Signal Detection of Potential Hepatotoxic Drugs: Case-Control Study Using Both a Spontaneous Reporting System and Electronic Medical Records

Decreased Hepatic Functional Reserve Increases the Risk of Piperacillin/Tazobactam-Induced Abnormal Liver Enzyme Levels: A Retrospective Case-Control Study

BACKGROUND

Piperacillin/tazobactam (PIPC/TAZ), which is a combination of a beta-lactam/beta-lactamase inhibitor, often causes liver enzyme abnormalities. The albumin-bilirubin (ALBI) score is a simple index that uses the serum albumin and total bilirubin levels for estimating hepatic functional reserve. Although patients with low hepatic reserve may be at high risk for drug-induced liver enzyme abnormalities, the relationship between PIPC/TAZ-induced abnormal liver enzymes levels and the ALBI score remains unknown.

OBJECTIVE

This study aimed to elucidate the relationship between PIPC/TAZ-induced abnormal liver enzyme levels and the ALBI score.

METHODS

This single-center retrospective case-control study included 335 patients. The primary outcome was PIPC/TAZ-induced abnormal liver enzyme levels. We performed COX regression analysis with male gender, age (≥75 years), alanine aminotransferase level (≥20 IU/L), and ALBI score (≥-2.00) as explanatory factors. To investigate the influence of the ALBI score on the development of abnormal liver enzyme levels, 1:1 propensity score matching between the ≤-2.00 and ≥-2.00 ALBI score groups was performed using the risk factors for drug-induced abnormal liver enzyme levels.

RESULTS

The incidence of abnormal liver enzyme levels was 14.0% (47/335). COX regression analysis revealed that an ALBI score ≥-2.00 was an independent risk factor for PIPC/TAZ-induced abnormal liver enzyme levels (adjusted hazard ratio: 3.08, 95% coefficient interval: 1.207-7.835, P = 0.019). After 1:1 propensity score matching, the Kaplan-Meier curve revealed that the cumulative risk for PIPC/TAZ-induced abnormal liver enzyme levels was significantly higher in the ALBI score ≥-2.00 group (n = 76) than in the <-2.00 group (n = 76) (P = 0.033).

CONCLUSION AND RELEVANCE

An ALBI score ≥-2.00 may predict the development of PIPC/TAZ-induced abnormal liver enzyme levels. Therefore, frequent monitoring of liver enzymes should be conducted to minimize the risk of severe PIPC/TAZ-induced abnormal liver enzyme levels in patients with low hepatic functional reserve.

Pharmacovigilance Strategies to Address Resistance to Antibiotics and Inappropriate Use-A Narrative Review

The spread of antimicrobial resistance (AMR) is a global challenge. Close and continuous surveillance for quick detection of AMR can be difficult, especially in remote places. This narrative review focuses on the contributions of pharmacovigilance (PV) as an auxiliary tool for identifying and monitoring the ineffectiveness, resistance, and inappropriate use of antibiotics (ABs). The terms "drug ineffective", "therapeutic failure", "drug resistance", "pathogen resistance", and "multidrug resistance" were found in PV databases and dictionaries, denoting ineffectiveness. These terms cover a range of problems that should be better investigated because they are useful in warning about possible causes of AMR. "Medication errors", especially those related to dose and indication, and "Off-label use" are highlighted in the literature, suggesting inappropriate use of ABs. Hence, the included studies show that the terms of interest related to AMR and use are not only present but frequent in PV surveillance programs. This review illustrates the feasibility of using PV as a complementary tool for antimicrobial stewardship activities, especially in scenarios where other resources are scarce.

Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review

INTRODUCTION

Pharmacovigilance programs protect patient health and safety by identifying adverse event signals through postmarketing surveillance of claims data and spontaneous reports. Electronic health records (EHRs) provide new opportunities to address limitations of traditional approaches and promote discovery-oriented pharmacovigilance.

METHODS

To evaluate the current state of EHR-based medication safety signal identification, we conducted a scoping literature review of studies aimed at identifying safety signals from routinely collected patient-level EHR data. We extracted information on study design, EHR data elements utilized, analytic methods employed, drugs and outcomes evaluated, and key statistical and data analysis choices.

RESULTS

We identified 81 eligible studies. Disproportionality methods were the predominant analytic approach, followed by data mining and regression. Variability in study design makes direct comparisons difficult. Studies varied widely in terms of data, confounding adjustment, and statistical considerations.

CONCLUSION

Despite broad interest in utilizing EHRs for safety signal identification, current efforts fail to leverage the full breadth and depth of available data or to rigorously control for confounding. The development of best practices and application of common data models would promote the expansion of EHR-based pharmacovigilance.

Risk evaluation of carbapenem-induced liver injury based on machine learning analysis

INTRODUCTION

Information regarding carbapenem-induced liver injury is limited, and the rate of liver injury caused by meropenem (MEPM) and doripenem (DRPM) remains unknown. Decision tree (DT) analysis, a machine learning method, has a flowchart-like model where users can easily predict the risk of liver injury. Thus, we aimed to compare the rate of liver injury between MEPM and DRPM and construct a flowchart that can be used to predict carbapenem-induced liver injury.

METHODS

We investigated patients treated with MEPM (n = 310) or DRPM (n = 320) and confirmed liver injury as the primary outcome. We used a chi-square automatic interaction detection algorithm to construct DT models. The dependent variable was set as liver injury from a carbapenem (MEPM or DRPM), and factors including alanine aminotransferase (ALT), albumin-bilirubin (ALBI) score, and concomitant use of acetaminophen were used as explanatory variables.

RESULTS

The rates of liver injury were 22.9% (71/310) and 17.5% (56/320) in the MEPM and DRPM groups, respectively; no significant differences in the rate were observed (95% confidence interval: 0.710-1.017). Although the DT model of MEPM could not be constructed, DT analysis showed that the incidence of introducing DRPM in patients with ALT >22 IU/L and ALBI scores > -1.87 might be high-risk.

CONCLUSIONS

The risk of developing liver injury did not differ significantly between the MEPM and DRPM groups. Since ALT and ALBI score are evaluated in clinical settings, this DT model is convenient and potentially useful for medical staff in assessing liver injury before DRPM administration.

Benzodiazepine-related dementia risks and protopathic biases revealed by multiple-kernel learning with electronic medical records

Objectives

To simultaneously estimate how the risk of incident dementia nonlinearly varies with the administration period and cumulative dose of benzodiazepines, the duration of disorders with an indication for benzodiazepines, and other potential confounders, with the goal of settling the controversy over the role of benzodiazepines in the development of dementia.

Methods

The classical hazard model was extended using the techniques of multiple-kernel learning. Regularised maximum-likelihood estimation, including determination of hyperparameter values with 10-fold cross-validation, bootstrap goodness-of-fit test, and bootstrap estimation of confidence intervals, was applied to cohorts retrospectively extracted from electronic medical records of our university hospitals between 1 November 2004 and 31 July 2020. The analysis was mainly focused on 8160 patients aged 40 or older with new onset of insomnia, affective disorders, or anxiety disorders, who were followed up for 4.10 ± 3.47 years.

Results

Besides previously reported risk associations, we detected significant nonlinear risk variations over 2-4 years attributable to the duration of insomnia and anxiety disorders, and to the administration period of short-acting benzodiazepines. After nonlinear adjustment for potential confounders, we observed no significant risk associations with long-term use of benzodiazepines.

Conclusions

The pattern of the detected nonlinear risk variations suggested reverse causation and confounding. Their putative bias effects over 2-4 years suggested similar biases in previously reported results. These results, together with the lack of significant risk associations with long-term use of benzodiazepines, suggested the need to reconsider previous results and methods for future analysis.

Effect of Ceftriaxone Dosage and Albumin-Bilirubin Score on the Risk of Ceftriaxone-Induced Liver Injury

The albumin-bilirubin (ALBI) score is an index of hepatic functional reserve and is calculated from serum albumin and total bilirubin levels. However, the relationship between ceftriaxone (CTRX)-induced liver injury and ALBI score remains unknown. Therefore, we aimed to elucidate the risk of CTRX-induced liver injury based on the ALBI scores and CTRX dosage. This was a single-center, retrospective, case-control study of 490 patients and the primary outcome was CTRX-induced liver injury. We performed a COX regression analysis using age ≥75 years, male sex, alanine aminotransferase levels, ALBI score, and CTRX dosage regimen (4 ≥2 or 1 g/d) as explanatory factors. We also performed 1 : 1 propensity score matching between non-liver injury and liver injury groups. The incidence of liver injury was 10.0% (49/490). In COX regression analysis, CTRX 4 g/d was an independent risk factor for liver injury (95% coefficient interval: 1.05-6.96, p = 0.04). Meanwhile, ALBI score ≥-1.61 was an independent factor for liver injury (95% coefficient interval: 1.03-3.22, p = 0.04) with the explanatory factor of ≥2 and 1 g/d. The Kaplan-Meier curve indicated that the cumulative risk for CTRX-induced liver injury was significantly higher in the ALBI score ≥-1.61 group than in the ALBI score <-1.61 group before propensity score matching (p = 0.032); however, no significant differences were observed after propensity score matching (p = 0.791). These findings suggest that in patients treated with CTRX with ALBI score ≥-1.61, frequent liver function monitoring should be considered.

Highlights of the drug-induced liver injury literature for 2021

INTRODUCTION

In 2021, over 3,000 articles on Drug-Induced Liver Injury (DILI) were published, nearly doubling the annual number compared to 2011. This review selected DILI articles from 2021 we felt held the greatest interest and clinical relevance.

AREAS COVERED

A literature search was conducted using PubMed between 1 March 2021 and 28 February 2022. 86 articles were included. This review discusses new and established cases of hepatotoxins, including new FDA approvals and COVID-19 therapeutics. Developments in biomarkers and causality assessment methods are discussed. Updates from registries are also explored.

EXPERT OPINION

DILI diagnosis and prognostication remain challenging. Roussel Uclaf Causality Assessment Method (RUCAM) is the best option for determining causality and has been increasingly accepted by clinicians. Revised Electronic Causality Assessment Method (RECAM) may be more user-friendly and accurate but requires further validation. Quantitative systems pharmacology methods, such as DILIsym, are increasingly used to predict hepatotoxicity. Oncotherapeutic agents represent many newly approved and described causes of DILI. Such hepatotoxicity is deemed acceptable relative to the benefit these drugs offer. Drugs developed for non-life-threatening disorders may not show a favorable benefit-to-risk ratio and will be more difficult to approve. As the COVID-19 landscape evolves, its effect on DILI deserves further investigation.

Detection of Synergistic Interaction on an Additive Scale Between Two Drugs on Abnormal Elevation of Serum Alanine Aminotransferase Using Machine-Learning Algorithms

Drug-induced liver injury (DILI) is a common adverse drug reaction, with abnormal elevation of serum alanine aminotransferase (ALT). Several clinical studies have investigated whether a combination of two drugs alters the reporting frequency of DILI using traditional statistical methods such as multiple logistic regression (MLR), but this model may over-fit the data. This study aimed to detect a synergistic interaction between two drugs on the risk of abnormal elevation of serum ALT in Japanese adult patients using three machine-learning algorithms: MLR, logistic least absolute shrinkage and selection operator (LASSO) regression, and extreme gradient boosting (XGBoost) algorithms. A total of 58,413 patients were extracted from Nihon University School of Medicine's Clinical Data Warehouse and assigned to case (N = 4,152) and control (N = 54,261) groups. The MLR model over-fitted a training set. In the logistic LASSO regression model, three combinations showed relative excess risk due to interaction (RERI) for abnormal elevation of serum ALT: diclofenac and famotidine (RERI 2.427, 95% bootstrap confidence interval 1.226-11.003), acetaminophen and ambroxol (0.540, 0.087-4.625), and aspirin and cilostazol (0.188, 0.135-3.010). Moreover, diclofenac (adjusted odds ratio 1.319, 95% bootstrap confidence interval 1.189-2.821) and famotidine (1.643, 1.332-2.071) individually affected the risk of abnormal elevation of serum ALT. In the XGBoost model, not only the individual effects of diclofenac (feature importance 0.004) and famotidine (0.016), but also the interaction term (0.004) was included in important predictors. Although further study is needed, the combination of diclofenac and famotidine appears to increase the risk of abnormal elevation of serum ALT in the real world.