most of drug-drug interactions (56.4%) were pharmacodynamics. Interaction between granisetron and metoclopramide were the top 10 detected interaction (11.4%). The interaction between docetaxel and carboplatin was the most frequent drug-drug interactions between oncology drugs (2.6% of total drug-drug interactions).

CONCLUSION

Potentially moderate or major drug-drug interactions frequently occur among solid tumor's cancer patients necessitate the establishment of a clinical pharmacy service for providing relevant pharmacotherapy consultations to prevent this potentially serious concern.

Potential Drug-drug Interactions at a Referral Pediatric Oncology Ward in Iran: A Cross-sectional Study

Incidence of drug-drug interactions (DDIs) has been widely reported; however, such reports in pediatric oncology patients still remain scarce. We studied frequency and demographic correlates of moderate and major DDIs at a pediatric oncology ward in Isfahan, Iran. All pediatric oncology patients admitted to the Omid hospital during a 6-month period (2017) who received at least 2 anticancer or non-anticancer drugs concomitantly were included in our study. Potential DDIs between anticancer and non-anticancer drugs during hospitalization was identified using Lexi-Interact on-line software. We detected 194 DDIs with moderate or major severity for our included 115 patients. Mechanistically, most of DDIs (56.4%) were pharmacodynamic. Systematic use of corticosteroids (82.0%), antimetabolites (77.0%), and antiemetic drugs (69.5%) were the most frequent medication classes responsible for detected DDIs. The interaction between aminoglycosides and the third generation cephalosporins was the most common (13.9%) non-anticancer DDI. The only identified interaction between 2 anticancer drugs was doxorubicin with cyclophosphamide. Age, sex, and the number of administered medications were associated with DDIs. Potential moderate or major DDIs occur frequently among pediatric cancer patients. More studies are needed to assess clinical and economic implications of DDIs in pediatric oncology patients.

Potential drug-drug interactions and nephrotoxicity in hematopoietic stem cell transplant adult recipients during bone marrow transplantation unit stay

PURPOSE

Studies have documented potential drug-drug interactions (pDDIs) occurring in cancer patients mainly with solid malignancies, either in the ambulatory or hospital settings. While hematopoietic stem cell transplant (HSCT) patients during their bone marrow transplantation unit (BMTU) stay have rather complex medical regimens combining chemotherapy, anti-infectious agents, immunosuppressive agents, and supportive-care drugs, studies on potential DDIs are lacking. Our objective was to evaluate the prevalence and the density of pharmacokinetic and pharmacodynamic potential DDIs, and the evolution of the renal function in hematopoietic stem cell transplant (HSCT) adult recipients during their BMTU stay.

METHODS

Retrospective study in 31 adult patients consecutively admitted to the BMTU.

RESULTS

Prevalence of pharmacokinetic interactions was ten times lower than the pharmacodynamic interactions. The contraindications were rare, and only of pharmacokinetic origin. The main drugs involved in pharmacokinetic DDIs were ciclosporine, methotrexate, esomeprazole, tramadol, and vincristine. The median number of potential nephrotoxicity-related DDIs per patient was 7 and the median number of days during which nephrotoxicity-related DDIs potentially occurred was 77 days per patient. The decrease in glomerular filtration rate (GFR) throughout the BMTU stay (mean decrease of 13 ml/min) was correlated with the number of days of potential nephrotoxic drug interactions.

CONCLUSIONS

Potential DDIs in HCST patients in BMTU were quite common. The DDIs from pharmacokinetic origin were less frequent, but of higher grade, than those of pharmacodynamic origin. The decrease in GFR suggests that the density of potential nephrotoxic drug interactions may be an issue to be considered in these patients.

Clarifying busulfan metabolism and drug interactions to support new therapeutic drug monitoring strategies: a comprehensive review

INTRODUCTION

Busulfan (Bu) is an alkylating agent with a limited therapeutic margin and exhibits inter-patient variability in pharmacokinetics (PK). Despite decades of use, mechanisms of Bu PK-based drug-drug interactions (DDIs), as well as the negative downstream effects of these DDIs, have not been fully characterized. Areas covered: This article provides an overview of Bu PK, with a primary focus on how known and potentially unknown drug metabolism pathways influence Bu-associated DDIs. In addition, pharmacogenomics of Bu chemotherapy and Bu-related DDIs observed in the stem cell transplant clinic (SCT) are summarized. Finally the increasing importance of Bu therapeutic drug monitoring is highlighted. Expert opinion: Mechanistic studies of Bu metabolism have shown that in addition to GST isoenzymes, other oxidative enzymes (CYP, FMO) and ABC/MDR drug transporters likely contribute to the overall clearance of Bu. Despite many insights, results from clinical studies, especially in polypharmacy settings and between pediatric and adult patients, remain conflicting. Further basic science and clinical investigative efforts are required to fully understand the key factors determining Bu PK characteristics and its effects on complications after SCT. Improved TDM strategies are promising components to further investigate, for instance DDI mechanisms and patient outcomes, in the highly complex SCT treatment setting.

Clinical relevancy and determinants of potential drug-drug interactions in chronic kidney disease patients: results from a retrospective analysis

Background

Chronic kidney disease (CKD) alters the pharmacokinetic and pharmacodynamic responses of various renally excreted drugs and increases the risk of drug-related problems, such as drug–drug interactions.

Objectives

To assess the pattern, determinants, and clinical relevancy of potential drug–drug interactions (pDDIs) in CKD patients.

Materials and methods

This study retrospectively reviewed medical charts of all CKD patients admitted in the nephrology unit of a tertiary care hospital in Pakistan from January 2013 to December 2014. The Micromedex Drug-Reax^® system was used to screen patient profiles for pDDIs, and IBM SPSS version 20 was used to carry out statistical analysis.

Results

We evaluated 209 medical charts and found pDDIs in nearly 78.5% CKD patients. Overall, 541 pDDIs were observed, of which, nearly 60.8% patients had moderate, 41.1% had minor, 27.8% had major, and 13.4% had contraindicated interactions. Among those interactions, 49.4% had good evidence, 44.0% had fair, 6.3% had excellent evidence, and 35.5% interactions had delayed onset of action. The potential adverse outcomes of pDDIs included postural hypotension, QT prolongation, ceftriaxone–calcium precipitation, cardiac arrhythmias, and reduction in therapeutic effectiveness. The occurrence of pDDIs was found strongly associated with the age of <60 years, number of prescribed medicines ≥5, hypertension, and the lengthy hospitalization of patients.

Conclusion

The occurrence of pDDIs was high in CKD patients. It was observed that CKD patients with an older age, higher number of prescribed medicines, lengthy hospitalization, and hypertension were at a higher risk of pDDIs.

Green Tea and Bone Marrow Transplantation: From Antioxidant Activity to Enzymatic and Multidrug-resistance Modulation

Epigallocatechin-3-gallate (EGCG), the main flavonoid of green tea (GT), could play an active role in the prevention of oxidative-stress-related diseases, such as hematologic malignancies. Some effects of EGCG are not imputable to antioxidant activity, but involve modulation of antioxidant enzymes and uric acid (UA) levels. The latter is the major factor responsible of the plasma non-enzymatic antioxidant capacity (NEAC). However, hyperuricemia is a frequent clinical feature caused by tumor lysis syndrome or cyclosporine side effects, both before and after bone marrow transplantation (BMT). Besides this, food-drug interactions could be associated with GT consumption and could have clinical implications. The molecular mechanisms involved in the redox and drug metabolizing/transporting pathways were discussed, with particular reference to the potential role of GT and EGCG in BMT. Moreover, on reviewing data on NEAC, isoprostanes, uric acid, and various enzymes from human studies on GT, its extract, or EGCG, an increase in NEAC, without effect on isoprostanes, and contrasting results on UA and enzymes were observed. Currently, few and contrasting available evidences suggest caution for GT consumption in BMT patients and more studies are needed to better understand the potential impact of EGCG on oxidative stress and metabolizing/transporting systems.

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.

Drug-drug interaction software in clinical practice: a systematic review

PURPOSE

Several electronic databases which report the prevalence of drug-drug interactions (DDIs) are used as a tool for evaluation of potentially harmful DDIs. The aim of our review was to evaluate the usability and appropriateness of commercially available electronic databases which assess the prevalence of potential DDIs.

METHODS

The systematic electronic literature search was conducted with the following search terms: "database" AND "software," and "drug-drug interactions" AND "database," and the inclusion and exclusion criteria were applied in order to identify the publications of interest.

RESULTS

A total of 3766 papers were identified by systematic search. After applying inclusion and exclusion criteria, 38 publications were included in the analysis. The most commonly used software in the included studies was Micromedex® Drug-Reax, for which some authors argue to be the most reliable due to highest sensitivity. It gives information about clinical consequences of DDIs, classifies underlying mechanism and onset of the adverse outcome (either rapid, or delayed) as well as severity (such as minor, moderate, or major), and provides the level of evidence which supports this information. This data is also provided by Drug Interaction Facts®, Lexi-Interact®, and Pharmavista®. A small number of studies which compared assessment of DDIs with electronic database and the clinician's assessment showed large discrepancy in number and relevance of detected DDIs. The overlap was in some cases as low as 11 %.

CONCLUSION

The deficiency of clinical relevance of detected DDIs should be addressed in the upcoming research as it would provide more relevant information to the prescribers' in clinical practice.

High prevalence of potential drug interactions affecting mycophenolic acid pharmacokinetics in nonmyeloablative hematopoietic stem cell transplant recipients

Objective: Mycophenolic acid (MPA) exposure is associated with clinical outcomes in hematopoietic cell transplant (HCT) recipients. Various drug interaction studies, predominantly in healthy volunteers or solid organ transplant recipients, have identified medications which impact MPA pharmacokinetics. Recipients of nonmyeloablative HCT, however, have an increased burden of comorbidities, potentially increasing the number of concomitant medications and potential drug interactions (PDI) affecting MPA exposure. Thus, we sought to be the first to characterize these PDI in nonmyeloablative HCT recipients. Materials and methods: We compiled PDI affecting MPA pharmacokinetics and characterized the prevalence of PDI in nonmyeloablative HCT recipients. A comprehensive literature evaluation of four databases and PubMed was conducted to identify medications with PDI affecting MPA pharmacokinetics. Subsequently, a retrospective medication review was conducted to characterize the cumulative PDI burden, defined as the number of PDI for an individual patient over the first 21 days after allogeneic graft infusion, in 84 nonmyeloablative HCT recipients. Results: Of the 187 concomitant medications, 11 (5.9%) had a PDI affecting MPA pharmacokinetics. 87% of 84 patients had one PDI, with a median cumulative PDI burden of 2 (range 0 – 4). The most common PDI, in descending order, were cyclosporine, omeprazole and pantoprazole. Conclusion: Only a minority of medications (5.9%) have a PDI affecting MPA pharmacokinetics. However, the majority of nonmyeloablative HCT recipients had a PDI, with cyclosporine and the proton pump inhibitors being the most common. A better understanding of PDI and their management should lead to safer medication regimens for nonmyeloablative HCT recipients.

Potential drug-drug interactions at a referral hematology-oncology ward in Iran: a cross-sectional study

PURPOSE

To assess the pattern and probable risk factors for moderate and major drug-drug interactions in a referral hematology-oncology ward in Iran.

METHODS

All patients admitted to hematology-oncology ward of Dr. Shariati Hospital during a 6-month period and received at least two anti-cancer or non-anti-cancer medications simultaneously were included. All being scheduled anti-cancer and non-anti-cancer medications both prescribed and administered during ward stay were considered for drug-drug interaction screening by Lexi-Interact On-Desktop software.

RESULTS

One hundred and eighty-five drug-drug interactions with moderate or major severity were detected from 83 patients. Most of drug-drug interactions (69.73 %) were classified as pharmacokinetics. Fluconazole (25.95 %) was the most commonly offending medication in drug-drug interactions. Interaction of sulfamethoxazole-trimethoprim with fluconazole was the most common drug-drug interaction (27.27 %). Vincristine with imatinib was the only identified interaction between two anti-cancer agents. The number of administered medications during ward stay was considered as an independent risk factor for developing a drug-drug interaction.

CONCLUSIONS

Potential moderate or major drug-drug interactions occur frequently in patients with hematological malignancies or related diseases. Performing larger standard studies are required to assess the real clinical and economical effects of drug-drug interactions on patients with hematological and non-hematological malignancies.