Prevalence and significance of potential drug-drug interactions among cancer patients receiving chemotherapy

Incidence and risk factors for potential drug-drug interactions in outpatients receiving opioid analgesics

BACKGROUND

Opioids are the most frequently used drugs to treat pain in cancer patients. However opioid analgesics can cause adverse effects and potential drug-drug interaction.

RESEARCH DESIGN AND METHODS

This cross-sectional retrospective study analyzed pDDI in 1839 patients with opioid analgesics in a large comprehensive hospital in China from January 1 to 31 December 2022. Three drug interaction databases were used to screen for pDDI including Drugs (U.S.A.), Medscape (U.S.A.), and Drug Assistant of Dingxiangyuan (China).

RESULTS

The prevalence of pDDIs among 1839 patients was around 41.27% of 759 patients, and 564 patients (74.31%) with pDDIs were diagnosed with tumor. Further, the total of 275 various pDDIs combinations were identified. The combination of oxycodone with morphine had the most frequent occurrence of 229 times, and its adverse effects mainly related to exacerbate central respiratory depression. While, gender, tumor, number of diagnoses, and the variety of opioid analgesics used were independent risk factors for pDDIs.

CONCLUSIONS

Outpatients taking opioid analgesics had a higher incidence of pDDIs. As consequently, optimized monitoring and management of patients taking opioid analgesics is recommended in order to ensure patient medication safety.

Clinical significance of coadministration of moderate to strong CYP enzyme inhibitors with doxorubicin in breast cancer patients receiving AC chemotherapy

INTRODUCTION

Cytochrome P450 (CYP) enzyme inhibitors may increase the toxicity of many chemotherapies. Medication databases classify doxorubicin coadministration with CYP2D6 or CYP3A4 inhibitors as either a major interaction or contraindication. This study assessed the incidence of toxicity secondary to doxorubicin given with or without CYP enzyme inhibitors in breast cancer patients receiving doxorubicin and cyclophosphamide.

METHODS

This retrospective study included female breast cancer patients treated with doxorubicin and cyclophosphamide (AC). Patients were divided into three arms: no moderate or strong CYP inhibitor interactions, moderate or strong CYP2D6 inhibitor interactions, or moderate or strong CYP3A4 inhibitor interactions. Primary outcomes included incidence of doxorubicin-associated toxicity, unplanned medical visits, chemotherapy treatment delays, and doxorubicin dose reductions. The secondary endpoint was time to toxicity.

RESULTS

There were 171 patients included (n = 20 patients in the CYP2D6 inhibitor group and n = 15 in the CYP3A4 inhibitor group). Neither CYP inhibitor group showed a difference in incidence of hepatotoxicity, cardiotoxicity, myelotoxicity, moderate/severe nausea, or treatment delays. Compared to the no CYP inhibitor group, the CYP2D6 inhibitor group experienced a higher incidence of unplanned medical visits (45% vs. 19.4%; p = 0.023) and more frequent doxorubicin dose reductions (30% vs. 7.2%; p = 0.006). The CYP3A4 inhibitor group did not differ from the no CYP inhibitor group for these outcomes.

CONCLUSIONS

CYP inhibitors, particularly CYP2D6 inhibitors, may affect doxorubicin tolerability, as seen in this study by an increased incidence of unplanned medical visits and doxorubicin dose reductions.

Polypharmacy and drug-drug interactions in metastatic breast cancer patients receiving cyclin-dependent kinase (CDK) 4/6 inhibitors

INTRODUCTION

Cyclin-dependent kinase (CDK) 4/6 inhibitors have significantly changed the treatment strategy for patients with locally advanced or metastatic hormone receptor positive (HR+), human epidermal growth factor 2 negative (HER2) breast cancer. The purpose of the study was to determine the prevalence of drug-drug interactions (DDI) in breast cancer patients using CDK 4/6 inhibitors and the extent of DDI reflected in the clinic and to increase clinical awareness among physicians.

METHOD

The data of 115 metastatic breast cancer patients using CDK 4/6 inhibitors who were admitted to the Medical Oncology outpatient clinic between July 2021 and July 2023 were retrospectively reviewed. The Drugs.com® Drug Interaction Checker application was used for the interaction between the CDK 4/6 inhibitor and other drugs.

RESULTS

Among patients included in the study, 97.3% had at least one additional drug use. We have identified a total of 170 potential DDI risks in 63.5 % of patients. Among these, 50.5% had a major potential DDI. In our study, there was a potential risk of QT prolongation in 45.2% of 170 DDI, an increase in the potential toxicity of the additional drug in 44.1%, an increase in the potential toxicity of the CDK 4/6 inhibitor in 5.3%, a decrease in the potential efficacy of the CDK 4/6 inhibitor in 2.9%, a decrease in the potential efficacy of the additional drug in 1.1%, and a serious potential infection risk in 1.1%. Most of the drug interactions were QT prolongation and increased toxicity of the additional drug. In terms of cardiovascular events, grade-2 and grade-3 QTc prolongation was found in 4.3% and 1.7% of these interactions, respectively. When evaluated in terms of CDK 4/6 inhibitor subtype, there was a potential risk of DDI at major level with Ribocilib and at moderate level with Palbociclib.

CONCLUSION

If CDK 4/6 inhibitors interact with concomitant drugs, they may cause an increase in the incidence of cardiac side effects and a decrease in the effect of the CDK 4/6 inhibitor or additional drug or an increase in toxicity. Increasing awareness of this issue will help to reduce the rates of side effects or toxicity and provide effective antitumour therapy.

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.

Comparative analysis of adverse event risks in breast cancer patients receiving pembrolizumab combined with paclitaxel versus paclitaxel monotherapy: insights from the FAERS database

Objective

This study aimed to evaluate the risk of adverse events (AEs) in breast cancer patients treated with pembrolizumab combined with paclitaxel versus those receiving pembrolizumab or paclitaxel monotherapy, using the FDA Adverse Event Reporting System (FAERS) database.

Methods

Data were extracted from the FAERS database for breast cancer patients treated with pembrolizumab combined with paclitaxel or with pembrolizumab or paclitaxel monotherapy from Q1 2016 to Q2 2023. Disproportionation analysis was performed by calculating the reporting odds ratio (ROR) with corresponding 95% confidence interval (95% CI), the information component (IC), and the lower bound of the information component 95% confidence interval (IC025) to identify potential safety signals.

Results

No significant difference in AEs was observed between the combined treatment group and the pembrolizumab monotherapy group. However, the combined treatment group exhibited a substantial increase in AE risk compared to the paclitaxel monotherapy group. The most significant increases in AE risk were adrenal insufficiency (ROR = 189.94, 95% CI 25.41-1419.7, IC = 3.37, IC025 = 1.59), hypophysitis (ROR = 99.46, 95% CI 12.72-777.4, IC = 3.31, IC025 = 1.44), and myocarditis (ROR = 69.5, 95% CI 8.55-565.23, IC = 3.25, IC025 = 1.33). The time-to-event for combined treatment was 35 (34-70) days, for pembrolizumab was 43 (35-90) days, and for paclitaxel was 42 (37-76) days. The combination therapy group demonstrated significantly shorter intervals to the onset of adrenal insufficiency (p = 0.008), myocarditis (p < 0.001), and immune-related enterocolitis (p = 0.009).

Conclusion

Analysis of the FAERS database indicates that combination therapy significantly elevates the risk of adrenal insufficiency, myocarditis, hypophysitis, and immune-related enterocolitis compared to paclitaxel monotherapy. These findings provide critical insights for clinicians in predicting and managing potential AEs associated with this treatment regimen.

Smart delivery vehicles for cancer: categories, unique roles and therapeutic strategies

Chemotherapy and surgery remain the primary treatment modalities for cancers; however, these techniques have drawbacks, such as cancer recurrence and toxic side effects, necessitating more efficient cancer treatment strategies. Recent advancements in research and medical technology have provided novel insights and expanded our understanding of cancer development; consequently, scholars have investigated several delivery vehicles for cancer therapy to improve the efficiency of cancer treatment and patient outcomes. Herein, we summarize several types of smart therapeutic carriers and elaborate on the mechanism underlying drug delivery. We reveal the advantages of smart therapeutic carriers for cancer treatment, focus on their effectiveness in cancer immunotherapy, and discuss the application of smart cancer therapy vehicles in combination with other emerging therapeutic strategies for cancer treatment. Finally, we summarize the bottlenecks encountered in the development of smart cancer therapeutic vehicles and suggest directions for future research. This review will promote progress in smart cancer therapy and facilitate related research.

Docetaxel, cyclophosphamide, and epirubicin: application of PBPK modeling to gain new insights for drug-drug interactions

The new adjuvant chemotherapy of docetaxel, epirubicin, and cyclophosphamide has been recommended for treating breast cancer. It is necessary to investigate the potential drug-drug Interactions (DDIs) since they have a narrow therapeutic window in which slight differences in exposure might result in significant differences in treatment efficacy and tolerability. To guide clinical rational drug use, this study aimed to evaluate the DDI potentials of docetaxel, cyclophosphamide, and epirubicin in cancer patients using physiologically based pharmacokinetic (PBPK) models. The GastroPlus™ was used to develop the PBPK models, which were refined and validated with observed data. The established PBPK models accurately described the pharmacokinetics (PKs) of three drugs in cancer patients, and the predicted-to-observed ratios of all the PK parameters met the acceptance criterion. The PBPK model predicted no significant changes in plasma concentrations of these drugs during co-administration, which was consistent with the observed clinical phenomenon. Besides, the verified PBPK models were then used to predict the effect of other Cytochrome P450 3A4 (CYP3A4) inhibitors/inducers on these drug exposures. In the DDI simulation, strong CYP3A4 modulators changed the exposure of three drugs by 0.71-1.61 fold. Therefore, patients receiving these drugs in combination with strong CYP3A4 inhibitors should be monitored regularly to prevent adverse reactions. Furthermore, co-administration of docetaxel, cyclophosphamide, or epirubicin with strong CYP3A4 inducers should be avoided. In conclusion, the PBPK models can be used to further investigate the DDI potential of each drug and to develop dosage recommendations for concurrent usage by additional perpetrators or victims.

Beyond cytotoxic potency: disposition features required to design ADC payload

1. Antibody-drug conjugates (ADCs) have demonstrated impressive clinical usefulness in treating several types of cancer, with the notion of widening of the therapeutic index of the cytotoxic payload through the minimisation of the systemic toxicity. Therefore, choosing the most appropriate payload molecule is a particularly important part of the early design phase of ADC development, especially given the highly competitive environment ADCs find themselves in today.2. The focus of the current review is to describe critical attributes/considerations needed in the discovery and ultimately development of cytotoxic payloads in support of ADC design. In addition to potency, several key dispositional characteristics including solubility, permeability and bystander effect, pharmacokinetics, metabolism, and drug-drug interactions, are described as being an integral part of the integrated activities required in the design of clinically safe and useful ADC therapeutic agents.

Survey of Potential Drug Interactions, Use of Non-Medical Health Products, and Immunization Status among Patients Receiving Targeted Therapies

In recent years, several changes have occurred in the management of chronic immunological conditions with the emerging use of targeted therapies. This two-phase cross-sectional study was conducted through structured in-person interviews in 2018-2019 and 2022. Additional data sources included ambulatory medical records and the itemized reimbursement reporting interface of the National Health Insurance Fund. Drug interactions were analyzed using the UpToDate Lexicomp, Medscape drug interaction checker, and Drugs.com databases. The chi-square test was used, and odds ratios (ORs) were calculated. In total, 185 patients participated. In 53% of patients (n = 53), a serious drug-drug interaction (DDI) was identified (mean number: 1.07 ± 1.43, 0-7), whereas this value was 38% (n = 38) for potential drug-supplement interactions (mean number: 0.58 ± 0.85, 0-3) and 47% (n = 47) for potential targeted drug interactions (0.72 ± 0.97, 0-5) in 2018. In 2022, 78% of patients (n = 66) were identified as having a serious DDI (mean number: 2.27 ± 2.69, 0-19), 66% (n = 56) had a potential drug-supplement interaction (mean number: 2.33 ± 2.69, 0-13), and 79% (n = 67) had a potential targeted drug interactions (1.35 ± 1.04, 0-5). Older age (>60 years; OR: 2.062), female sex (OR: 3.387), and polypharmacy (OR: 5.276) were identified as the main risk factors. Screening methods and drug interaction databases do not keep pace with the emergence of new therapeutics.

Are measures and related symptoms of cachexia recorded as outcomes in gastrointestinal cancer chemotherapy clinical trials?

BACKGROUND

Cachexia is prevalent in gastrointestinal cancers and worsens patient outcomes and chemotherapy compliance. We examined to what extent registered gastrointestinal cancer chemotherapy clinical trials record measures and related symptoms of cachexia as outcomes, and whether these were associated with trial characteristics.

METHODS

Four public trial registries (2012-2022) were accessed for Phase II and/or III randomized controlled pancreatic, gastric, and colorectal cancer chemotherapy trial protocols. Trial outcome measures of overall survival and toxicity/side effects, and those related to cachexia [physical activity, weight/body mass index (BMI), dietary limitations, caloric intake, lean muscle mass] and symptoms (appetite loss, diarrhoea, pain, fatigue/insomnia, constipation, nausea, vomiting, and oral mucositis) were extracted, along with the number and types of performance status and patient-reported outcomes (PROs) tools. Data were summarized descriptively. Chi-square tests examined associations between outcomes and trial characteristics (cancer type, trial location, funding source, PROs tools, and commencement year). Statistical significance was set at P < 0.05.

RESULTS

We included 540 trial protocols (pancreatic (35.2%), colorectal (33.3%) and gastric (31.5%)), with most trials from Europe (44.1%). Trial lead investigator was from academia (28.3%), industry (27.6%) and government (26.3%). Allied health professional involvement (26.9%) occurred at eligibility. Adjuvant therapy in trials was mainly treatment-related (68.1%). Additional medication included anti-nausea (2.2%) and analgesia (0.9%). Trial protocols mostly recorded overall survival (90.4%) and toxicity (78.9%), and the symptoms appetite loss (26.1%) and diarrhoea (19.1%), with the other symptoms recorded in <10% of the trials. Reporting of physical activity (P = 0.001), dietary limitations (P = 0.002), lean muscle mass (P = 0.027), appetite loss (P < 0.001), pain (P = 0.001), nausea (P = 0.012), and oral mucositis (P = 0.049) varied depending cancer type. Toxicity/side effects (P = 0.022), physical activity (P < 0.001), appetite loss, nausea, and vomiting (all P < 0.001), diarrhoea (P = 0.010), pain (P = 0.001), fatigue/insomnia (P = 0.001) varied depending on the trial location. Trial funding was predominantly from private/industry (34.3%) and influenced the reporting of overall survival (P = 0.049), weight/BMI (P = 0.005), caloric intake (P = 0.015), and pain (P = 0.031). Performance status and PROs tools were mentioned in 91.2% and 46.3% of the trials, respectively. Trials that incorporated PROs tools were more likely to report cachexia related outcomes, except for overall survival, lean muscle mass, and oral mucositis. The proportion of trials measuring weight/BMI increased with trial commencement year (P = 0.04).

CONCLUSIONS

Cachexia-related outcomes were under-recorded in gastrointestinal cancer chemotherapy trials. As trial patients experience a high symptom burden, cachexia-relevant measures and symptoms should be assessed throughout the trial, and integrated with primary endpoints to support their progress.

Implementation of Partnered Pharmacist Medication Charting in haematology and oncology inpatients

AIM

Partnered Pharmacist Medication Charting (PPMC) in patients admitted under general medical units has been shown to reduce medication errors. The aim of this study is to evaluate the impact of the PPMC model on medication errors in patients admitted under cancer units in Victorian hospitals.

METHODS

A prospective cohort study comparing cohorts before and after the introduction of PPMC was conducted. This included a 2-month pre-intervention phase and 3-month intervention phase. PPMC was implemented during the intervention phase as new model of care that enabled credentialed pharmacists to chart all admission medications, including pre-admission or new medications and cancer therapies, in collaboration with the admitting medical officer. The proportion of medication charts with at least one error was the primary outcome measure.

RESULTS

Seven health services across Victoria were included in the study. The majority of health services were using paper-based prescribing systems for oncology. Of the 547 patients who received standard medical medication charting, 331 (60.5%) had at least one medication error identified compared to 18 out of 416 patients (4.3%) using the PPMC model (p < 0.001). The median (interquartile range) inpatient length of stay was 5 (2.9-10.6) days in pre-intervention and 4.9 (2.9-11) days in intervention (p  =  0.88). In the intervention arm, 42 patients had cancer therapy charted by a pharmacist with no errors.

CONCLUSIONS

PPMC was successfully scaled into cancer units as a collaborative medication safety strategy. The model was associated with significantly lower rates of medication errors, including cancer therapies. PPMC should be adopted more widely in cancer units in Australia.

Risk stratification model for the pharmaceutical care of oncology patients with solid or hematologic neoplasms

OBJECTIVE

We aimed to develop of a risk stratification model for the pharmaceutical care (PC) of patients with solid or hematologic neoplasms who required antineoplastic agents or supportive treatments.

METHOD

The risk stratification model was collaboratively developed by oncology pharmacists from the Spanish Society of Hospital Pharmacy (SEFH). It underwent refinement through three workshops and a pilot study. Variables were defined, grouped into four dimensions, and assigned relative weights. The pilot study collected and analyzed data from participating centers to determine priority levels and evaluate variable contributions. The study followed the Kaiser Permanente pyramid model, categorizing patients into three priority levels: Priority 1 (intensive PC, 90th percentile), Priority 2 (60th-90th percentiles), and Priority 3 (60th percentile). Cut-off points were determined based on this stratification. Participating centers recorded variables in an Excel sheet, calculating mean weight scores for each priority level and the total risk score.

RESULTS

The participants agreed to complete a questionnaire that comprised 22 variables grouped into 4 dimensions: demographic (maximum score =11); social and health variables and cognitive and functional status (maximum = 19); clinical and health services utilization (maximum = 25); and treatment-related (maximum = 41). From the results of applying the model to the 199 patients enrolled, the cutoff points for categorization were 28 or more points for priority 1, 16 to 27 points for priority 2 and less than 16 for priority 3; more than 80% of the total score was based on the dimensions of 'clinical and health services utilization' and 'treatment-related'. Interventions based on the pharmaceutical care model were recommended for patients with solid or hematological neoplasms, according to their prioritization level.

CONCLUSION

This stratification model enables the identification of cancer patients requiring a higher level of pharmaceutical care and facilitates the adjustment of care capacity. Validation of the model in a representative population is necessary to establish its effectiveness.

Risk stratification model for the pharmaceutical care of oncology patients with solid or hematologic neoplasms

OBJECTIVE

We aimed to develop of a risk stratification model for the pharmaceutical care of patients with solid or hematologic neoplasms who required antineoplastic agents or supportive treatments.

METHOD

The risk stratification model was collaboratively developed by oncology pharmacists from the Spanish Society of Hospital Pharmacy (SEFH). It underwent refinement through 3 workshops and a pilot study. Variables were defined, grouped into 4 dimensions, and assigned relative weights. The pilot study collected and analyzed data from participating centers to determine priority levels and evaluate variable contributions. The study followed the Kaiser Permanente pyramid model, categorizing patients into 3 priority levels: Priority 1 (intensive PC, 90th percentile), Priority 2 (60th-90th percentiles), and Priority 3 (60th percentile). Cut-off points were determined based on this stratification. Participating centers recorded variables in an Excel sheet, calculating mean weight scores for each priority level and the total risk score.

RESULTS

The participants agreed to complete a questionnaire that comprised 22 variables grouped into 4 dimensions: demographic (maximum score=11); social and health variables and cognitive and functional status (maximum=19); clinical and health services utilization (maximum=25); and treatment-related (maximum=41). From the results of applying the model to the 199 patients enrolled, the cut-off points for categorization were 28 or more points for priority 1, 16-27 points for priority 2, and less than 16 for priority 3; more than 80% of the total score was based on the dimensions of "clinical and health services utilization" and "treatment-related." Interventions based on the pharmaceutical care model were recommended for patients with solid or hematological neoplasms, according to their prioritization level.

CONCLUSION

This stratification model enables the identification of cancer patients requiring a higher level of pharmaceutical care and facilitates the adjustment of care capacity. Validation of the model in a representative population is necessary to establish its effectiveness.

Potential Drug-Drug Interactions in Outpatient Lung Cancer Patients in a University Hospital

INTRODUCTION

Concomitant use of drugs in the same or different indications can sometimes lead to undesirable interactions. The prevalence of drug interactions is high in cancer patients. In this study, we aimed to determine the frequency and clinical severity of drug interactions in outpatient lung cancer patients.

METHODS

The drugs used, kidney and liver blood analysis results of 160 outpatient lung cancer patients over the age of 18 years who received chemotherapy between October 2020 and July 2021 were evaluated. The Lexi-Interact online database was used to identify the types of clinically significant drug interactions, frequently interacting drugs, and clinical outcomes predicted by the databases.

RESULTS

The average number of drugs per patient was 4.2 ± 2.3. It was determined that there was a relationship between multidrug use and comorbidity, and the number of drugs used increased as the number of diagnoses increased. A relationship was also found between potential drug-drug interactions (pDDIs), which we observed in 52.5% of the patients, and the number of drugs used and age. The most common clinically significant C- (36.9%), D- (16.9%), and X- (10.6%) type pDDIs were detected between conventional paclitaxel-hydrochlorothiazide, conventional paclitaxel-carboplatin, and ipratropium-tiotropium, respectively.

CONCLUSIONS

The use of frequently interacting drugs in outpatient lung cancer patients can lead to pDDIs. In these patients, the application of therapy by observing the drug-drug interaction may improve the quality of life.

Assessment of potential drug-drug interactions in hospitalized cancer patients

INTRODUCTION

Drug-drug interactions (DDIs) pose a significant threat to patients with cancer, resulting in several adverse events in an oncology setting. Our study aims to identify potential DDIs in inpatient oncology wards, assess their severity, and provide recommendations to avoid these interactions.

MATERIALS AND METHODS

This prospective study was conducted in 79 hospitalized cancer patients over a period of 9 months (from August 2021 to May 2022) at the Amrita Institute of Medical Sciences, Kochi receiving at least two oncological or non-oncological drugs for 5 days.

RESULTS

Significant differences were found in drug count (61.6% vs. 38.4%), hospitalization duration (63.1% vs. 36.9%), and medications for comorbidities (63% vs. 37%) between patients with and without DDIs (p < 0.001, <0.001, and 0.01, respectively). The study identified 321 DDIs, with 14 (4.4%) X interactions, 93 (30%) D interactions, 161 (50%) C interactions, and 53 (15.6%) B interactions. Severity-wise, 76 (23.7%) were major, 190 (59.1%) were moderate, and 55 (17.2%) were minor.

CONCLUSION

Our study showed that drug count, medications for comorbidities, and hospitalization duration significantly increase the risk of DDIs in hospitalized oncology patients. Around 96.4% of recommendations for potential interactions were accepted and implemented, highlighting the huge opportunities and requirements for improvement, implementation, and management of drug interactions in oncology settings.

Potential drug-drug interaction and its determinants among patients with cancer receiving chemotherapy in oncology centres of Northwest Ethiopia: an institutional-based cross-sectional study

OBJECTIVE

The study was conducted to assess potential drug-drug interactions (PDDIs) and its determinants among patients with cancer receiving chemotherapy.

DESIGN AND SETTING

An institutional-based cross-sectional study was used. This study was conducted from 1 June 2021 to 15 December 2021, in Northwest Ethiopia oncology centres.

PARTICIPANTS

All eligible patients with cancer received a combination of chemotherapy.

OUTCOMES

The prevalence and severity of PDDIs were evaluated using three drug interaction databases. Characteristics of participants were presented, arranged and summarised using descriptive statistics. The predictors and outcome variables were examined using logistic regression. The cut-off point was a p value of 0.05.

RESULTS

Of 422 patients included in the study, 304 patients were exposed to at least one PDDI with a prevalence of 72.1% (95 % CI: 68% to 76%) using three drug interaction databases. There were varied reports of the severity of PDDI among databases, but the test agreement using the kappa index was 0.57 (95% CI: 0.52 to 0.62, p=0.0001) which is interpreted as a moderate agreement among three databases. Patients aged ≥50 years old had the risk to be exposed to PDDI by odds of 3.1 times (adjusted OR (AOR)=3.1, 95% CI (1.8 to 5.3); p=0.001) as compared with patients <50 years old. Similarly, patients with polypharmacy and comorbidity were more likely to be exposed to PDDI than their counterparts (AOR=2.4, 95% CI (1.4 to 4.1); p=0.002 and AOR=1.9, 95% CI (1.1 to 3.4); p=0.02, respectively).

CONCLUSION

The main finding of this study is the high prevalence of PDDI, signifying the need for strict patient monitoring for PDDIs among patients with cancer receiving chemotherapy. We suggest the use of at least three drug databases for quality screening. Patients with an age ≥50 years old, polypharmacy and comorbidity were significantly associated with PDDIs. The establishment of oncology clinical pharmacists and computerised reminder mechanisms for PDDIs through drug utilisation review is suggested.

A systematic review and meta-analysis of randomized controlled trials on the effectiveness of immersive virtual reality in cancer patients receiving chemotherapy

PURPOSE

Immersive virtual reality (IVR) shows promise in cancer care, especially for chemotherapy patients. This systematic review and meta-analysis assesses IVR's impact on adult and pediatric cancer patients undergoing chemotherapy.

METHODS

We searched PubMed, Cochrane Library, Embase, Scopus, Web of Science, and Google Scholar for relevant randomized controlled trials (RCTs). We focused on anxiety, depression, fatigue, pain, and anxiety in adults and pain and anxiety in pediatric patients.

RESULTS

Fifteen trials were included, enrolling 607 adult and 257 pediatric cancer patients. IVR significantly reduced anxiety (SMD = -1.89, 95% CI = -2.93 to -0.85), depression (SMD = -1.85, 95% CI = -3.14 to -0.55), fatigue (SMD = -3.40, 95% CI = -5.54 to -1.26), and systolic blood pressure (MD = -3.54, 95% CI = -6.67 to -0.40) in adults. In pediatric patients, IVR significantly lowered pain (SMD = -1.17, 95% CI = -1.84 to -0.50) and anxiety (SMD = -1.18, 95% CI = -1.77 to -0.59) but not heart rate (MD = 0.48, 95% CI = -2.38 to 3.34).

CONCLUSION

IVR effectively reduces anxiety, depression, fatigue, systolic blood pressure, pain, and anxiety in cancer patients. More robust RCTs are needed for further IVR research.

No Interference of H9 Extract on Trastuzumab Pharmacokinetics in Their Combinations

Trastuzumab is used to treat breast cancer patients overexpressing human epidermal growth factor receptor 2, but resistance and toxicity limit its uses, leading to attention to trastuzumab combinations. Recently, the synergistic effect of trastuzumab and H9 extract (H9) combination against breast cancer has been reported. Because drug exposure determines its efficacy and toxicity, the question of whether H9 changes trastuzumab exposure in the body has been raised. Therefore, this study aimed to characterize trastuzumab pharmacokinetics and elucidate the effect of H9 on trastuzumab pharmacokinetics at a combination dose that shows synergism in mice. As a result, trastuzumab showed linear pharmacokinetics after its intravenous administration from 1 to 10 mg/kg. In the combination of trastuzumab and H9, single and 2-week treatments of oral H9 (500 mg/kg) did not influence trastuzumab pharmacokinetics. In the multiple-combination treatments of trastuzumab and H9 showing their synergistic effect (3 weeks of trastuzumab with 2 weeks of H9), the pharmacokinetic profile of trastuzumab was comparable to that of 3 weeks of trastuzumab alone. In tissue distribution, the tissue to plasma ratios of trastuzumab below 1.0 indicated its limited distributions within the tissues, and these patterns were unaffected by H9. These results suggest that the systemic and local exposures of trastuzumab are unchanged by single and multiple-combination treatments of H9.

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.

TOP-PIC: a new tool to optimize pharmacotherapy and reduce polypharmacy in patients with incurable cancer

PURPOSE

Polypharmacy is a significant problem in patients with incurable cancer and a method to optimize pharmacotherapy in this patient group is lacking. Therefore, a drug optimization tool was developed and tested in a pilot test.

METHODS

A multidisciplinary team of health professionals developed a "Tool to Optimize Pharmacotherapy in Patients with Incurable Cancer" (TOP-PIC) for patients with a limited life expectancy. The tool consists of five sequential steps to optimize medications, including medication history, screening for medication appropriateness and drug interactions, a benefit-risk assessment using the TOP-PIC Disease-based list, and shared decision-making with the patient. For pilot testing of the tool, 8 patient cases with polypharmacy were analyzed by 11 oncologists before and after training with the TOP-PIC tool.

RESULTS

TOP-PIC was considered helpful by all oncologists during the pilot test. The median additional time required to administer the tool was 2 min per patient (P < 0.001). For 17.4% of all medications, different decisions were made by using TOP-PIC. Among possible treatment decisions (discontinuation, reduction, increase, replacement, or addition of a drug), discontinuation of medications was the most common. Without TOP-PIC, physicians were uncertain in 9.3% of medication changes, compared with only 4.8% after using TOP-PIC (P = 0.001). The TOP-PIC Disease-based list was considered helpful by 94.5% of oncologists.

CONCLUSIONS

TOP-PIC provides a detailed, disease-based benefit-risk assessment with recommendations specific for cancer patients with limited life expectancy. Based on the results of the pilot study, the tool seems practicable for day-to-day clinical decision-making and provides evidence-based facts to optimize pharmacotherapy.

Clinical and economic impact of clinical oncology pharmacy in cancer patients receiving injectable anticancer treatments: a systematic review

PURPOSE

Clinical pharmacy can reduce drug-related iatrogenesis by improving the management of adverse effects of drugs, limiting drug-drug interactions, and improving patient adherence. Given the vulnerability of cancer patients and the toxicity of injectable anticancer drugs, clinical pharmacy service (CPS) could provide a significant clinical benefit in cancer care. This review aims to synthesize existing evidence on clinical pharmacy's impact on patients treated with intravenous anticancer drugs.

METHODS

A comprehensive search was performed in the PubMed/Medline database from January 2000 to December 2021, associating the keywords: clinical pharmacy, pharmaceutical care, pharmacist, oncology, and chemotherapy. To be eligible for inclusion, studies have to report clinical pharmaceutical services for patients treated with intravenous chemotherapy with a clinical and/or economic impact.

RESULTS

Forty-one studies met the selection criteria. Various CPS were reported: medication reconciliation, medication review, and pharmaceutical interview with patient. There was a lack of randomized study (n = 3; 7.3%). In one randomized controlled trial, pharmaceutical intervention significantly improved quality of life of patients receiving pharmaceutical care during injectable anticancer drugs courses. Economical results appear to show positive impact of clinical pharmacy with cost savings reported from 3112.87$ to 249 844€. Although most studies were non-comparative, they highlighted that clinical pharmacy tend to limit chemotherapy side effects and drug-related problems, improve quality of life and satisfaction of patients and healthcare professional, and a positive economic impact.

CONCLUSION

Clinical pharmacy can reduce adverse drug events in cancer patients. More robust and economic evaluations are still required to support its development in everyday practice.

Development of evidence-based indicators for the detection of drug-related problems among ovarian cancer patients

Background: Antineoplastic drugs produce serious drug-related problems and their management is challenging. DRPs are critical, for saving on therapeutic costs, particularly in resource poor settings within low-middle-income countries such as India. Indicators are clues that helps to detect DRPs within the healthcare organization and minimize overall harm from medications. Indicators enable healthcare professionals to determine the future therapeutic course. And enable healthcare professionals to take a proactive stand, and stay informed and empowered to both prevent and manage DRPs. This study aims to develop evidence-based indicators for detecting potential drug-related problems in ovarian cancer patients. Patients and Methods: A retrospective study was conducted in the Department of Oncology of a tertiary care teaching hospital in South India. Based on literature search, we developed a list of indicators, which were validated by a Delphi panel of multidisciplinary healthcare professionals (16 members). Based on 2 years of ovarian cancer data, we performed a feasibility test retrospectively and classified the DRPs according to the Pharmaceutical Care Network Europe classification of DRPs version-9.1. Results: The feasibility test identified 130 out of 200 indicators. A total of 803 pDRPs were identified under four main categories: drug selection problem, drug use problem, adverse drug reaction and drug-drug interaction The most frequently observed were ADR 381 (47.45%), DDIs 354 (44.08%), and drug selection problems 62 (7.72%). Conclusion: Indicators developed by us effectively identified pDRPs in ovarian cancer patients, which can potentially help healthcare professionals in the early detection, timely management, and attenuating severity of DRPs. Identifying the pDDIs can potentially improve interdisciplinary involvement and task sharing, including enhanced pharmacists' participation within the healthcare team.

Hybrid peptides as platform for synchronized combination therapy

Combination therapy, where two or more therapeutic agents are combined to target different cellular pathways, is an effective tool in cancer treatment but often difficult to execute. Here we present the collagen peptide-based platform that allows for synchronous and colocalized cellular delivery of three different agents. The peptide is a hybrid between collagen and cell penetrating peptide (CPP) that assembles into a heterotrimer helix and forms fully organic, high aspect ratio nanoparticles. The validity of the approach was tested with three chemically different agents (Paclitaxel, Doxorubicin, and 5-Fluorouracil; a combination used in clinical treatment of (ER)-positive and (PR)-positive breast cancer) conjugated to N-terminus of the peptide. The design of this peptide-based drug delivery system provides several advantages: it avoids drug loading problems; removes the need for orthogonal synthesis; and allows for colocalized delivery of up to three drugs (which leads to the same biodistribution for each drug). In addition, hybrid collagen/CPP peptides are known to enhance cellular uptake and improve solubility of drugs. The synergistic effect, in terms of enhanced efficacy, of the Paclitaxel-Doxorubicin-5-Fluorouracil combination was also calculated. We envision self-assembling peptides as a platform for drug codelivery that can be expanded into a library of personalized combinations that may also include other functionalities like targeting or imaging.

MecDDI: Clarified Drug-Drug Interaction Mechanism Facilitating Rational Drug Use and Potential Drug-Drug Interaction Prediction

Drug-drug interactions (DDIs) are a major concern in clinical practice and have been recognized as one of the key threats to public health. To address such a critical threat, many studies have been conducted to clarify the mechanism underlying each DDI, based on which alternative therapeutic strategies are successfully proposed. Moreover, artificial intelligence-based models for predicting DDIs, especially multilabel classification models, are highly dependent on a reliable DDI data set with clear mechanistic information. These successes highlight the imminent necessity to have a platform providing mechanistic clarifications for a large number of existing DDIs. However, no such platform is available yet. In this study, a platform entitled "MecDDI" was therefore introduced to systematically clarify the mechanisms underlying the existing DDIs. This platform is unique in (a) clarifying the mechanisms underlying over 1,78,000 DDIs by explicit descriptions and graphic illustrations and (b) providing a systematic classification for all collected DDIs based on the clarified mechanisms. Due to the long-lasting threats of DDIs to public health, MecDDI could offer medical scientists a clear clarification of DDI mechanisms, support healthcare professionals to identify alternative therapeutics, and prepare data for algorithm scientists to predict new DDIs. MecDDI is now expected as an indispensable complement to the available pharmaceutical platforms and is freely accessible at: https://idrblab.org/mecddi/.

Frequency, severity, and factors associated with clinically significant drug-drug interactions among patients with cancer attending Mbarara Regional Referral Hospital Cancer Unit, Uganda

BACKGROUND

Cancer is a major public health problem with pharmacotherapy being the cornerstone of its management. Cancer patients receive multiple drugs concurrently risking Drug-Drug Interactions (DDIs). DDIs, though avoidable, can significantly contribute to morbidity, mortality, and increased healthcare costs in this population of patients. Currently, there is no published study from Uganda on clinically significant DDIs (cs-DDIs) among cancer patients. This study identifies frequency, severity, and factors associated with cs-DDIs at Mbarara Regional Referral Hospital Cancer Unit (MRRHCU).

METHOD

A cross-sectional study was conducted among 300 cancer patients receiving chemotherapy from a tertiary care hospital in western Uganda from January-February 2022. A questionnaire and data collection form were used to collect patient data. Lexicomp® Drug interaction software was used to screen the patient drug information for DDIs and assess their severity. Predictors of DDIs were identified using logistic regression using SPSS (Statistical Package for Social Sciences).

RESULT

Three hundred participants were enrolled with a mean age of 48 ± 23.3 years. One hundred eighty-one patients experienced 495 cs-DDIs; with a mean of 1.7 ± 2.2. The prevalence of cs-DDI was 60.3% (55.0-66.0% at 95% CI). Digestive organ neoplasms were the most commonly (80, 26.7%) diagnosed category, and 'plant alkaloids and other natural products were the most frequently (143, 47.7%) used chemotherapeutic drug classes. About three-quarters of cs-DDIs were rated as category C risk (367, 74.1%) whereas over two-thirds (355, 71.7%) were moderate in severity.. Being female (aOR = 2.43 [1.23-4.48 at 95% CI]; P-value = 0.011) and use of ≥ 6 drugs concurrently (aOR = 18.82 [9.58-36.95 at 95% CI]; P-value < 0.001)) were significantly associated with cs-DDIs.

CONCLUSION

More than half of the participants experienced at-least one cs-DDI which is generally higher than what was reported in high-income settings. About three-quarters were category C and moderate in severity, and require enhanced monitoring for safety and treatment outcome. Being female and using ≥ 6 drugs were significantly associated with cs-DDIs.

Predictors of treatment refusal in patients with colorectal cancer: A systematic review

This systematic review was conducted to investigate predictors of treatment refusal in colorectal cancer (CRC) patients. An understanding of these predictors would inform statistical models for the identification of high-risk patients who might benefit from interventions that seek to improve treatment compliance. We performed a search of PubMed and Scopus to identify potentially relevant studies on predictors of treatment refusal in CRC patients that were published between January 1, 2000 and December 31, 2021. We screened manuscripts using predefined eligibility criteria. Information on study design, study location, patient characteristics, treatments, rates and predictors of treatment refusal, and the impact of treatment refusal on mortality or survival were collected from eligible studies. Study quality was assessed using the Newcastle-Ottawa score. The overall findings of the review process were summarized using descriptive statistics and a narrative synthesis. A total of 13 studies were included in this review. Ten studies reported on refusal of CRC surgery, refusal rate: 0.25%-3.26%; three studies reported on chemotherapy refusal (one of which reported on both surgery and chemotherapy refusal), refusal rate: 7.8%-41.5%; and one study reported on refusal of any cancer treatment, refusal rate: 8.7%. The bulk of the published literature confirmed the harmful association between treatment refusal and poor survival outcomes in CRC patients. Frequently cited predictors of treatment refusal included patient demographic characteristics (age, race, gender), clinical characteristics (disease stage, comorbidity), and factors that impact access to cancer care services (healthcare insurance, facility level). Potentially high rates of treatment refusal pose a challenge to CRC control. This review has identified several factors which must be considered when attempting to reduce treatment refusal in CRC patients. Furthermore, these factors should be tested as components of predictive risk models for this important outcome.

A technical note on emerging combination approach involved in the onconanotherapeutics

Cancer is the second cause of mortality worldwide, and the currently available conventional treatment approach is associated with serious side effects and poor clinical outcomes. Based on the outcome of the exploratory preclinical and clinical studies, it was found that therapeutic response increases multiple folds when anticancer drugs are used in combination. However, the conventional combination of anticancer drugs was associated with various limitations such as increased cost of treatment, systemic toxicity, drug resistance, and reduced pharmacokinetic attributes. Hence, attempts were made to formulate nanocarrier fabricated combinatorial drugs (NFCDs) to effectively manage and treat cancer. This approach offers several advantages, such as improved stability, lower drug exposure, targeted drug delivery, low side effects, and improved clinical outcome. Hence, in this review, first time, we have discussed the recent advancement and various types of nano carrier-based combinatorial drug delivery systems in a different type of cancer and highlighted the personalized combinatorial theranostic medicine as a futuristic anticancer treatment approach.

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.

Associated factors of potential drug-drug interactions and drug-food interactions in patients with multiple sclerosis

Background:

Multiple sclerosis (MS) is the most common immune-mediated demyelinating disease in younger adults. Patients with MS (PwMS) are vulnerable to the presence of potential drug–drug interactions (pDDIs) and potential drug–food interactions (pDFIs) as they take numerous medications to treat MS, associated symptoms and comorbidities. Knowledge about pDDIs and pDFIs can increase treatment success and reduce side effects.

Objective:

We aimed at determining the frequency and severity of pDDIs and pDFIs in PwMS, with regard to polypharmacy.

Methods:

In the cross-sectional study, we analysed pDDIs and pDFIs of 627 PwMS aged ⩾18 years. Data collection was performed through patient record reviews, clinical examinations and structured patient interviews. pDDIs and pDFIs were identified using two DDI databases: Drugs.com Interactions Checker and Stockley’s Interactions Checker.

Results:

We identified 2587 pDDIs (counted with repetitions). Of 627 PwMS, 408 (65.1%) had ⩾ 1 pDDI. Polypharmacy (concomitant use of ⩾ 5 drugs) was found for 334 patients (53.3%). Patients with polypharmacy (Pw/P) were found to have a 15-fold higher likelihood of having ⩾ 1 severe pDDI compared with patients without polypharmacy (Pw/oP) (OR: 14.920, p < 0.001). The most frequently recorded severe pDDI was between citalopram and fingolimod. Regarding pDFIs, ibuprofen and alcohol was the most frequent severe pDFI.

Conclusion:

Pw/P were particularly at risk of severe pDDIs. Age and educational level were found to be factors associated with the occurrence of pDDIs, independent of the number of medications taken. Screening for pDDIs/pDFIs should be routinely done by the clinical physician to increase drug safety and reduce side effects.

Potential Drug Interactions Between Psychotropics and Intravenous Chemotherapeutics Used by Patients With Cancer

Introduction: Patients undergoing cancer treatment usually have comorbidities, and psychiatric disorders are commonly seen in these patients. For the treatment of these psychiatric disorders, the use of psychotropic drugs is common, turning these patients susceptible to untoward drug interactions. Therefore, the aim of this study was to estimate the prevalence of clinically relevant drug-drug interactions (DDI) between chemotherapeutic and psychotropic agents in patients with cancer treated at an oncology service in southern Brazil. Methods: An observational epidemiological study with a cross-sectional census-type design was carried out between October and December 2020. The drug-drug interactions were identified through consultation and analysis of the Medscape Drug Interaction Check and Micromedex databases. The interactions were classified as major, when the interaction can be fatal and/or require medical intervention to avoid or minimize serious adverse effects and moderate, when the interaction can exacerbate the patient's condition and/or requires changes in therapy. Results: A total of 74 patients was included in the study among the 194 patients seen in the oncology service during the period studied. A total of 24 (32.4%) DDIs were found, 21 (87.5%) of which were classified as being of major risk and 3 (12.5%) as moderate risk. According to the mechanism of action, 19 (79.1%) were classified as pharmacodynamic interactions and 5 (20.9%) as pharmacokinetic interactions. Conclusion: It was shown that a considerable percentage of patients undergoing intravenous chemotherapy are at risk of pharmacological interaction with psychotropic drugs. Thus, it is essential that the oncologist considers all psychotropic drugs and other drugs used by patients in order to avoid drug-drug interactions.

A comprehensive evaluation of potentially significant drug-drug, drug-herb, and drug-food interactions among cancer patients receiving anticancer drugs

INTRODUCTION

During the cancer treatment path, cancer patients use numerous drugs, including anticancer, supportive, and other prescribed medications, along with herbs and certain products. This puts them at risk of significant drug interactions (DIs). This study describes DIs in cancer patients and their prevalence and predictors.

METHODS

A cross-sectional study design was used to achieve the study objectives. The study was carried out in two centers in the northern West Bank, Palestine. The Lexicomp® Drug Interactions tool (Lexi-Comp, Hudson OH, USA) was applied to check the potential DIs. In addition, the Statistical Package for the Social Sciences (SPSS) was used to show the results and find the associations.

RESULTS

The final analysis included 327 patients. Most of the participants were older than 50 years (61.2%), female (68.5%), and had a solid tumor (74.6%). The total number of potential DIs was 1753, including 1510 drug-drug interactions (DDIs), 24 drug-herb interactions, and 219 drug-food interactions. Importantly, the prevalence of DDIs was 88.1%. In multivariate analysis, the number of potential DDIs significantly decreased with the duration of treatment (p = 0.007), while it increased with the number of comorbidities (p < 0.001) and the number of drugs used (p < 0.001).

CONCLUSIONS

We found a high prevalence of DIs among cancer patients. This required health care providers to develop a comprehensive protocol to monitor and evaluate DIs by improving doctor-pharmacist communication and supporting the role of clinical pharmacists.

Analysis of the Management Effect of Cancer Patients after Oral Chemotherapy Based on Nursing Process Reengineering

With the pollution of the environment and the acceleration of the social rhythm, the prevalence of tumors has increased year by year, and tumors have brought huge pain and inconvenience to patients. However, traditional nursing work consumes a lot of manpower and material resources, but it is difficult to improve the happiness of cancer patients, and it also brings a lot of troubles to many nursing workers. Based on the above reasons, we reengineered the traditional nursing process based on the BPR theory and applied the new process to the analysis of the management effect of cancer patients after oral chemotherapy drugs. The data shows that there are 23 patients with no pressure ulcer risk (score greater than 19) before care, 27 patients with low risk (15-19 points), 32 patients with moderate risk (13-14 points), and 18 people at high risk (less than 12 points). After nursing, there were 82 patients with no pressure ulcer risk, 10 patients with low risk, 7 patients with moderate risk, and 1 patient with high risk. This shows that the risk of pressure ulcers in patients with cancer after the use of chemotherapy drugs is significantly reduced compared with those without nursing. Nursing intervention can improve the psychological state of cancer patients during the recovery period, and nursing intervention can promote the compliance of cancer patients in various aspects of rehabilitation.

The prognostic role of polypharmacy in metastatic colorectal cancer patients treated with regorafenib

Aim: To evaluate polypharmacy (PP) in patients with metastatic colorectal cancer receiving regorafenib. Methods: Patients with metastatic colorectal cancer receiving regorafenib were included and divided into two categories by their PP status: PP^- (<5 regular drug use/day) and PP⁺ (≥5 regular drug use/day). Results: 80 patients were included. 31 (38.7%) patients had PP. The median number of drugs used was three and seven in PP^- and PP⁺ patients, respectively. Antiemetics (26.5%) and antacids (48.4%) were the most common drugs used by PP^- and PP⁺ patients, respectively. In multivariate analysis, the risk of death was higher in PP⁺ patients (hazard ratio: 2.1; 95% CI: 1.2-3.7; p = 0.005). Conclusion: PP was an independent prognostic factor for overall survival in patients with metastatic colorectal cancer receiving regorafenib.

Clinical Opportunities for Germline Pharmacogenetics and Management of Drug-Drug Interactions in Patients With Advanced Solid Cancers

PURPOSE

Precision medicine approaches, including germline pharmacogenetics (PGx) and management of drug-drug interactions (DDIs), are likely to benefit patients with advanced cancer who are frequently prescribed multiple concomitant medications to treat cancer and associated conditions. Our objective was to assess the potential opportunities for PGx and DDI management within a cohort of adults with advanced cancer.

METHODS

Medication data were collected from the electronic health records for 481 subjects since their first cancer diagnosis. All subjects were genotyped for variants with clinically actionable recommendations in Clinical Pharmacogenetics Implementation Consortium guidelines for 13 pharmacogenes. DDIs were defined as concomitant prescription of strong inhibitors or inducers with sensitive substrates of the same drug-metabolizing enzyme and were assessed for six major cytochrome P450 (CYP) enzymes.

RESULTS

Approximately 60% of subjects were prescribed at least one medication with Clinical Pharmacogenetics Implementation Consortium recommendations, and approximately 14% of subjects had an instance for actionable PGx, defined as a prescription for a drug in a subject with an actionable genotype. The overall subject-level prevalence of DDIs and serious DDIs were 50.3% and 34.8%, respectively. Serious DDIs were most common for CYP3A, CYP2D6, and CYP2C19, occurring in 24.9%, 16.8%, and 11.7% of subjects, respectively. When assessing PGx and DDIs together, approximately 40% of subjects had at least one opportunity for a precision medicine-based intervention and approximately 98% of subjects had an actionable phenotype for at least one CYP enzyme.

CONCLUSION

Our findings demonstrate numerous clinical opportunities for germline PGx and DDI management in adults with advanced cancer.

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.

Evaluation of potential drug-drug interactions in cancer patients at a tertiary care hospital in Pakistan

BACKGROUND

Despite harboring a high burden of cancer patients who are at high risk of potential drug-drug interactions (pDDIs), there is scarcity of published information about pDDIs in cancer patients from Pakistan.

OBJECTIVE

To evaluate frequency, pattern, mechanism and factors associated with pDDIs in cancer patients treated at a tertiary care hospital in Pakistan.

METHODS

In this cross-sectional analytical study, a total of 253 eligible ambulatory cancer patients treated at Center for Nuclear Medicine and Radiotherapy Hospital Quetta were evaluated for pDDIs using IBM Micromedex® Drug Interactions. SPSS (version 26) was used for conducting multivariate analysis to find factors associated with the presence pDDIs. A p-value <0.05 was considered statistically significant.

RESULTS

A total of 141/253 (55.7%) patients were exposed to at-least one pDDI. A total of 251 pDDIs were noted with a median of one pDDI/per patient (interquartile range:1-2) Majority interactions were of major severity (72.9%), pharmacodynamic (49.8%) and had fair documentation level (64.1%). Anti-cancer drugs were involved in 73.0% pDDIs with doxorubicin as the most commonly involved (40.0%) anti-cancer followed by cyclophosphamide (27.6%) and cisplatin (13.5%). Potential cardiac adverse events made the bulk (33.8%) of predicted events. Receiving >2 anti-cancer (OR = 5.19, p-value = 0.001) and >6 ancillary drugs (OR = 4.16, p-value = 0.033) emerged as the risk factors of pDDIs.

CONCLUSIONS

The prevalence of pDDIs was within the range reported in published literature. Solid medication review, availability of DDI detecting tools and clinical pharmacist, and paying special attention to the high-risk patients may reduce the frequency of pDDIs at the study site.

The potential roles of Nrf2/Keap1 signaling in anticancer drug interactions

Nuclear factor (erythroid-derived 2)-related factor 2 (Nrf2), together with its suppressive binding partner Kelch-like ECH-associated protein 1 (Keap1), regulates cellular antioxidant response and drug metabolism. The roles of Nrf2/Keap1 signaling in the pathology of many diseases have been extensively investigated, and small molecules targeting Nrf2/Keap1 signaling have been developed to prevent or treat diseases such as multiple sclerosis, chronic kidney disease and cancer. Notably, Nrf2 plays dual roles in cancer development and treatment. Activation of Nrf2/Keap1 signaling in cancer cells has been reported to promote cancer progression and result in therapy resistance. Since cancer patients are often suffering comorbidities of other chronic diseases, anticancer drugs could be co-administrated with other drugs and herbs. Nrf2/Keap1 signaling modulators, especially activators, are common in drugs, herbs and dietary ingredients, even they are developed for other targets. Therefore, drug-drug or herb-drug interactions due to modulation of Nrf2/Keap1 signaling should be considered in cancer therapies. Here we briefly summarize basic biochemistry and physiology functions of Nrf2/Keap1 signaling, Nrf2/Keap1 signaling modulators that cancer patients could be exposed to, and anticancer drugs that are sensitive to Nrf2/Keap1 signaling, aiming to call attention to the potential drug-drug or herb-drug interactions between anticancer drugs and these Nrf2/Keap1 signaling modulators.

Potential drug-drug interactions in the era of integrase strand transfer inhibitors: a cross-sectional single-center study in Japan

BACKGROUND

Potential drug-drug interactions (PDDIs) commonly occur because of aging and comorbidities in people living with human immunodeficiency virus (HIV; PLWH). Protease inhibitors and non-nucleoside reverse transcriptase inhibitors have been reported to cause PDDIs in these patients. However, there are few reports of PDDIs in the era of treatment using integrase strand transfer inhibitors. Therefore, we investigated PDDIs in Japanese PLWH receiving antiretroviral drugs (ARVs).

METHODS

This was a cross-sectional observational study conducted in Japanese outpatients. All eligible patients who had received ARV therapy for at least 48 weeks were enrolled. The primary endpoint was the incidence of PDDIs detected using the Lexicomp® interface.

RESULTS

Of the 71 eligible patients, 51 (71.8%) were prescribed concomitant non-ARV medications. In 21 patients (29.6%), PDDIs with the potential to reduce the effects of ARVs occurred, although the HIV load was suppressed in all cases. Polypharmacy (the use of ≥5 non-ARVs) was observed in 25 patients (35.2%). There was a significantly higher median number of non-ARV medications in the PDDI group than in the non-PDDI group (6 vs. 3, P <  0.001). Furthermore, the proportion of patients on polypharmacy was significantly higher in those with PDDIs than in those without PDDIs (81.0% vs. 26.7%, P <  0.001).

CONCLUSIONS

The incidence of PDDIs is relatively high in Japanese PLWH, even in the era of treatment using integrase strand transfer inhibitors. Therefore, it is important for patients and health care providers to be constantly aware of PDDIs associated with ARV treatment.

Site-Specific Vesicular Drug Delivery System for Skin Cancer: A Novel Approach for Targeting

Skin cancer, one of the most prevalent cancers worldwide, has demonstrated an alarming increase in prevalence and mortality. Hence, it is a public health issue and a high burden of disease, contributing to the economic burden in its treatment. There are multiple treatment options available for skin cancer, ranging from chemotherapy to surgery. However, these conventional treatment modalities possess several limitations, urging the need for the development of an effective and safe treatment for skin cancer that could provide targeted drug delivery and site-specific tumor penetration and minimize unwanted systemic toxicity. Therefore, it is vital to understand the critical biological barriers involved in skin cancer therapeutics for the optimal development of the formulations. Various nanocarriers for targeted delivery of chemotherapeutic drugs have been developed and extensively studied to overcome the limitations faced by topical conventional dosage forms. A site-specific vesicular drug delivery system appears to be an attractive strategy in topical drug delivery for the treatment of skin malignancies. In this review, vesicular drug delivery systems, including liposomes, niosomes, ethosomes, and transfersomes in developing novel drug delivery for skin cancer therapeutics, are discussed. Firstly, the prevalence statistics, current treatments, and limitations of convention dosage form for skin cancer treatment are discussed. Then, the common type of nanocarriers involved in the research for skin cancer treatment are summarized. Lastly, the utilization of vesicular drug delivery systems in delivering chemotherapeutics is reviewed and discussed, along with their beneficial aspects over other nanocarriers, safety concerns, and clinical aspects against skin cancer treatment.

Association between Olaparib Exposure and Early Toxicity in BRCA-Mutated Ovarian Cancer Patients: Results from a Retrospective Multicenter Study

Factors associated with olaparib toxicity remain unknown in ovarian cancer patients. The large inter-individual variability in olaparib pharmacokinetics could contribute to the onset of early significant adverse events (SAE). We aimed to retrospectively analyze the pharmacokinetic/pharmacodynamic relationship for toxicity in ovarian cancer patients from “real life” data. The clinical endpoint was the onset of SAE (grade III/IV toxicity or dose reduction/discontinuation). Plasma olaparib concentration was assayed using liquid chromatography at any time over the dosing interval. Trough concentrations (CminPred) were estimated using a population pharmacokinetic model. The association between toxicity and clinical characteristics or CminPred was assessed by logistic regression and non-parametric statistical tests. Twenty-seven patients were included, among whom 13 (48%) experienced SAE during the first six months of treatment. Olaparib CminPred was the only covariate significantly associated with increased risk of SAE onset (odds ratio = 1.31, 95% CI = [1.10; 1.57], for each additional 1000 ng/mL). The ROC curve identified a threshold of CminPred = 2500 ng/mL for prediction of SAE onset (sensitivity/specificity 0.62 and 1.00, respectively). This study highlights a significant association between olaparib plasma exposure and SAE onset and identified the threshold of 2500 ng/mL trough concentration as potentially useful to guide dose adjustment in ovarian cancer patients.

Biologically Active α-Amino Amide Analogs and γδ T Cells-A Unique Anticancer Approach for Leukemia

Advanced stage cancers are aggressive and difficult to treat with mono-therapeutics, substantially decreasing patient survival rates. Hence, there is an urgent need to develop unique therapeutic approaches to treat cancer with superior potency and efficacy. This study investigates a new approach to develop a potent combinational therapy to treat advanced stage leukemia. Biologically active α-amino amide analogs (RS)-N-(2-(cyclohexylamino)-2-oxo-1-phenylethyl)-N-phenylpropiolamide (α-AAA-A) and (RS)-N-(2-(cyclohexylamino)-2-oxo-1-phenylethyl)-N-phenylbut2-enamide (α-AAA-B) were synthesized using linear Ugi multicomponent reaction. Cytotoxicities and IC50 values of α-AAA-A and α-AAA-B against leukemia cancer cell lines (HL-60 and K562) were analyzed though MTT assay. Cytotoxic assay analyzed percent killing of leukemia cell lines due to the effect of γδ T cells alone or in combination with α-AAA-A or α-AAA-B. Synthesized biologically active molecule α-AAA-A exhibited increased cytotoxicity of HL-60 (54%) and K562 (44%) compared with α-AAA-B (44% and 36% respectively). Similarly, α-AAA-A showed low IC50 values for HL-60 (1.61 ± 0.11 μM) and K562 (3.01 ± 0.14 μM) compared to α-AAA-B (3.12 ± 0.15 μM and 6.21 ± 0.17 μM respectively). Additive effect of amide analogs and γδ T cells showed significantly high leukemia cancer cell killing as compared to γδ T cells alone. A unique combinational therapy with γδ T cells and biologically active anti-cancer molecules (α-AAA-A/B), concomitantly may be a promising cancer therapy.

Prevalence of potential interactions of medications, including herbs and supplements, before, during, and after chemotherapy in patients with breast and prostate cancer

BACKGROUND

The use of herbs and supplements (HS) is common among patients with cancer, yet limited information exists about potential medication interactions (PMIs) with HS use around chemotherapy.

METHODS

Patients with breast or prostate cancer who had recently finished chemotherapy at 2 academic medical centers were surveyed by telephone. Interviewers inquired about all medications, including HS, before, during, and after chemotherapy. Micromedex, Lexicomp, and Natural Medicines Comprehensive Database interaction software programs were used to determine PMIs.

RESULTS

A total of 67 subjects (age range, 39-77 years) were evaluated in this study. Participants were primarily White patients (73%) with breast cancer (87%). The median number of medications was 11 (range, 2-28) during the entire study and was highest during chemotherapy (7; range, 2-22). Approximately four-fifths (84%) used HS. A total of 1747 PMIs were identified, and they represented 635 unique PMIs across all 3 timeframes, with most occurring during chemotherapy. Prescription-related PMIs (70%) were the most common type, and they were followed by HS-related (56%) and anticancer treatment-related PMIs (22%). Approximately half of the PMIs (54%) were categorized as moderate interactions, and more than one-third (38%) were categorized as major interactions. Patient use of HS increased from 51% during chemotherapy to 66% after chemotherapy, and this correlated with an increased prevalence of HS PMIs (46% to 60%). HS users were more likely to be at risk for a major PMI than non-HS users (92% vs 70%; P = .038).

CONCLUSIONS

The use of HS remains prevalent among patients with cancer and may place them at risk for PMIs both during chemotherapy and after the completion of treatment.

LAY SUMMARY

This study evaluates the risk of potential medication interactions for patients with breast or prostate cancer undergoing chemotherapy. The results show that patients often use herbs and supplements during treatment. Prescription medications are most often associated with medication interactions, which are followed by herb and supplement-related interactions. More than one-third of potential medication interactions are considered major. Patients should be educated about the risk of herb and supplement-related medication interactions during treatment.

The Complex Management of Atrial Fibrillation and Cancer in the COVID-19 Era: Drug Interactions, Thromboembolic Risk, and Proarrhythmia

PURPOSE OF REVIEW

Cardiotoxicity by anticancer agents has emerged as a multifaceted issue and is expected to affect both mortality and morbidity. This review summarizes clinical challenges in the management of oncological patients requiring anticoagulants for atrial fibrillation (AF) also considering the current outbreak of the COVID-19 (coronavirus disease 2019) pandemic, since this infection can add challenges to the management of both conditions. Specifically, the aims are manyfold: (1) describe the evolving use of direct oral anticoagulants (DOACs) in AF patients with cancer; (2) critically appraise the risk of clinically important drug-drug interactions (DDIs) between DOACs and oral targeted anticancer agents; (3) address expected DDIs between DOACs and candidate anti-COVID drugs, with implications on management of the underlying thrombotic risk; and (4) characterize the proarrhythmic liability in cardio-oncology in the setting of COVID-19, focusing on QT prolongation.

RECENT FINDINGS

AF in cardio-oncology poses diagnostic and management challenges, also due to the number of anticancer drugs recently associated with AF onset/worsening. Oral targeted drugs can potentially interact with DOACs, with increased bleeding risk mainly due to pharmacokinetic DDIs. Moreover, the vast majority of oral anticancer agents cause QT prolongation with direct and indirect mechanisms, potentially resulting in the occurrence of torsade de pointes, especially in susceptible patients with COVID-19 receiving additional drugs with QT liability. Oncologists and cardiologists must be aware of the increased bleeding risk and arrhythmic susceptibility of patients with AF and cancer due to DDIs. High-risk individuals with COVID-19 should be prioritized to target preventive strategies, including optimal antithrombotic management, medication review, and stringent monitoring.