Drug-drug interaction potential among patients with nonmetastatic castration-resistant prostate cancer (nmCRPC) treated with novel androgen receptor inhibitors

BACKGROUND

Nonmetastatic castration-resistant prostate cancer (nmCRPC) patients are often older and use concurrent medications that increase the potential for drug-drug interactions (pDDIs). This study assessed pDDI prevalence in real-world nmCRPC patients treated with apalutamide, darolutamide, or enzalutamide.

RESEARCH DESIGN AND METHODS

Castrated prostate cancer patients without metastases prior to androgen receptor inhibitor initiation were identified retrospectively via Optum Clinformatics Data Mart claims data (8/2019-3/2021). The top 100 concomitant medications were assessed for pDDIs.

RESULTS

Among 1,515 patients (mean age: 77 ± 8 years; mean Charlson Comorbidity Index: 3 ± 3), 340 initiated apalutamide, 112 darolutamide, and 1,063 enzalutamide. Common concomitant medication classes were cardiovascular (80%) and central nervous system (52%). Two-thirds of the patients received ≥5 concomitant medications; 30 (30/100 medications) pDDIs were identified for apalutamide and enzalutamide each and 2 (2/100 medications) for darolutamide. Most pDDIs had risk ratings of C or D, but four for apalutamide were rated X. Approximately 58% of the patients on apalutamide, 5% on darolutamide, and 54% on enzalutamide had ≥1 identified pDDI.

CONCLUSIONS

Results showed a higher frequency of pDDIs in patients receiving apalutamide and enzalutamide vs darolutamide. The impact of these could not be determined retrospectively. DDI risk should be carefully evaluated when discussing optimal therapy for patients with nmCRPC.

Drug-drug interactions of protein kinase inhibitors in chronic myeloid leukaemia patients: A study using the French health insurance database

The introduction of protein kinase inhibitors (PKIs) for chronic myeloid leukaemia (CML) has considerably improved prognosis of the disease but has also demonstrated a great potential for drug-drug interactions. Using the French health insurance databases, we aim to investigate the frequency, identify the associated factors and describe the potential consequences of potential drug-drug interactions (pPKI-DIs) between PKIs and concurrent medications in CML. A retrospective cohort study has been performed among patients with CML identified in the French healthcare database from 2011 to 2014. A pPKI-DI is defined as the presence of drugs listed as 'interacting' on the same day as PKI dispensing (co-dispensing) or in its coverage period (co-medication) during the first year of follow-up. The list of interacting drugs is based on the summary of products characteristics (SPCs) and Thesaurus of interactions. We performed specific nested case-control comparisons to investigate the association between PKI-DI and each of the three potential outcomes (death, hospitalisation for adverse drug reactions and switch to another PKI). We included 3480 patients; 1429 (41%) had a co-dispensing pPKI-DI, and 2153 (62%) had a co-medication pPKI-DI; 50% of the pPKI-DIs were 'to be taken into account', and 17% were 'not recommended'. The PKI with the most interactions was imatinib, and additional common drug classes included statins, benzodiazepines and proton pump inhibitors. Multivariate analysis demonstrated that the use of a higher number of additional drugs, comorbidities at baseline, high number of prescribers and higher ages were potential risk factors. Nilotinib and dasatinib showed a tendency towards a higher risk of pPKI-DI compared to imatinib. Despite the fact that some PKI-DIs were potentially clinically relevant, we did not find any significant association with death, hospitalisation for adverse drug reactions and switching. These findings should increase awareness to help reduce the prevalence of PKI-drug interactions and thereby ensure better management of CML patients.

Metabolic activation of tyrosine kinase inhibitors: recent advance and further clinical practice

At present, receptor tyrosine kinase signaling-related pathways have been successfully mediated to inhibit tumor proliferation and promote anti-angiogenesis effects for cancer therapy. Tyrosine kinase inhibitors (TKIs), a group of novel chemotherapeutic agents, have been applied to treat diverse malignant tumors effectively. However, the latent toxic and side effects of TKIs, such as hepatotoxicity and cardiotoxicity, limit their use in clinical practice. Metabolic activation has the potential to lead to toxic effects. Numerous TKIs have been demonstrated to be transformed into chemically reactive/potentially toxic metabolites following cytochrome P450-catalyzed activation, which causes severe adverse reactions, including hepatotoxicity, cardiotoxicity, skin toxicity, immune injury, mitochondria injury, and cytochrome P450 inactivation. However, the precise mechanisms of how these chemically reactive/potentially toxic species induce toxicity remain poorly understood. In addition, we present our viewpoints that regulating the production of reactive metabolites may decrease the toxicity of TKIs. Exploring this topic will improve understanding of metabolic activation and its underlying mechanisms, promoting the rational use of TKIs. This review summarizes the updated evidence concerning the reactive metabolites of TKIs and the associated toxicities. This paper provides novel insight into the safe use of TKIs and the prevention and treatment of multiple TKIs adverse effects in clinical practice.

Potential interactions between antineoplastic agents and medicines used to treat Covid-19

INTRODUCTION

Cancer patients with Covid-19 are exposed to treatment combinations that can potentially result in interactions that adversely affect patient outcomes. This study aimed to identify potential drug-drug interactions between antineoplastic agents and medicines used to treat Covid-19.

METHODS

We conducted a search for potential interactions between 201 antineoplastic agents and 26 medicines used to treat Covid-19 on the Lexicomp^® and Micromedex^® databases. The following data were extracted: interaction severity ("major" and "contraindicated") and interaction effects (pharmacokinetic and pharmacodynamic). We also sought to identify the therapeutic indication of the antineoplastic drugs involved in the potential drug-drug interactions.

RESULTS

A total of 388 "major" or "contraindicated" drug-drug interactions were detected. Eight drugs or combinations (baricitinib, lopinavir/ritonavir, atazanavir, darunavir, azithromycin, chloroquine, hydroxychloroquine, and sirolimus) accounted for 91.5% of these interactions. The class of antineoplastic agents with the greatest potential for interaction was tyrosine kinase inhibitors (accounting for 46.4% of all interactions). The findings show that atazanavir, baricitinib, and lopinavir/ritonavir can affect the treatment of all common types of cancer. The most common pharmacokinetic effect of the potential drug-drug interactions was increased plasma concentration of the antineoplastic medicine (39.4%).

CONCLUSIONS

Covid-19 is a recent disease and pharmacological interventions are undergoing constant modification. This study identified a considerable number of potential drug-drug interactions. In view of the vulnerability of patients with cancer, it is vital that health professionals carefully assess the risks and benefits of drug combinations.

Real-life drug-drug and herb-drug interactions in outpatients taking oral anticancer drugs: comparison with databases

PURPOSE

Due to polypharmacy and the rising popularity of complementary and alternative medicines (CAM), oncology patients are particularly at risk of drug-drug interactions (DDI) or herb-drug interactions (HDI). The aims of this study were to assess DDI and HDI in outpatients taking oral anticancer drug.

METHOD

All prescribed and non-prescribed medications, including CAM, were prospectively collected by hospital pharmacists during a structured interview with the patient. DDI and HDI were analyzed using four interaction software programs: Thériaque^®, Drugs.com^®, Hédrine, and Memorial Sloan Kettering Cancer Center (MSKCC) database. All detected interactions were characterized by severity, risk and action mechanism. The need for pharmaceutical intervention to modify drug use was determined on a case-by-case basis.

RESULTS

294 patients were included, with a mean age of 67 years [55-79]. The median number of chronic drugs per patient was 8 [1-29] and 55% of patients used at least one CAM. At least 1 interaction was found for 267 patients (90.8%): 263 (89.4%) with DDI, 68 (23.1%) with HDI, and 64 (21.7%) with both DDI and HDI. Only 13% of the DDI were found in Thériaque^® and Drugs.com^® databases, and 125 (2.5%) were reported with similar level of risk on both databases. 104 HDI were identified with only 9.5% of the interactions found in both databases. 103 pharmaceutical interventions were performed, involving 61 patients (20.7%).

CONCLUSION

Potentially clinically relevant drug interaction were frequently identified in this study, showing that several databases and structured screening are required to detect more interactions and optimize medication safety.

Impact of gastrointestinal tract variability on oral drug absorption and pharmacokinetics: An UNGAP review

The absorption of oral drugs is frequently plagued by significant variability with potentially serious therapeutic consequences. The source of variability can be traced back to interindividual variability in physiology, differences in special populations (age- and disease-dependent), drug and formulation properties, or food-drug interactions. Clinical evidence for the impact of some of these factors on drug pharmacokinetic variability is mounting: e.g. gastric pH and emptying time, small intestinal fluid properties, differences in pediatrics and the elderly, and surgical changes in gastrointestinal anatomy. However, the link of colonic factors variability (transit time, fluid composition, microbiome), sex differences (male vs. female) and gut-related diseases (chronic constipation, anorexia and cachexia) to drug absorption variability has not been firmly established yet. At the same time, a way to decrease oral drug pharmacokinetic variability is provided by the pharmaceutical industry: clinical evidence suggests that formulation approaches employed during drug development can decrease the variability in oral exposure. This review outlines the main drivers of oral drug exposure variability and potential approaches to overcome them, while highlighting existing knowledge gaps and guiding future studies in this area.

Sensitivity and specificity of drug interaction databases to detect interactions with recently approved oral antineoplastics

Rationale:

Drug-drug interactions (DDIs) with oral antineoplastics (OAs) are of increasing concern given the rapid increase in OA approvals and use in cancer patients. A small pilot study of 20 DDIs with OAs showed significant variability in commonly used DDI screening databases in sensitivity of detecting potentially clinically relevant DDIs. This study builds upon that work by expanding the number of potential DDIs analyzed and including a specificity analysis.

Methods

Newly approved OAs from 2016 to May 2019 (n = 22) were included in this analysis. Prescribing information for each drug was reviewed. A list of explicit and theoretical drug interactions was created for each OA by the two investigators. A board-certified oncology pharmacist adjudicated all DDI pairs for potential clinical significance. In total, 229 DDI pairs were used to analyze sensitivity of 5 DDI databases (Lexicomp®, Micromedex®, Medscape, Eporactes®, & Drugs.com). Additionally, 64 “dummy” or false DDI pairs were created to analyze specificity. Sensitivity and specific were analyzed using Cochran’s Qtest, while accuracy was analyzed using chi-square test.

Results

There was significant variability among the databases with regards to sensitivity (p < 0.0001), specificity (p < 0.0001), and accuracy (p < 0.0001). In terms of accuracy (max score = 400), Lexicomp®(355), Epocrates® (344), and Drugs.com (352) scored higher than MicroMedex® (270) and Medscape (280).

Conclusions

Considerable variability exists among DDI screening databases with regards to OAs and potential drug interactions. Clinicians should be vigilant in both screening for DDIs with OAs and describing DDIs encountered in clinical practice.

Role of OATP1B1 and OATP1B3 in Drug-Drug Interactions Mediated by Tyrosine Kinase Inhibitors

Failure to recognize important features of a drug's pharmacokinetic characteristics is a key cause of inappropriate dose and schedule selection, and can lead to reduced efficacy and increased rate of adverse drug reactions requiring medical intervention. As oral chemotherapeutic agents, tyrosine kinase inhibitors (TKIs) are particularly prone to cause drug-drug interactions as many drugs in this class are known or suspected to potently inhibit the hepatic uptake transporters OATP1B1 and OATP1B3. In this article, we provide a comprehensive overview of the published literature and publicly-available regulatory documents in this rapidly emerging field. Our findings indicate that, while many TKIs can potentially inhibit the function of OATP1B1 and/or OATP1B3 and cause clinically-relevant drug-drug interactions, there are many inconsistencies between regulatory documents and the published literature. Potential explanations for these discrepant observations are provided in order to assist prescribing clinicians in designing safe and effective polypharmacy regimens, and to provide researchers with insights into refining experimental strategies to further predict and define the translational significance of TKI-mediated drug-drug interactions.

Acute pancreatitis in a patient treated with imatinib and gefitinib

INTRODUCTION

Use of oral antineoplastic agents (OAAs) has increased significantly in recent years. OAAs currently represent 30-50% of all cancer treatments. Drug interactions are the most frequent drug-related problem affecting OAAs. We describe the case of a patient who presented acute pancreatitis, possibly induced by the concomitant use of imatinib and gefitinib.

CASE REPORT

A female patient received imatinib and gefitinib for the treatment of chronic myeloid leukemia and lung adenocarcinoma, respectively. Liver function and pancreatic enzyme values gradually worsened after initiation of imatinib, and the patient was diagnosed with acute pancreatitis.

MANAGEMENT AND OUTCOMES

Imatinib was discontinued owing to pancreatic toxicity. Gefitinib was subsequently discontinued owing to tumor progression. The patient received supportive measures for pancreatitis, although she eventually died 3 months after the onset of symptoms.

DISCUSSION

To our knowledge, this is the first case in the medical literature of acute pancreatitis possibly induced by an interaction between imatinib and gefitinib. The interaction most likely arose because imatinib is a CYP2D6 inhibitor and could therefore impair the metabolism of gefitinib (a CYP2D6 substrate) and increase its serum concentration. This interaction is extremely rare. However, due to its severity, hepatic and pancreatic function should be carefully monitored in patients treated with imatinib and/or gefitinib and other inhibitors or inducers of CYP2D6 and CYP3A4.

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.

Real-world prevalence of potential drug-drug interactions involving oral antineoplastic agents: a population-based study

PURPOSE

We aimed to gain insight into the real-world prevalence of potentially significant drug-drug interactions (DDIs) involving oral antineoplastic agents using nationwide data in Korea.

METHODS

The data from the 2016 and 2017 Health Insurance Review and Assessment Service-National Patients Sample (HIRA-NPS) of South Korea were used. The drugs prescribed concomitantly with oral anticancer drugs were screened for the potential DDIs by using two international DDI databases: Lexicomp^TM and Micromedex®. Potentially significant DDIs were defined as DDIs with a severity rating of "major" or higher from at least one reference. The DDIs were classified into category 1 if the severity ratings were major or higher using both references.

RESULTS

Overall 5657 cases of DDIs in 2925 patients (26.4%) and 1640 cases of category 1 DDIs in 997 patients (9.0%) were identified among 11,076 patients receiving oral anticancer drugs. The prevalence was highest among the targeted agents (63.2%) followed by traditional (21.2%) and endocrine agents (19.3%). The common potential clinical consequences were increased risk of corrected QT interval prolongation (36.7%), reduced efficacy of antineoplastic agents (30.4%), and increased toxicities of antineoplastic agents (8.0%). Polypharmacy and the duration of oral cancer treatment increased the likelihood of potential DDIs in addition to individual antineoplastic agents.

CONCLUSIONS

This study showed that potentially significant DDIs with oral antineoplastic agents were prevalent in real-world practice. Recognizing the high prevalence of DDIs among patients taking oral antineoplastic agents is a necessary step toward improving the clinical outcome.

Drug interactions with oral antineoplastic drugs: The role of the pharmacist

The main objective of the study is to determine the pharmacist detection of drug-drug and drug-food interactions in patients receiving oral antineoplastic drugs (OADs). Descriptive, prospective study in a tertiary-care teaching hospital. The study population included patients who received OADs from the Outpatient Pharmacy of the hospital. The study population was attended by a pharmacist who checked potential interactions. The severity of interactions was evaluated using the summary of product characteristics of each drug and three different databases. We included 219 patients with a total of 736 concomitant medications. A total of 34 drug-drug or food-drug interactions were recorded. The most common interaction detected was between erlotinib and ranitidine (major interaction). In 19 of the 34 interactions detected in the experimental group, the pharmacist prevented them from reaching the patient. Interactions were resolved by drug suspensions, drug changes, or changes in schedules always according to the attending physician or the patient. In the remaining 15 interactions, the doctor was not contacted because the interactions were considered to be of little relevance or because they only required surveillance. Hospital pharmacist can improve the patient's safety and the efficiency of oral cytostatic treatment by detecting and preventing drug-drug and drug-food interactions.

Recommendations on managing lenvatinib and everolimus in patients with advanced or metastatic renal cell carcinoma

INTRODUCTION

There are several second-line treatment options for patients with renal cell carcinoma after first-line failure of a tyrosine kinase inhibitor, especially with the recent approvals of cabozantinib, nivolumab, and the lenvatinib plus everolimus combination. A lack of reliable biomarkers and an overall lack of prospective head-to-head comparisons make it a challenge to choose a second-line treatment in the clinic. Areas covered: In this review/meta-opinion, we describe the safety profile of the lenvatinib plus everolimus combination in renal cell carcinoma. The combination of lenvatinib plus everolimus has achieved the highest rates of objective responses and the longest progression free and overall survival in cross-comparison trials. At the same time, the safety profile of this combination, including the rate of total and severe adverse events, the percentage of dose reductions required, and the rate of treatment discontinuation, was less favorable compared with available monotherapy options, suggesting that better management could help to maximize the activity of this combination while protecting patients from undue harm. Expert opinion: Herein, we aim to postulate multidisciplinary recommendations on the advice to offer to patients and caregivers before starting treatment and how to manage the combination from the perspective of daily clinical practice.