Risk Evaluation for Acute Kidney Injury Induced by the Concomitant Use of Valacyclovir, Analgesics, and Renin-Angiotensin System Inhibitors: The Detection of Signals of Drug-Drug Interactions

Exploring the impact of co-exposure timing on drug-drug interactions in signal detection through spontaneous reporting system databases: a scoping review

INTRODUCTION

Drug-drug interactions (DDIs) are defined as the pharmacological effects produced by the concomitant administration of two or more drugs. To minimize false positive signals and ensure their validity when analyzing Spontaneous Reporting System (SRS) databases, it has been suggested to incorporate key pharmacological principles, such as temporal plausibility.

AREAS COVERED

The scoping review of the literature was completed using MEDLINE from inception to March 2023. Included studies had to provide detailed methods for identifying DDIs in SRS databases. Any methodological approach and adverse event were accepted. Descriptive analyzes were excluded as we focused on automatic signal detection methods. The result is an overview of all the available methods for DDI signal detection in SRS databases, with a specific focus on the evaluation of the co-exposure time of the interacting drugs. It is worth noting that only a limited number of studies (n = 3) have attempted to address the issue of overlapping drug administration times.

EXPERT OPINION

Current guidelines for signal validation focus on factors like the number of reports and temporal association, but they lack guidance on addressing overlapping drug administration times, highlighting a need for further research and method development.

The effect of valacyclovir on secondary prevention of congenital cytomegalovirus infection, following primary maternal infection acquired periconceptionally or in the first trimester of pregnancy. An individual patient data meta-analysis

OBJECTIVE

Recent studies have shown that a dosage of 8 g/d of oral valacyclovir reduces substantially the vertical transmission rate of cytomegalovirus in women with primary cytomegalovirus infection acquired periconceptionally or during the first trimester of pregnancy. This individual patient data meta-analysis aimed to assess the effectiveness and safety of valacyclovir treatment in the secondary prevention of congenital cytomegalovirus infection.

DATA SOURCES

MEDLINE, Scopus, Cochrane Central Register of Controlled Trials, the US registry of clinical trials (www.

CLINICALTRIALS

gov), and gray literature sources were searched from inception to March 2023.

STUDY ELIGIBILITY CRITERIA

Randomized controlled trials and quasi-randomized studies administering 8 g/d of oral valacyclovir in pregnant women with primary cytomegalovirus infection acquired periconceptionally or during the first trimester of pregnancy were included.

METHODS

All corresponding authors of the eligible studies were contacted. Cochrane's Risk of Bias 2 and Risk Of Bias In Non-randomised Studies - of Interventions tools were used for the risk of bias assessment. The result of amniocentesis was the primary outcome of interest. A 1-stage individual patient data meta-analysis was performed, using a generalized linear mixed model, clustered by the different trials. A subgroup analysis was performed, assessing separately the effect of valacyclovir in the periconceptional period and first trimester of pregnancy.

RESULTS

Overall, 3 studies were included in the analysis (n=527 women). Valacyclovir reduced the vertical transmission rate of cytomegalovirus (adjusted odds ratio, 0.34; 95% confidence interval, 0.18-0.61). This reduction was apparent for both periconceptional period (adjusted odds ratio, 0.34; 95% confidence interval, 0.12-0.96) and first-trimester (adjusted odds ratio, 0.35; 95% confidence interval, 0.16-0.76) infections. Moreover, valacyclovir reduced the rate of neonatal infection (adjusted odds ratio, 0.30; 95% confidence interval, 0.19-0.47), in both periconceptional period (adjusted odds ratio, 0.30; 95% confidence interval, 0.14-0.61) and first-trimester (adjusted odds ratio, 0.30; 95% confidence interval, 0.17-0.54) infections. Furthermore, valacyclovir reduced the rate of termination of pregnancy because of cytomegalovirus-associated severe fetal findings (adjusted odds ratio, 0.23; 95% confidence interval, 0.22-0.24). The gestational age at the initiation of treatment has a positive correlation with all outcomes. The overall prevalence of severe side effects was 2.1%.

CONCLUSION

A dosage of 8 g/d of oral valacyclovir reduced the vertical transmission rates of cytomegalovirus following primary maternal infection acquired periconceptionally or in the first trimester of pregnancy, with a low incidence of side effects.

Real-world safety and efficacy of amenamevir in patients with herpes zoster in Japan: A postmarketing observational study (REWARD)

The helicase-primase inhibitor amenamevir (AMNV) was approved for herpes zoster in Japan in 2017. The authors conducted a 1-month postmarketing observational study to evaluate the real-world safety and efficacy (cutaneous improvement and pain resolution) of AMNV in patients with herpes zoster. Of the 3453 patients registered between March 2018 and December 2020, 3110 were included in the safety analyses. The mean age (±standard deviation) was 63.7 ± 17.5 years, with 57.9% of patients aged ≥65 years. Most patients had mild (53.3%) or moderate (41.0%) cutaneous lesions. Regarding pain, 43.9%, 25.6%, and 12.5% of patients had pain at the levels of 1-3, 4-6, and 7-10 on the numerical rating scale. In total, 30.0%, 27.2%, and 16.1% of patients were concomitantly treated with analgesics: acetaminophen, nonsteroidal anti-inflammatory drugs, and Ca2+ channel α 2δ ligands, respectively, and 10.6% were treated with topical antiherpetic drugs. Adverse drug reactions occurred in 0.77% of patients, including four serious adverse drug reactions in four patients (hyponatremia, thrombocytopenia, rash, and rhabdomyolysis). Regarding important potential risks, renal disorder, cardiovascular events, and decreased platelets were observed in one, one, and two patients, respectively. Concerning efficacy, the cutaneous improvement rate (significantly improved or improved) was 95.5%, with significantly higher improvement rates in patients treated with AMNV for 7 days and in patients with less severe cutaneous lesions or less pain. Factors affecting the time to pain resolution were the severity of cutaneous lesions and pain at the start of AMNV treatment and older age. This study demonstrated that the AMNV is safe and effective in patients with herpes zoster in a real-world clinical setting.

Drug-drug interaction signals between loop diuretics and teicoplanin during acute kidney injury evaluated using Japanese spontaneous adverse drug event reports

Teicoplanin can cause acute kidney injury, but little is known about the risk of acute kidney injury when teicoplanin is co-administered with loop diuretics (a powerful diuresis), which can alter renal hemodynamics and glomerular filtration rate. We performed a signal detection analysis using a Japanese adverse event database to determine the additive impact of loop diuretics on acute kidney injury associated with teicoplanin. The dataset originated between April 2004 and August 2022. Disproportionality analysis was performed to detect the signals for acute kidney injury (the Standardized MedDRA Query) when co-administered teicoplanin or vancomycin (a positive control) with individual diuretics, including loop diuretics. Multivariate logistic regression analysis was tested to estimate the adjusted reporting odds ratio (aROR) and 95% confidence interval (95% CI). There were 147 and 515 events of acute kidney injury associated with teicoplanin and vancomycin, respectively. A significant positive signal for acute kidney injury when teicoplanin was co-administered with loop diuretics was present (aROR 4.83, 95% CI 3.52-6.61, p < 0.0001). Contrastingly, no significant signals were observed when vancomycin was co-administered with any diuretics. These findings suggest that co-administered loop diuretics may have an unfavorable effect on acute kidney injury while undertaking teicoplanin but not vancomycin.

Detection of potential drug-drug interactions for risk of acute kidney injury: a population-based case-control study using interpretable machine-learning models

Background: Acute kidney injury (AKI), with an increase in serum creatinine, is a common adverse drug event. Although various clinical studies have investigated whether a combination of two nephrotoxic drugs has an increased risk of AKI using traditional statistical models such as multivariable logistic regression (MLR), the evaluation metrics have not been evaluated despite the fact that traditional statistical models may over-fit the data. The aim of the present study was to detect drug-drug interactions with an increased risk of AKI by interpreting machine-learning models to avoid overfitting. Methods: We developed six machine-learning models trained using electronic medical records: MLR, logistic least absolute shrinkage and selection operator regression (LLR), random forest, extreme gradient boosting (XGB) tree, and two support vector machine models (kernel = linear function and radial basis function). In order to detect drug-drug interactions, the XGB and LLR models that showed good predictive performance were interpreted by SHapley Additive exPlanations (SHAP) and relative excess risk due to interaction (RERI), respectively. Results: Among approximately 2.5 million patients, 65,667 patients were extracted from the electronic medical records, and assigned to case (N = 5,319) and control (N = 60,348) groups. In the XGB model, a combination of loop diuretic and histamine H₂ blocker [mean (|SHAP|) = 0.011] was identified as a relatively important risk factor for AKI. The combination of loop diuretic and H₂ blocker showed a significant synergistic interaction on an additive scale (RERI 1.289, 95% confidence interval 0.226-5.591) also in the LLR model. Conclusion: The present population-based case-control study using interpretable machine-learning models suggested that although the relative importance of the individual and combined effects of loop diuretics and H₂ blockers is lower than that of well-known risk factors such as older age and sex, concomitant use of a loop diuretic and histamine H₂ blocker is associated with increased risk of AKI.

Adverse event profiles of microscopic colitis in the Japanese Adverse Drug Event Report (JADER) database

Microscopic colitis (MC) is a chronic inflammatory bowel disease that is characterized by nonbloody watery diarrhea. The epidemiology in Japan differs from that in Europe and the United States, but little information is available from epidemiological surveys of MC in Japan. This study aimed to provide a new hypothesis regarding the factors associated with MC by using the Japanese Adverse Drug Event Report (JADER) database. "Colitis microscopic" (preferred term code: 10056979) cases entered into the JADER database between 2004 and 2021 were analyzed. Of the 246,997 cases in the JADER database, 161 cases were observed to be associated with MC. A Weibull analysis revealed that the median onset duration of MC (interquartile range) was 72.5 (36.0‒125.5) days in lansoprazole users and 116.0 (60.3‒1089.0) days in aspirin users. A multiple logistic regression analysis revealed that MC was significantly associated with the female sex, as well as ages ≥ 60 years and drugs including lansoprazole, aspirin, and nicorandil. A subset analysis revealed that MC was positively associated with obesity in female cases. Our study cannot demonstrate a causal inference between MC and each drug; however, the findings suggest that MC was associated with nicorandil as well as with lansoprazole and aspirin.

Baculovirus Display of Varicella–Zoster Virus Glycoprotein E Induces Robust Humoral and Cellular Immune Responses in Mice

Varicella–zoster virus (VZV) is the causative agent of varicella and herpes zoster (HZ) and can pose a significant challenge to human health globally. The initial VZV infection—more common in children—causes a self-limiting chicken pox. However, in later life, the latent VZV can become reactivated in these patients, causing HZ and postherpetic neuralgia (PHN), a serious and painful complication. VZV glycoprotein E (gE) has been developed into a licensed subunit vaccine against HZ (Shingrix). However, its efficacy relies on the concomitant delivery of a robust adjuvant (AS01B). Here, we sought to create a new immunogen for vaccine design by displaying the VZV–gE on the baculovirus surface (Bac–gE). Correct localization and display of gE on the engineered baculovirus was verified by flow cytometry and immune electron microscopy. We show that Bac–gE provides excellent antigenicity against VZV and induces not only stronger gE-specific CD4⁺ and CD8⁺ T cell responses but also higher levels of VZV–specific neutralizing antibodies as compared with other vaccine strategies in mice. Collectively, we show that the baculovirus display of VZV–gE confers ideal humoral and cellular immune responses required for HZ vaccine development, paving the way for a baculovirus-based vaccine design.

Valacyclovir-associated acute kidney injury

A man in his 70s presented to hospital with an acute kidney injury. He recently had started taking valacyclovir for treatment of shingles. The valacyclovir was stopped and his acute kidney injury improved. Work-up for other causes of acute kidney injury was negative and he was diagnosed with valacyclovir-associated acute kidney injury. He was discharged home after four days in the hospital with improving renal function.

Time until onset of acute kidney injury by combination therapy with “Triple Whammy” drugs obtained from Japanese Adverse Drug Event Report database

Acute kidney injury (AKI) associated with “Triple Whammy” drug therapy consisting of renin-angiotensin system inhibitors, diuretics, and nonsteroidal anti-inflammatory drugs (NSAIDs) has been reported. There have been no reports investigating “Triple Whammy” drug therapy and the time to AKI onset using adverse drug events report databases. The aim of this study was to determine the relationship between the time to AKI onset and treatment with “Triple Whammy” drug therapy. We analyzed AKI cases registered in the Japanese Adverse Drug Event Report database. The data were analyzed using the Kaplan–Meier approach, generalized Wilcoxon tests, and Weibull distribution. AKI was reported in 18,415 cases, of which 7,466 cases used Triple Whammy drugs. All combinations of Triple Whammy drugs were associated with significantly higher odds ratios for reporting AKI. In Weibull analysis, AKI onset was early for most combination patterns of Triple Whammy drugs. The Kaplan–Meier approach showed that the treatment duration to AKI onset was much shorter in cases using NSAIDs; median onsets, 8 days for triple combination, 7 days for NSAIDs added to renin-angiotensin system inhibitors, 9 days for NSAIDs added to diuretics, 6 days for diuretics added to NSAIDs, and 9 days for NSAIDs alone. AKI associated with Triple Whammy drugs is likely to occur in the early stages of treatment, especially with concomitant NSAIDs. Patients should be monitored for the occurrence of AKI within the first 2 weeks.

Possibility of Multiple Drug-Drug Interactions in Patients Treated with Statins: Analysis of Data from the Japanese Adverse Drug Event Report (JADER) Database and Verification by Animal Experiments

Adverse drug events due to drug-drug interactions can be prevented by avoiding concomitant use of causative drugs; therefore, it is important to understand drug combinations that cause drug-drug interactions. Although many attempts to identify drug-drug interactions from real-world databases such as spontaneous reporting systems have been performed, little is known about drug-drug interactions caused by three or more drugs in polypharmacy, i.e., multiple drug-drug interactions. Therefore, we attempted to detect multiple drug-drug interactions using decision tree analysis using the Japanese Adverse Drug Event Report (JADER) database, a Japanese spontaneous reporting system. First, we used decision tree analysis to detect drug combinations that increase the risk of rhabdomyolysis in cases registered in the JADER database that used six statins. Next, the risk of three or more drug combinations that significantly increased the risk of rhabdomyolysis was validated with in vivo experiments in rats. The analysis identified a multiple drug-drug interaction signal only for pitavastatin. The reporting rate of rhabdomyolysis for pitavastatin in the JADER database was 0.09, and it increased to 0.16 in combination with allopurinol. Furthermore, the rate was even higher (0.40) in combination with valsartan. Additionally, necrosis of leg muscles was observed in some rats simultaneously treated with these three drugs, and their creatine kinase and myoglobin levels were elevated. The combination of pitavastatin, allopurinol, and valsartan should be treated with caution as a multiple drug-drug interaction. Since multiple drug-drug interactions were detected with decision tree analysis and the increased risk was verified in animal experiments, decision tree analysis is considered to be an effective method for detecting multiple drug-drug interactions.

BRAF/MEK inhibitor-associated nephrotoxicity in a real-world setting and human kidney cells

Acute kidney injury (AKI) associated with cancer chemotherapy can be life-threatening. Inhibitors of rapidly accelerated fibrosarcoma kinase B (BRAF)-mutants and mitogen-activated extracellular signal-regulated kinase (MEK) administered as combination therapy are effective against BRAF-mutant melanoma, but drug-associated AKI events were reported after marketing. Here, we examined the nephrotoxicity of two BRAF inhibitors, vemurafenib and dabrafenib, and two MEK inhibitors, cobimetinib and trametinib, in a real-world setting and human kidney cells. Target drug-associated AKI signals were detected by reporting odds ratio (ROR) derived from report data in the Food and Drug Administration Adverse Events Reporting System database. In-vitro cytotoxicity was evaluated in proximal renal tubular epithelial cells (RPTEC), glomerular endothelial cells (GEnC), and glomerular epithelial cells (GEpC).

RESULTS

AKI RORs associated with vemurafenib [ROR, 3.28; confidence interval (CI), 2.91-3.69] and cobimetinib (ROR, 4.40; CI, 3.55-5.45) were higher than those associated with dabrafenib (ROR, 1.35; CI, 1.15-1.60) and trametinib (ROR, 1.32; CI, 1.11-1.56). Vemurafenib reduced cell viability and increased cell death in RPTEC and GEpC at 10 μM, which was below the mean maximum concentration in blood under steady-state condition [115.7 μM (56.7 μg/mL)]. No vemurafenib-associated cytotoxicity was detected in GEnC. Mean maximum concentrations of cobimetinib, dabrafenib and trametinib did not induce cell death.

CONCLUSION

This work revealed that vemurafenib had stronger cytotoxic effects on tubular and glomerular epithelial cells than the other BRAF and MEK inhibitors. Hence, we recommend careful monitoring for clinical signs of kidney injury in patients treated with vemurafenib.

Evaluation of Potential Complications of Interstitial Lung Disease Associated With Antiandrogens Using Data From Databases Reporting Spontaneous Adverse Effects

From 2002 to 2018, the number of patients with prostate cancer significantly increased from 679,023 to 1276,106 worldwide. Total prostatectomy (including robot-assisted prostatectomy), radiation therapy, and pharmacological treatment are commonly used to treat prostate cancer. The Chief of the Pharmaceutical Safety Division, that is, the Federation of Pharmaceutical Manufacturers’ Associations of Japan (FPMAJ), recently called for the revision of package inserts for ethical drugs. However, the pathogenesis of interstitial lung disease (ILD), a serious drug-induced adverse effect, remains unclear. Moreover, there have been no large-scale evaluations of potential complications associated with currently used antiandrogens, which are commonly employed to treat prostate cancer. Hence, ILD, as an adverse event, remains poorly understood. Therefore, we conducted a survey of reports in the Japanese Adverse Drug Event Report (JADER) database to investigate the potential association between the reporting of ILD and antiandrogen drug use in clinical practice. The occurrence of ILD was investigated by evaluating the relationship between antiandrogen drug use and ILD. Adverse event signals were detected with reporting odds ratios (RORs), using data from the JADER and FDA Adverse Event Reporting System (FAERS) databases, for the analysis of post-marketing adverse event reports. The JADER was used to examine the time profile of adverse event occurrence for each drug, whereas the FAERS was used to screen cases of unknown adverse events and analyze their trends of occurrence. The analysis of data from both databases revealed the 95% confidence interval lower limits of ROR for bicalutamide and flutamide to be > 1, and adverse event signals were detected following the use of either drug. While caution should be exercised for drugs that are new to the market, we conclude that drugs with similar therapeutic effects that have been in use for a long period should also be re-examined for potential adverse events.

[Potential for Big Data Analysis Using AI in the Field of Clinical Pharmacy]

Industrial reforms utilizing artificial intelligence (AI) have advanced remarkably in recent years. The application of AI to big data analysis in the medical information field has also been advancing and is expected to be used to find drug adverse effects that cannot be predicted by conventional methods. We have developed an adverse drug reactions analysis system that uses machine learning and data from the Japanese Adverse Drug Event Report (JADER) database. The system was developed using the C# programming language and incorporates the open source machine learning library Accord.Net. Potential analytical capabilities of the system include discovering unknown drug adverse effects and evaluating drug-induced adverse events in pharmaceutical management. However, to apply the system to pharmaceutical management, it is important to examine the characteristics and suitability of the level of AI used in the system and to select statistical methods or machine learning when appropriate. If these points are addressed, there is potential for pharmaceutical management to be individualized and optimized in the clinical setting by using the developed system to analyze big data. The system also has the potential to allow individual healthcare facilities such as hospitals and pharmacies to contribute to drug repositioning, including the discovery of new efficacies, interactions, and drug adverse events.