Leukotriene-modifying agents may increase the risk of depression: A cross-sectional study

INTRODUCTION

Post-market monitoring has shown a potential link between the use of leukotriene-modifying agents (LTRAs) and an increased risk of neuropsychiatric events, such as depression. However, observational studies have produced inconsistent findings, offering no definitive conclusions.

OBJECTIVE

To assess the potential correlation between LTRAs exposure and depression in US adults.

METHOD

This cross-sectional study, based on population data from the National Health and Nutrition Examination Survey (NHANES) 2007-2016 cycle. The Patient Health Questionnaire-9 was used to assess depression. Multivariable regression was used to evaluate the association between LTRAs exposure and depression. Sensitivity and subgroup analyses were conducted, with the calculation of the E-value. Network pharmacology was employed to investigate the influence of LTRAs on mechanisms of depression.

RESULTS

Among the 9414 participants, 595 (6.3 %) were classified as having depression. LTRAs exposure was associated with a higher prevalence of depression (16.9 % vs. 6.0 %). The multivariable logistic regression results showed that LTRAs use increased the risk of depression (OR = 1.70; 95 % CI, 1.05-2.75). An association between LTRAs exposure and depression was found in sensitivity analyses conducted regardless of multivariable linear regression with the PHQ-9 score as a continuous variable (β = 0.97; 95 % CI, 0.44-1.50) or multivariable logistic regression with the PHQ-9 cut-off of 5 (OR = 1.52; 95 % CI, 1.08-2.14). The association between LTRAs and depression was stable in the different subgroups.

CONCLUSION

LTRAs exposure is positively associated with depression in US adults. Therefore, the risk for depression in patients receiving long-term LTRAs treatment should be considered.

A Pilot, Predictive Surveillance Model in Pharmacovigilance Using Machine Learning Approaches

INTRODUCTION

The identification of a new adverse event (AE) caused by a drug product is one of the key activities in the pharmaceutical industry to ensure the safety profile of a drug product. Machine learning (ML) has the potential to assist with signal detection and supplement traditional pharmacovigilance (PV) surveillance methods. This pilot ML modeling study was designed to detect potential safety signals for two AbbVie products and test the model's capability of detecting safety signals earlier than humans.

METHODS

Drug X, a mature product with post-marketing data, and Drug Y, a recently approved drug in another therapeutic area, were selected. Gradient boosting-based ML approaches (e.g., XGBoost) were applied as the main modeling strategy.

RESULTS

For Drug X, eight true signals were present in the test set. Among 12 potential new signals generated, four were true signals with a 50.0% sensitivity rate and a 33.3% positive predictive value (PPV) rate. Among the remaining eight potential new signals, one was confirmed as a signal and detected six months earlier than humans. For Drug Y, nine true signals were present in the test set. Among 13 potential new signals generated, five were true signals with a 55.6% sensitivity rate and a 38.5% PPV rate. Among the remaining eight potential new signals, none were confirmed as true signals upon human review.

CONCLUSION

This model demonstrated acceptable accuracy for safety signal detection and potential for earlier detection when compared to humans. Expert judgment, flexibility, and critical thinking are essential human skills required for the final, accurate assessment of adverse event cases.

Pembrolizumab-induced Stevens-Johnson syndrome/Toxic Epidermal Necrolysis in a Vietnamese patient with nonsmall-cell lung cancer

Chemoimmunotherapy is an effective therapy for an individual with nonsmall-cell lung cancer (NSCLC) without anaplastic lymphoma kinase or epidermal growth factor receptor mutations. However, it can also be related to adverse cutaneous reactions such as Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) with high morbidities and mortality rates. We present a case of a 65-year-old male with NSCLC who underwent first-line chemotherapy with paclitaxel, carboplatin, and pembrolizumab, which was later followed by a second cycle of the same therapies. The patient developed a fever and rash 12 days after the second cycle. Pembrolizumab was strongly suspected as the culprit medication because cutaneous reactions to this drug have been frequently reported and threw other medications used as less likely candidates. This is the first case reported in Vietnam of SJS/TEN related to pembrolizumab and contributes to our knowledge of severe skin reactions associated with immune checkpoint inhibitors.

NSAID (nonsteroidal anti-inflammatory drugs) Induced Stevens Johnson Syndrome in a 50-year-old woman: A case study

Stevens-Johnson Syndrome (SJS) is a severe and rare adverse drug reaction associated with significant morbidity and mortality. Although SJS is commonly triggered by multiple drugs, non-steroidal anti-inflammatory drugs (NSAIDs), including diclofenac, have been frequently implicated. A middle-aged woman, who is 50 years old, has a prior medical record of high blood pressure, type 2 diabetes, and has recently suffered from a pulmonary embolism. She was later admitted to the intensive care unit (ICU), where she was ultimately diagnosed with Steven Johnson syndrome. Careful drug selection, close monitoring of patients with predisposing factors, and prompt identification of adverse events are crucial to prevent severe drug reactions.

Antibiotic-associated vanishing bile duct syndrome: a real-world retrospective and pharmacovigilance database analysis

PURPOSE

Vanishing bile duct syndrome (VBDS) is a rare, but potentially fatal adverse reaction triggered by certain medications. Few real-world studies have shown association between antibiotics and VBDS. We sought to quantify the risk and evaluate the clinical features of VBDS associated with antibiotics.

METHODS

Data from 2004 to 2022 on VBDS events induced by antibiotics were retrieved from the FDA Adverse Event Reporting System (FAERS) database and disproportionality analyses were conducted. Furthermore, case reports from 2000 to 31 December 2022 on antibiotics-induced VBDS were retrieved for retrospective analysis.

RESULTS

We collected 132 VBDS reports from the FAERS database. Fluoroquinolones had the greatest proportion and highest positive signal values of VBDS. The RORs (95% CIs) for antibiotics were fluoroquinolones 23.68 (18.12-30.95), macrolides 19.37 (13.58-27.62), carbapenems 17.39 (7.77-38.96), beta-lactam 13.28 (9.69-18.20), trimethoprim/sulfamethoxazole 9.05 (5.57-14.7), and tetracycline 4.02 (1.50-10.77). Twenty-three cases from 22 studies showed evidence of VBDS, beta-lactam (52.2%) was the most frequently reported agent. The median age was 45 years, the typical initial symptoms included rash (30.4%), fatigue/asthenia (26.1%), dark urine (21.7%) and Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN) (21.7%). The median time to onset of VBDS was 2 weeks. All cases had abnormal liver function test, and the median level of total bilirubin was 23.6 mg/dl (range 3.2-80 mg/dl). Cessation of culprit drugs and treatment with ursodeoxycholic acid (83.3%) were not associated with improved outcomes (57.1%).

CONCLUSION

This study identified thirteen antibacterial agents with significant reporting associations with VBDS. Fluoroquinolones may be a neglected agent of inducing VBDS.

[Drug reaction with eosinophilia and systemic symptoms (DRESS): a hypersensitivity reaction with various symptoms]

Drug reaction with eosinophilia and systemic symptoms (DRESS) is an illness which is difficult to diagnose because of its various symptoms. In our case, a patient with small spotted exanthema with nearly erythroderma and eosinophilia presented to the emergency room. Systemic steroid therapy was started on suspicion of a drug reaction. Over the course of time, the patient's general condition deteriorated significantly and the patient developed cholecystitis, Staphylococcus aureus bacteremia, pneumonitis and cytomegalovirus reactivation. With this case report, we want to show that DRESS is a disease that is difficult to treat and can develop after a long delay.

Drug-induced Tongue Disorders: A Comprehensive Literature Review

BACKGROUND

Some drugs cause tongue disorders as adverse effects. Most of the druginduced tongue disorders are benign and will resolve after drug discontinuation. However, the changes in the color or appearance of the tongue may frighten patients and decrease compliance with drug therapy.

OBJECTIVE

To review the literature to find all reports of drug-induced tongue disorders, their presentation, management, and outcome of patients Methods: The search was conducted in Google Scholar and PubMed using key words "ageusia," "burning tongue," "coated tongue," "drug-induced taste disturbances," "dysgeusia," "glossitis," "glossodynia," "hairy tongue," "hypogeusia," "stomatodynia," "stomatopyrosis," "swollen tongue" "tongue discoloration," "tongue irritation," "tongue numbness, "tongue oedema," and "tongue ulcer. All reports that were published from 1980 to 2022 in the English language were included in the study. Reports that were not in English language but had English abstracts with adequate data for extraction were also included.

RESULTS

A total of 208 case reports and case series were included. The most reported drug classes were antineoplastic and immunomodulating agents and anti-infectives for systemic use, and the most common tongue disorders were tongue discoloration and black hairy tongue. Having good oral hygiene and discontinuing the offending drug could manage and resolve the problem.

CONCLUSION

Drug-induced tongue disorders are not rare adverse drug reactions. They are benign in most cases, and withholding offending agents results in significant improvement or complete resolution of tongue lesions.

Safety of Empagliflozin: An Individual Participant-Level Data Meta-Analysis from Four Large Trials

INTRODUCTION

Empagliflozin is a sodium-glucose co-transporter-2 inhibitor used to treat type 2 diabetes (T2D) to improve glycemic control, reduce risk of cardiovascular death in patients with T2D, and treat patients with symptomatic chronic heart failure (HF) and chronic kidney disease (CKD). The safety profile of empagliflozin is well documented, although adverse events (AEs) remain of interest to clinicians. This study provides an up-to-date safety evaluation of empagliflozin.

METHODS

Data were pooled from four long-term trials which included: patients with T2D and established cardiovascular disease (EMPA-REG OUTCOME), patients with HF, with/without diabetes (EMPEROR-Reduced and EMPEROR-Preserved), and patients with CKD, with/without diabetes (EMPA-KIDNEY). Since three of the four trials evaluated empagliflozin 10 mg, the meta-analysis was restricted to this dose.

RESULTS

Total trial medication exposure was 19,727 patient-years for patients who received empagliflozin (n = 10,472) and 19,447 patient-years for placebo (n = 10,461). The percentages of patients with serious AEs, fatal AEs, and AEs leading to discontinuation were similar for both groups. The incidences of serious urinary tract infection and serious pyelonephritis or urosepsis were similar for both groups but higher for women taking empagliflozin versus placebo. Serious genital infections were not increased with empagliflozin versus placebo. There was a slight increase in ketoacidosis and serious volume depletion in patients who received empagliflozin versus placebo. The occurrence of serious acute kidney injury was lower with empagliflozin versus placebo. Empagliflozin was not associated with an increased incidence of severe hypoglycemia, bone fractures, or lower limb amputations. Empagliflozin is therefore considered safe in people without diabetes, the elderly, patients with very low estimated glomerular filtration rate, low body mass index, and HF. Safety is unaltered by blood pressure, concomitant medication for hypertension, HF, and immunosuppression.

CONCLUSION

This meta-analysis of long-term safety data extends current knowledge and confirms the safety and tolerability of empagliflozin.

Polypharmacy, drug-drug interactions, and adverse drug reactions among systemic sclerosis patients: A cross-sectional risk factor study

OBJECTIVES

Polypharmacy, drug-drug interactions (DDI) and related adverse drug reaction (ADR) are understudied in SSc. The aim of this work was to determine the prevalence and determinants of DDI and ADR in a real-life prospective cohort of SSc patients.

METHODS

We performed a retrospective analysis of the drug prescriptions of SSc patients admitted to the daily scleroderma clinic between January 2020 and April 2022. DDI were identified using 2 prescription analysis applications, and adjudicated related ADRs occurring during a one-year follow-up were reported. Risk factors for DDI and ADR were identified using multivariate analysis.

RESULTS

One hundred and eight SSc patients were included. The median number of medications per patient was 6 [4-9]. Seventy-one (65.7 %) patients had 5 or more medications, and 23 (21.3 %) had 10 or more. Seventy-two (66.7 %) patients had DDIs on their prescriptions at inclusion. Patients with DDIs had more medications than patients without DDIs (7 [5-10] versus 3 [2-5], p < 0.0001). Six (8.3) patients experienced ADRs during the one-year follow-up. Patients with ADRs had more medications (14 [10-18] versus 7 [5-10] p < 0.001) and more DDIs (12 [7-32] versus 3 [1-6]; p < 0.001) than patients without ADRs. Multivariate analysis confirmed that the number of prescribed medications was independently positively associated with DDIs (OR: 2.25 [1.52-3.32], p < 0.0001) as well as with ADRs (OR: 1.68 [1.17-2.40], p < 0.01).

CONCLUSIONS

SSc patients are significantly exposed to polypharmacy, DDIs and related ADRs, particularly in cases of severe illness, and especially if 5 or more medications are prescribed.

Emerging pharmacotherapy for the treatment of cannabis use disorder

INTRODUCTION

About one-fifth of cannabis users, the most commonly used illicit substance, have cannabis use disorder (CUD). Psychiatric disorders and suicide are more common in these patients, and the disability-adjusted life years were reported to be 0.69 million. Pharmacotherapy for CUD is an unmet public health need, as current evidence-based therapies have limited efficacy.

AREAS COVERED

After explaining the pathophysiology of CUD, the effects of emerging pharmacological interventions in its treatment obtained from randomized controlled trials were reviewed in light of mechanisms of action. Superiority over control of cannabidiol, gabapentin, galantamine, nabilone plus zolpidem, nabiximols, naltrexone, PF-04457845, quetiapine, varenicline, and topiramate were observed through the cannabinoid, glutamatergic, γ-aminobutyric acidergic, serotonergic, noradrenergic, dopaminergic, opioidergic, and cholinergic systems. All medications were reported to be safe and tolerable.

EXPERT OPINION

Adding pharmacotherapy to psychotherapy is the optimal treatment for CUD on a case-by-case basis. Drug development to add to psychotherapy is the main path, but time and cost suggest repurposing and repositioning existing drugs. Considering sample size, follow-up, and effect size, further studies using objective tools are necessary. The future of CUD treatment is promising.

TIRPnet: Risk prediction of traditional Chinese medicine ingredients based on a deep neural network

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese medicine (TCM) has a history of over 3000 years of medical practice. Due to the complex ingredients and unclear pharmacological mechanism of TCM, it is very difficult to predict its risks. With the increase in the number and severity of spontaneous reports of adverse drug reactions (ADRs) of TCM, its safety has received widespread attention.

AIM OF THE STUDY

In this study, we proposed a framework based on deep learning to predict the probability of adverse reactions caused by TCM ingredients and validated the model using real-world data.

MATERIALS AND METHODS

The spontaneous reporting data from Jiangsu Province of China was selected as the research data, which included 72,561 ADR reports of TCMs. All the ingredients of these TCMs were collected from the medical website and correlated with the corresponding ADRs. Then, a risk prediction model was constructed based on a deep neural network (DNN), named TIRPnet. Based on one-hot encoded data, our model achieved the optimal performance by fine-tuning some hyperparameters. The ten most commonly used TCM ingredients and their ADRs were collected as the test set to evaluate their performance as objective criteria.

RESULTS

TIRPnet was constructed as a 7-layer DNN. The experimental results showed that TIRPnet performs excellently in all indicators, with a sensitivity of 0.950, specificity of 0.995, accuracy of 0.994, precision of 0.708, and F1 of 0.811.

CONCLUSIONS

The proposed TIRPnet owns the ability to predict the ADRs of a single TCM ingredient by learning a large number of TCM-related spontaneous reports, which can help doctors design safe prescriptions and provide technical support for the pharmacovigilance of TCM.

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.

Drug-related hypophosphatemia: Descriptive study and case/non-case analysis of the French national pharmacovigilance database

Phosphorus is an essential element for all living organisms and is involved in various biological pathways. A severe hypophosphatemia can lead to serious complications (acute heart or respiratory failure, rhabdomyolysis, hemolysis…) and increases mortality in patients at risk. Various drugs are known to induce hypophosphatemia through various mechanisms. The aim of this study was to highlight the main drugs associated with hypophosphatemia and to deduce the underlying mechanisms based on a descriptive analysis and a case/non-case analysis using the cases of drug-induced hypophosphatemia reported to the French Pharmacovigilance Network. A total of 368 cases of hypophosphatemia were included in the study. Patients' mean age was 52±18 years. One hundred and ninety-one cases (52%) were serious including 131 (36%) hospitalizations. The median value of serum phosphorus level was 0.54mmol/L [0.40-0.66] (n=309). Those 368 cases corresponded to 185 different suspected substances among which the most frequent drugs were tenofovir disoproxil (n=175; 48%), ferric carboxymaltose (n=29; 8%), denosumab (n=16; 4%), zoledronic acid (n=14; 4%) and hydrochlorothiazide (n=10; 3%). For these five drugs, a significant disproportionality was found. Tenofovir-disoproxil related hypophosphatemia occurred more than one year after its introduction, and a renal tubulopathy (Fanconi's syndrome) was reported in 44 cases (25%). Hypophosphatemia related to iron carboxymaltose occurred within a median of 20 days after injection and was mostly severe. Mechanism included the fibroblast growth factor 23 which can be measured to confirm drug origin. Concerning anti-osteoporosis treatments, hypophosphatemia could be explained by their mechanism of action (abrupt increase of parathormone induced by hypocalcemia) but the patient history (malignancy condition) was a major bias. For hydrochlorothiazide, hyphosphatemia was often moderate, associated with other electrolytic disturbances and occurred during a long-term treatment. Awareness of healthcare professionals is essential to detect as soon as possible hypophosphatemia and its complications related to these drugs.

Knowledge Graphs in Pharmacovigilance: A Step-By-Step Guide

PURPOSE

This work aims to demystify Knowledge Graphs (KGs) in pharmacovigilance (PV). It complements the scoping review within this issue. By bridging knowledge gaps and stimulating interest, further engagement with this topic by pharmacovigilance professionals will be facilitated.

METHODS

We elucidate fundamental KGs concepts and terminology, followed by delineating a sequence of implementation steps: use case definition, data type selection, data sourcing, KG construction, KG embedding, and deriving actionable insights. Information technology options and limitations are also explored.

FINDINGS

KGs in pharmacovigilance is a multi-disciplinary field involving information technology, machine learning, biology, and PV. We were able to synthesize the relevant core concepts to create an intuitive exposition of KGs in PV.

IMPLICATIONS

This work demystifies KGs with a pharmacovigilance focus, preparing readers for the accompanying in-depth scoping review. that follows. It lays the groundwork for advancing PV research and practice by emphasizing the importance of engaging with vigilance experts. This approach enhances knowledge sharing and collaboration, contributing to more effective and informed pharmacovigilance efforts and optimal assessment and deployment of KGs in PV.

Machine learning algorithms to predict colistin-induced nephrotoxicity from electronic health records in patients with multidrug-resistant gram-negative infection

OBJECTIVES

Colistin-induced nephrotoxicity prolongs hospitalisation and increases mortality. The study aimed to construct machine learning models to predict colistin-induced nephrotoxicity in patients with multidrug-resistant Gram-negative infection.

METHODS

Patients receiving colistin from three hospitals in the Clinical Research Database were included. Data were divided into a derivation cohort (2011-2017) and a temporal validation cohort (2018-2020). Fifteen machine learning models were established by categorical boosting, light gradient boosting machine and random forest. Classifier performances were compared by the sensitivity, F1 score, Matthews correlation coefficient (MCC), area under the receiver operating characteristic (AUROC) curve, and area under the precision-recall curve (AUPRC). SHapley Additive exPlanations plots were drawn to understand feature importance and interactions.

RESULTS

The study included 1392 patients, with 360 (36.4%) and 165 (40.9%) experiencing nephrotoxicity in the derivation and temporal validation cohorts, respectively. The categorical boosting with oversampling achieved the highest performance with a sensitivity of 0.860, an F1 score of 0.740, an MCC of 0.533, an AUROC curve of 0.823, and an AUPRC of 0.737. The feature importance demonstrated that the days of colistin use, cumulative dose, daily dose, latest C-reactive protein, and baseline haemoglobin were the most important risk factors, especially for vulnerable patients. A cutoff colistin dose of 4.0 mg/kg body weight/d was identified for patients at higher risk of nephrotoxicity.

CONCLUSIONS

Machine learning techniques can be an early identification tool to predict colistin-induced nephrotoxicity. The observed interactions suggest a modification in dose adjustment guidelines. Future geographic and prospective validation studies are warranted to strengthen the real-world applicability.

Profile of adverse drug reactions reported via the Continuum+ platform: Results from three-year regional follow-up

In 2017, the Continuum+ platform was launched to provide a monitoring solution to home-based cancer care patients: AKO@dom monitoring. This platform also offers the follow-up of adverse drug reactions (ADRs) via direct notification to regional centers of pharmacovigilance (RCPVs). According to previous studies, the AKO@dom monitoring has successfully maintained treatment at the maximum effective dosage, managing ADRs and patient satisfaction. However, on the pharmacovigilance side, opinions are more divided. Due to the launch of the AKO@dom-PICTO experimentation in December 2021, in which our RCPV takes part, and to provide more data on pharmacovigilance, we decided to conduct a descriptive analysis of cases reported to our RCPV via the Continuum+ platform between 2019 and 2022. During these three years, we analyzed 1070 events, corresponding to 37 patients. Patients were primarily women (74.8%) aged around seventy with breast cancer. The most used drugs were tyrosine kinase inhibitors: palbociclib (29.7%), axitinib (16.2%), and cabozantinib (13.2%). Patients had an average of 8 ADRs, including one serious and/or unexpected ADR. Although the Continuum+ platform makes it possible to considerably limit under-reporting in pharmacovigilance, it has shortcomings. The lack of medical elements and context in notifications is a massive problem for analyzing pharmacovigilance reports. Improved access to the platform's medical information for RCPVs and pharmacovigilance training for healthcare professionals would make Continuum+ a helpful tool in pharmacovigilance.

Association Between First-time Neurologic Events and Metronidazole Treatment: A Case-time Control Study

PURPOSE

Metronidazole, a widely used antimicrobial medication, has been linked to neurologic adverse drug reactions. This study investigates the association between metronidazole use and first-time neurologic events.

METHODS

We conducted a case-time-control study using data from the Danish National Patient Register and the National Prescription Register in years 2013 to 2021. Patients with a first-time diagnosis of encephalopathy, cerebellar dysfunction, or peripheral neuropathy were included. Conditional logistic regression analyses were performed to estimate the risk of neurologic events associated with metronidazole use.

FINDINGS

Out of 476,066 first-time metronidazole prescriptions, the 100-day cumulative incidence of peripheral neuropathy was 0.016%, and 0.002% for cerebellar dysfunction or encephalopathy. In the case-time control study, we identified 17,667 persons with a first-time neurologic event and were included for the analysis. The estimated odds ratio for the combined neurologic events was 0.98 (95% CI, 0.59-1.64, P = 0.95) with no statistically significant association across different subgroups and time windows.

IMPLICATIONS

Our findings suggest that metronidazole-induced neurologic events may be rarer than previously described, and we did not find any consistent or statistically significant association between metronidazole exposure. Nonetheless, clinicians should remain vigilant to potential neurologic risks in patients receiving metronidazole, to ensure its safe and effective use.

The prevalence of hepatic and thyroid toxicity associated with imatinib treatment of chronic myeloid leukaemia: a systematic review

BACKGROUND

Imatinib, a potent inhibitor of targeted protein tyrosine kinases, treats chronic myeloid leukaemia (CML). Data on imatinib-associated changes in hepatic and thyroid functions are limited and conflicting.

AIM

To report the prevalence of hepatic and thyroid toxicity associated with the use of imatinib in CML patients.

METHOD

Articles for the systematic review were selected from electronic databases (PubMed, CINALH, Web of Science). Readily accessible peer-reviewed full articles in English published 1st January 2000 to 18th July 2023 were included. The search terms included combinations of: imatinib, CML, liver toxicity, hepatic toxicity, thyroid toxicity. Screening of titles, abstracts, full text articles was conducted independently by two reviewers. Inclusions and exclusions were recorded following PRISMA guidelines. Detailed reasons for exclusion were recorded. Included articles were critically appraised.

RESULTS

Ten thousand one hundred and twenty-three CML patients were reported in the 82 included studies corresponding to 21 case reports, 2 case series, 39 clinical trials and 20 observational studies were selected. Excluding case studies/reports, 1268 (12.6%; n = 1268/10046) hepatotoxicity adverse events were reported, of which 64.7% were rated as mild grade I & II adverse events, 363 (28.6%) as severe, grade III and IV adverse events; some led to treatment discontinuation, liver transplantation and fatal consequences. Twenty (35.1%) studies reported discontinuation of imatinib treatment due to the severity of hepatic toxicity. Fourteen (8.4%, n = 14/167) thyroid dysfunction adverse events were reported.

CONCLUSION

High frequency of mild and severe hepatotoxicity, associated with imatinib in CML patients, was reported in the published literature. Low numbers of mild and manageable thyroid toxicity events were reported.

Comparison of the incidence of nausea and vomiting between linezolid and vancomycin using claims database: a retrospective cohort study

BACKGROUND

Nausea and vomiting during linezolid therapy have been reported as part of safety analyses in clinical trials. We have previously examined the incidence of vomiting during linezolid therapy (18.1%). A previous study conducted at a single hospital showed low external validity. It is necessary to verify whether these results can be reproduced using generalizable data sources.

AIM

To evaluate the incidence of nausea and vomiting during linezolid therapy compared with vancomycin using a Japanese claims database.

METHOD

Patients administered linezolid or vancomycin were selected from the database between January 2005 and June 2017. The primary endpoint was the comparison of nausea and vomiting between the linezolid and vancomycin groups. We conducted propensity score matching (PSM) to adjust for patient characteristics. To assess risk factors for nausea and vomiting, logistic regression was conducted as the secondary endpoint. We defined nausea and vomiting as the first prescription of antiemetics during linezolid or vancomycin therapy as a surrogate endpoint.

RESULTS

In total, 1215 patients were enrolled. After PSM, the number of patients in the linezolid and vancomycin groups was 241. Nausea and vomiting were observed in 11.2% and 5.0% of patients in the linezolid and vancomycin groups, respectively (p < 0.05). Linezolid administration was extracted as a risk factor for nausea and vomiting (odds ratio, 2.09; 95% confidence interval, 1.02-4.30).

CONCLUSION

This study clarified the relationship between linezolid and nausea and vomiting using a Japanese claims database. Further studies are required to elucidate the unknown mechanisms of linezolid-induced nausea and vomiting.

Analysis of post-market adverse events of istradefylline: a real-world study base on FAERS database

Analyze the adverse event (AE) signals of istradefylline based on the FAERS database. By extracting large-scale data from the FAERS database, this study used various signal quantification techniques such as ROR, PRR, BCPNN, and MGPS to calculate and evaluate the ratio and association between istradefylline and specific AEs. In the FAERS database, this study extracted data from the third quarter of 2019 to the first quarter of 2023, totaling 6,749,750 AE reports. After data cleansing and drug screening, a total of 3633 AE reports related to istradefylline were included for analysis. Based on four calculation methods, this study unearthed 25 System Organ Class (SOC) AE signals and 82 potential preferred terms (PTs) related to istradefylline. The analysis revealed new AEs during istradefylline treatment, including reports of Parkinsonism hyperpyrexia syndrome (n = 3, ROR 178.70, PRR 178.63, IC 1.97, EBGM 165.63), Compulsions (n = 5, ROR 130.12, PRR 130.04, IC 2.53, EBGM 123.02), Deep brain stimulation (n = 10, ROR 114.42, PRR 114.27, IC 3.33, EBGM 108.83), and Freezing phenomenon (n = 60, ROR 97.52, PRR 96.76, IC 5.21, EBGM 92.83). This study provides new risk signals and important insights into the use of istradefylline, but further research and validation are needed, especially for those AE that may occur in actual usage scenarios but are not yet explicitly described in the instructions.