Spontaneous Reporting System Database Research Articles

Timing Matters: A Machine Learning Method for the Prioritization of Drug-Drug Interactions Through Signal Detection in the FDA Adverse Event Reporting System and Their Relationship with Time of Co-exposure.

Current drug-drug interaction (DDI) detection methods often miss the aspect of temporal plausibility, leading to false-positive disproportionality signals in spontaneous reporting system (SRS) databases. This study aims to develop a method for detecting and prioritizing temporally plausible disproportionality signals of DDIs in SRS databases by incorporating co-exposure time in disproportionality analysis. The method was tested in the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The CRESCENDDI dataset of positive controls served as the primary source of true-positive DDIs. Disproportionality analysis was performed considering the time of co-exposure. Temporal plausibility was assessed using the flex point of cumulative reporting of disproportionality signals. Potential confounders were identified using a machine learning method (i.e. Lasso regression). Disproportionality analysis was conducted on 122 triplets with more than three cases, resulting in the prioritization of 61 disproportionality signals (50.0%) involving 13 adverse events, with 61.5% of these included in the European Medicine Agency's (EMA's) Important Medical Event (IME) list. A total of 27 signals (44.3%) had at least ten cases reporting the triplet of interest, and most of them (n = 19; 70.4%) were temporally plausible. The retrieved confounders were mainly other concomitant drugs. Our method was able to prioritize disproportionality signals with temporal plausibility. This finding suggests a potential for our method in pinpointing signals that are more likely to be furtherly validated.

Multivariate generalized mixed-effects models for screening multiple adverse drug reactions in spontaneous reporting systems.

Introduction: For assessing drug safety using spontaneous reporting system databases, quantitative measurements, such as proportional reporting rate (PRR) and reporting odds ratio (ROR), are widely employed to assess the relationship between a drug and a suspected adverse drug reaction (ADR). The databases contain numerous ADRs, and the quantitative measurements need to be calculated by performing the analysis multiple times for each ADR. We proposed a novel, simple, and easy-to-implement method to estimate the PRR and ROR of multiple ADRs in a single analysis using a generalized mixed-effects model for signal detection. Methods: The proposed method simultaneously analyzed the association between any drug and numerous ADRs, as well as estimated the PRR and ROR for a specific combination of drugs and suspected ADRs. Furthermore, the proposed method was applied to detect drug-drug interactions associated with the concurrent use of two or more drugs. Results and discussion: In our simulation studies, the false-positive rate and sensitivity of the proposed method were similar to those of the traditional PRR and ROR. The proposed method detected known ADRs when applied to the Food and Drug Administration Adverse Event Reporting System database. As an important advantage, the proposed method allowed the simultaneous evaluation of several ADRs using multiple drugs.

Disease-Modifying Therapies (DMTs) in Pregnant and Lactating Women with Multiple Sclerosis: Analysis of Real-World Data from EudraVigilance Database.

(1) Background: The purpose of study was to compare the safety profile of glatiramer with natalizumab, alemtuzumab and ocrelizumab in pregnant and lactating women affected by multiple sclerosis (MS). (2) Methods: Individual case safety reports (ICSRs) were retrieved from the European spontaneous reporting system database (EudraVigilance). The reporting odds ratios (RORs) were computed to compare the reporting probability of events between natalizumab, alemtuzumab and ocrelizumab vs. glatiramer. (3) Results: A total of 1236 ICSRs reporting at least one DMT as a suspected drug were selected. More adverse drug reactions (ADRs) unrelated to pregnancy and breastfeeding (n = 1171; 32.6%) were reported than ADRs specific to pregnancy and breastfeeding (n = 1093; 30.4%). The most frequently reported unrelated ADR was MS relapse. Alemtuzumab and natalizumab seem to have a lower reporting probability of MS relapse compared to glatiramer (ROR 0.17, 95% CI 0.07-0.45 and ROR 0.34, 95% CI 0.20-0.57). Among pregnancy- and breastfeeding-related ADRs, the first most reported event was spontaneous abortion (n = 321; 8.9%). Natalizumab and ocrelizumab were associated with a higher reporting probability of spontaneous abortion compared to glatiramer (ROR 2.22, 95% CI 1.58-3.12; ROR 2.18, 95% CI 1.34-3.54, respectively), while alemtuzumab had a lower reporting frequency (ROR 0.32, 95% CI 0.17-0.60). (4) Conclusions: This study did not suggest any strong or new insights for DMTs in this special subpopulation. However, further studies need to be performed.

A Pharmacovigilance Study of Drug-Induced Glaucoma Utilizing the Japanese Adverse Event Reporting System.

Clinically, glaucoma is a serious problem because it is asymptomatic until a relatively late stage in most cases, which can lead to delays in the diagnosis and treatment of the disease. The purpose of this study was to clarify the rank-order of the association of glaucoma with the causative drugs using a spontaneous reporting system database. Data were extracted from the Japanese Adverse Drug Event Report database of the Pharmaceuticals and Medical Devices Agency (Japan). Based on reports of glaucoma caused by all drugs, we calculated the reporting odds ratio (ROR) and 95% confidence interval (CI) for glaucoma. Among 609 reports of adverse events corresponding to glaucoma (46%, women), the most frequently implicated drug were steroids (prednisolone, betamethasone sodium phosphate, triamcinolone acetonide, and fluorometholone), pregabalin, ranibizumab, crizotinib, tacrolimus hydrate, darbepoetin alfa, and foscarnet sodium hydrate. Among 207 reports involved in angle-closure glaucoma (86%, women), anticholinergic drug and antidepressants ranked high and showed signals. Signals were also detected in bromazepam (ROR, 69.7; 95% CI, 30.9-157.5), oral brotizolam (ROR, 16.6; 95% CI, 6.18-44.8), and oral milnacipran hydrochloride (ROR, 22.8; 95% CI, 8.46-61.4) for angle-closure glaucoma. A national pharmacovigilance database enabled us to identify the drugs that frequently induce glaucoma. The likelihood of the reporting of glaucoma varied among the drugs, which should be used carefully in clinical practice to avoid it.

Evidence-based clinical engineering: Health information technology adverse events identification and classification with natural language processing

The primary goal of this project is to create a framework to extract Real-World Evidence to support Health Technology Assessment, Health Technology Management, Evidence-Based Maintenance, and Post Market Surveillance (as outlined in the EU Medical Device Regulation 2017/745) of medical devices using Natural Language Processing (NLP) and Artificial Intelligence. An initial literature review on Spontaneous Reporting System databases, Health Information Technologies (HIT) fault classification, and Natural Language Processing has been conducted, from which it clearly emerges that adverse events related to HIT are increasing over time. The proposed framework uses NLP techniques and Explainable Artificial Intelligence models to automatically identify HIT-related adverse event reports. The designed model employs a pre-trained version of ClinicalBERT that has been fine-tuned and tested on 3,075 adverse event reports extracted from the FDA MAUDE database and manually labelled by experts.

Risk evaluation of diabetic ketoacidosis associated with antipsychotics among patients with schizophrenia in the Japanese adverse event report database

ObjectiveDiabetic ketoacidosis (DKA) is a serious life-threatening condition and can be associated with antipsychotic medication. Asian patients with diabetes exhibit less insulin resistance than Caucasians; however, all previous studies concerning antipsychotic-related DKA have been conducted in Western populations. We analyzed the rank order of the association of antipsychotic agents for schizophrenia with DKA using the Japanese Adverse Drug Event Report database, a spontaneous reporting system database. MethodsWe performed a retrospective pharmacovigilance disproportionality analysis using adverse event reports submitted to the Pharmaceuticals and Medical Devices Agency between April 2004 and March 2021. The study population comprised 7435 patients with schizophrenia, and the total number of antipsychotic-related DKA reports was 55. ResultsAmong the 55 cases of DKA in patients with schizophrenia, 6% (3/55) patients died after DKA. The signals of DKA were reported after treatment with olanzapine, with a significant adjusted reporting odds ratio (95% CI) of 3.26 (1.87–5.66). In 1399 olanzapine treatment cases, multivariable logistic regression analysis using a forward selection method showed that being male (adjusted RORs 2.72 (1.07–6.90)) was associated with the onset of DKA. ConclusionOur study revealed that treatment with olanzapine was associated with the development of DKA among patients with schizophrenia. The results also clarified that male patients were at higher risk for DKA among patients treated with olanzapine. The application of these data will aid in risk monitoring and management that may reduce the occurrence of antipsychotic-related DKA in treatment for schizophrenia.

[Utilization of Big Data with a Focus on Administrative Claims Database].

With the development of information technology, patient information is stored as electronic data, and huge amounts of such data are collected every day. Such a collection compiled over the course of clinical practice is called real-world data and is expected to be used for evaluating drug efficacy and safety. Real-world data such as health insurance association-based administrative claims databases, pharmacy-based dispensing databases, and spontaneous reporting system databases are mainly used in pharmaceutical research. Among them, claims databases are used for various observational studies such as studies on nationwide prescription trends, pharmacovigilance studies, and studies on rare diseases due to their large sample size. Although the nature of omics data is different from that of real-world data, it has become accessible on cloud platforms and are being used to broaden the scope of research in recent years. In this paper, we introduce a method for generating and further testing hypotheses through integrated analysis of real-world data and omics data, with a focus on administrative claims databases.

Appendicitis Associated With Clozapine: Analyses Based on a Spontaneous Reporting System Database in Japan.

An association between appendicitis and clozapine has recently been reported; however, few studies other than case reports have investigated this association. Therefore, we aimed to investigate the association between appendicitis and clozapine, using a large spontaneous reporting database in Japan. Japanese Adverse Drug Event Report data were used in this study, and patients who had received clozapine or nonclozapine second-generation antipsychotics (NC-SGAs) available in Japan were included. To compare the reporting frequency of appendicitis associated with clozapine and NC-SGAs, we calculated the adjusted reporting odds ratio using logistic regression models, adjusting for age group, sex, and anticholinergic use. We conducted a time-to-event analysis to examine the time to onset of appendicitis associated with clozapine. In total, 8921 patients were included in this study, of whom 85 (1.0%) had appendicitis. Of these, 83 patients had received clozapine. Appendicitis was significantly more frequently reported with clozapine than with NC-SGAs. Time-to-event analysis showed that the risk of developing appendicitis associated with clozapine increased over time. Clozapine was associated with a higher risk of appendicitis than NC-SGAs, which increased with time. These findings suggest that clinicians need to pay greater attention to the risk of developing appendicitis during clozapine treatment.

Safety Monitoring of mRNA COVID-19 Vaccines in Children Aged 5 to 11 Years by Using EudraVigilance Pharmacovigilance Database: The CoVaxChild Study.

Although the safety profiles of mRNA COVID-19 vaccines (mRNA-1273 and BNT162b2) were evaluated in pre-authorization clinical trials, real-world data allow us to better define their benefit/risk ratio in the paediatric population. The current study aimed to evaluate the safety profiles of mRNA COVID-19 vaccines in children by analysing the pharmacovigilance data of the European spontaneous reporting system database EudraVigilance (EV) in the period from 1 January 2021, to 1 October 2022. During our study period, overall 4838 ICSRs related to mRNA COVID-19 vaccines referring to 5-11-year-old subjects were retrieved from EV, of which 96.9% were related to BNT162b2 and 49.3% were related to males. A total of 12,751 Adverse Events Following Immunization (AEFIs) were identified, of which 38.7% were serious. The most frequently reported AEFIs were pyrexia, headache, and vomiting. Only 20 Individual Case Safety Reports (ICSRs) reported Multisystem Inflammatory Syndrome (MIS) as an AEFI, all related to BNT162b2. The majority of MIS cases were females, and six cases were completely resolved at the time of reporting. Our results show a favourable risk-benefit profile for all mRNA COVID-19 vaccines in this paediatric sub-population, supporting their use in children. Considering the peculiarity and fragility of children, continuous safety monitoring of COVID-19 vaccines is required.

Safety profile of tyrosine kinase inhibitors used in non-small-cell lung cancer: An analysis from the Italian pharmacovigilance database.

Non-small cell lung cancer (NSCLC) is often caused by molecular alterations that can be detected by predictive biomarkers including mutations or amplifications of several genes. Several tyrosine kinase inhibitors (TKIs) have been approved in Europe by the European Medicines Agency (EMA) for NSCLC. The aim of this study was to analyze the onset of adverse drug reactions (ADRs) related to TKIs in NSCLC through a spontaneous reporting system (SRS) database. All ADR reports having as suspected drug afatinib (AFT), alectinib (ALEC), brigatinib (BRG), ceritinib (CER), crizotinib (CRIZ), erlotinib (ERL), gefitinib (GEF), lorlatinib (LORL), nintedanib (NTB), and osimertinib (OSI) recorded into the Report Reazioni Avverse dei Medicinali (RAM) system database for national data and into the Italian SRS database for Sicilian data and collected from 2006 to 2021 have been evaluated. A descriptive analysis of basal demographic and drug-related characteristics was performed. A case-by-case methodology was conducted paying particular attention to all serious ADR reports collected in Sicily, focusing on type of seriousness, age, sex, concomitant drugs, and comorbidities. Of the 3,048 Italian reports, most of ADRs were related to ERL (n = 1,448), followed by AFT (n = 435) and GEF (n = 366). ADR reports were slightly more frequent in females (52.2%) and in the age group >65 years (53.0%). A higher number of cases were related to skin disorders (n = 1,766; 57.9%), followed by gastrointestinal disorders (n = 1,024; 33.6%), general disorders and administration site conditions (n = 536; 17.6%), and infections (n = 483; 15.8%). The case-by-case assessment of Sicilian ADRs showed that 33 cases were serious (12.5%) and mainly involved ERL (n = 17; 51.5%), occurring in males with a higher onset of respiratory diseases (30.3%) such as respiratory failure, interstitial lung disease and dyspnea. The analysis of spontaneous ADR reports of TKIs confirmed, in general, well-known risks, which often include skin, gastrointestinal, general, liver, and respiratory diseases as well as infections. However, more attention should be paid to the occurrence of serious life-threatening ADRs including respiratory failure, interstitial lung disease, and cardiogenic shock, especially in young patients.

Real-world Adverse Events Associated with Fluconazole and Itraconazole: Analysis of Nationwide Data Using a Spontaneous Reporting System Database

Real-world Adverse Events Associated with Fluconazole and Itraconazole: Analysis of Nationwide Data Using a Spontaneous Reporting System Database

On the use of the likelihood ratio test methodology in pharmacovigilance.

The safety of medical products due to adverse events (AE) from drugs, therapeutic biologics, and medical devices is a major public health concern worldwide. Likelihood ratio test (LRT) approaches to pharmacovigilance constitute a class of rigorous statistical tools that permit objective identification of AEs of a specific drug and/or a class of drugs cataloged in spontaneous reporting system databases. However, the existing LRT approaches encounter certain theoretical and computational challenges when an underlying Poisson model assumption is violated, including in cases of zero-inflated data. We briefly review existing LRT approaches and propose a novel class of (pseudo-) LRT methods to address these challenges. Our approach uses an alternative parametrization to formulate a unified framework with a common test statistic that can handle both Poisson and zero-inflated Poisson (ZIP) models. The proposed framework is computationally efficient, and it reveals deeper insights into the comparative behaviors of the Poisson and the ZIP models for handling AE data. Our extensive simulation studies document notably superior performances of the proposed methods over existing approaches particularly under zero-inflation, both in terms of statistical (eg, much better control of the nominal level and false discovery rate with substantially enhanced power) and computational ( 100-500-fold gains in average running times) performance metrics. An application of our method on the statin drug class from the FDA FAERS database reveals interesting insights on potential AEs. An R package, pvLRT, implementing our methods has been released in the public domain.

Adverse event profiles of drugs used for treatment of juvenile idiopathic arthritis according to spontaneous reporting system database.

Juvenile idiopathic arthritis (JIA) is a systemic inflammatory disease of childhood onset. The purpose of this study was to clarify the frequency of adverse events caused by drugs used in JIA treatment and characterize their safety profiles using a spontaneous reporting system database. We performed a retrospective pharmacovigilance disproportionality analysis using the Japanese Adverse Drug Event Report (JADER) database. Adverse event reports on drugs used for the treatment of JIA and which were submitted to the Pharmaceuticals and Medical Devices Agency were analyzed, and the reporting odds ratio (ROR) and 95% confidence interval (CI) for reports on each adverse event were calculated. A total of 5,748 reports were identified in the treatment of JIA, in which 35 different drugs were involved. Adverse events by drugs in JIA were frequently reported in females (64.3%) and in those younger than 10 (61.2%). Among the most frequently reported drugs, prednisolone (36.8%) and tocilizumab (36.0%) were predominant. Prednisolone was significantly correlated with hematophagic histiocytosis (ROR, 1.37; 95% CI, 1.18-1.61). Tocilizumab was associated with a high ROR for pneumonia (ROR, 8.61: 95% CI, 5.81-12.7), a decreased neutrophil count (ROR, 6.1; 95% CI, 4.07-9.16), and lymphadenitis (ROR, 8.34; 95% CI, 4.2-16.6). Our results revealed the safety profile of drugs for the treatment of JIA patients. It was suggested that there is a diversity in drugs and their strength of association with adverse events in JIA patients. Our results may provide useful information for the treatment of JIA patients, although further research with more data is needed.

Effect of Dipeptidyl Peptidase-4 Inhibitors vs. Metformin on Major Cardiovascular Events Using Spontaneous Reporting System and Real-World Database Study.

Background: Metformin had been recommended as the first-line treatment for type 2 diabetes since 2006 because of its low cost, high efficacy, and potential to reduce cardiovascular events, and thus death. However, dipeptidyl peptidase-4 (DPP-4) inhibitors are the most commonly prescribed first-line agents for patients with type 2 diabetes in Japan. Therefore, it is necessary to clarify the effect of DPP-4 inhibitors on preventing cardiovascular events, taking into consideration the actual prescription of antidiabetic drugs in Japan. Methods: This study examined the effect of DPP-4 inhibitors on preventing cardiovascular events. The Japanese Adverse Drug Event Report (JADER) database, a spontaneous reporting system in Japan, and the Japanese Medical Data Center (JMDC) Claims Database, a Japanese health insurance claims and medical checkup database, were used for the analysis. Metformin was used as the DPP-4 inhibitor comparator. Major cardiovascular events were set as the primary endpoint. Results: In the analysis using the JADER database, a signal of major cardiovascular events was detected with DPP-4 inhibitors (IC: 0.22, 95% confidence interval: 0.03–0.40) but not with metformin. In the analysis using the JMDC Claims Database, the hazard ratio of major cardiovascular events for DPP-4 inhibitors versus metformin was 1.01 (95% CI: 0.84–1.20). Conclusions: A comprehensive analysis using two different databases in Japan, the JADER and the JMDC Claims Database, showed that DPP-4 inhibitors, which are widely used in Japan, have a non-inferior risk of cardiovascular events compared to metformin, which is used as the first-line drug in the United States and Europe.

Tardive Dyskinesia and Long-Acting Injectable Antipsychotics: Analyses Based on a Spontaneous Reporting System Database in Japan.

Objective: This study compared the reporting frequency of tardive dyskinesia (TD) between long-acting injectable antipsychotics (LAI-APs) and the equivalent oral antipsychotics (O-APs), LAI first-generation antipsychotics (LAI-FGAs) and LAI second-generation antipsychotics (LAI-SGAs), and individual LAI-APs.Methods: The Japanese Adverse Drug Event Report was used in this study, and data were obtained from April 2004 to February 2021. Patients who received LAI-APs available in Japan (LAI haloperidol, LAI fluphenazine, LAI aripiprazole, LAI risperidone, and LAI paliperidone) or the equivalent O-APs were included in this study. We calculated the adjusted reporting odds ratios (aRORs) to compare the reporting frequency of TD.Results: A total of 8,425 patients were included in the study. TD was reported significantly less frequently with LAI paliperidone than with oral paliperidone (aROR [95% confidence interval (CI)] = 0.13 [0.05-0.36]). Other LAI-APs were associated with a numerically lower reporting frequency of TD than the equivalent oral SGAs. The reporting frequency of TD associated with LAI-SGAs was significantly lower than that of LAI-FGAs (aROR [95% CI] = 0.18 [0.08-0.43]). All LAI-SGAs were significantly associated with a lower reporting frequency of TD than that of LAI fluphenazine (aROR [95% CI]: LAI aripiprazole, 0.11 [0.04-0.35]; LAI risperidone, 0.09 [0.03-0.32]; LAI paliperidone, 0.02 [0.005-0.09]). and LAI haloperidol, 8.58 [1.85-39.72]). LAI fluphenazine was significantly associated with a higher reporting frequency of TD than LAI haloperidol (aROR [95% CI] = 8.58 [1.85-39.72]). The reporting frequency of TD associated with LAI paliperidone was significantly lower than that with LAI aripiprazole (aROR [95% CI] = 0.18 [0.05-0.73]).Conclusions: Compared to O-APs, LAI-APs, particularly LAI-SGAs, may be associated with a lower risk of TD.

Drug-induced Neuropsychiatric Adverse Events Using Post-Marketing Surveillance.

Several studies reported that abnormal behavior was noted in pediatric patients receiving several drugs, including neuraminidase inhibitors (NIs). However, the information on drugs associated with abnormal behavior in a real-world setting remains limited. The purpose of this study was to clarify the drugs associated with abnormal behavior using a spontaneous reporting system database. We performed a retrospective pharmacovigilance disproportionality analysis using the Japanese Adverse Drug Event Report database. Adverse event reports submitted to the Pharmaceuticals and Medical Devices Agency were analyzed, and the reporting odds ratio at 95% confidence interval were calculated. A total of 1,144 reports of abnormal behavior were identified. The signals were detected through the association of 4 neuraminidase inhibitors (oseltamivir, zanamivir, laninamivir, and peramivir) with the abnormal behaviour. These signals were stronger for oseltamivir than other neuraminidase inhibitors. The signals were also detected for acetaminophen and montelukast. Our results should be able to raise physicians' awareness of drugs associated with abnormal behavior, but further investigation of these medications is warranted.

Increased acid sphingomyelinase levels in pediatric patients with obesity

The level of secretory acid sphingomyelinase (S-ASM), a key enzyme in the sphingolipid metabolism, is elevated in a variety of human diseases, including in the serum of obese adults. Alterations in S-ASM were also found to induce morphological changes in erythrocytes. Consequently, the inhibition of S-ASM by functional Inhibitors of ASM (FIASMA) may have broad clinical implications. The purpose of this study was to assess S-ASM activity in pediatric patients with obesity and healthy matched controls, as well as to investigate the erythrocyte morphology using transmission electron microscopy. We recruited 46 obese patients (mean age 11 ± 2.9 years) and 44 controls (mean age 10.8 ± 2.9 years). S-ASM activity was significantly higher (Wilcoxon signed-rank test p-value: 0.004) in obese patients (mean 396.4 ± 49.7 pmol/ml/h) than in controls (mean 373.7 ± 23.1 pmol/ml/h). No evidence of morphological differences in erythrocytes was found between the two populations. We then carried out a case–control study based on the spontaneous reporting system database to compare FIASMAs with NON-FIASMAs in terms of weight gain risk. Children who received FIASMA had a significantly lower frequency of weight gain reports than patients who took NON-FIASMA agents (p < 0.001). Our findings suggest there is an intriguing possibility that S-ASM may play a role in pediatric obesity. This pilot study could serve as the basis for future studies in this interesting field of research.

Characteristics of adverse reactions among antipsychotic drugs using the Korean Adverse Event Reporting System database from 2010 to 2019.

Retrospective studies using spontaneous reporting system databases have provided a great understanding of adverse drug reactions (ADRs) in the real world, complementing the data obtained from randomized controlled trials. However, there have been few reports on large-scale epidemiological studies on the adverse effects of antipsychotics in Asia. This study aimed to investigate the characteristics of antipsychotic ADRs using a nationwide pharmacovigilance database. Data were collected from the Korea Adverse Event Reporting System database between 2010 and 2019. The study subjects were selected using the International Classification of Disease codes for diseases related to psychosis and Electronic Data Interchange codes for amisulpride, aripiprazole, clozapine, haloperidol, olanzapine, paliperidone, quetiapine, risperidone, and ziprasidone. The causality assessment of "possible," "probable," or "certain" by the World Health Organization-Uppsala Monitoring Center System causality category was selected. All data were descriptively analyzed. In total, 5067 adverse events associated with antipsychotic drugs were reported. The antipsychotics that commonly resulted in ADRs were quetiapine (47.7%), olanzapine (11.3%), and clozapine (10.7%). Serious ADRs were most commonly observed with clozapine. Gastrointestinal and central nervous system problems occurred within a month when ADRs were classified according to the time of onset. In contrast, metabolic and bone marrow-related symptoms occurred after long-term use. Sedation and nausea were the most common ADRs in children and adolescents, whereas constipation and dizziness were common in adults and the elderly. This study extends our knowledge of antipsychotic ADRs in the Asian population.

A reference set of clinically relevant adverse drug-drug interactions

The accurate and timely detection of adverse drug-drug interactions (DDIs) during the postmarketing phase is an important yet complex task with potentially major clinical implications. The development of data mining methodologies that scan healthcare databases for drug safety signals requires appropriate reference sets for performance evaluation. Methodologies for establishing DDI reference sets are limited in the literature, while there is no publicly available resource simultaneously focusing on clinical relevance of DDIs and individual behaviour of interacting drugs. By automatically extracting and aggregating information from multiple clinical resources, we provide a scalable approach for generating a reference set for DDIs that could support research in postmarketing safety surveillance. CRESCENDDI contains 10,286 positive and 4,544 negative controls, covering 454 drugs and 179 adverse events mapped to RxNorm and MedDRA concepts, respectively. It also includes single drug information for the included drugs (i.e., adverse drug reactions, indications, and negative drug-event associations). We demonstrate usability of the resource by scanning a spontaneous reporting system database for signals of DDIs using traditional signal detection algorithms.

Corrigendum: Suspected Adverse Drug Reactions in Pediatric Cancer Patients in China: An Analysis of Henan Province Spontaneous Reporting System Database

[This corrects the article DOI: 10.3389/fonc.2021.807171.].