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In Vivo (Athens, Greece) 2023The COVID-19 prophylactic vaccine for the prevention of coronavirus infection was approved in Japan on February 14, 2021. Adverse event reports for the vaccine were...
BACKGROUND/AIM
The COVID-19 prophylactic vaccine for the prevention of coronavirus infection was approved in Japan on February 14, 2021. Adverse event reports for the vaccine were collected from the Japan Adverse Drug Event Relief (JADER) database, similar to those for drugs. Reported odds ratios (RORs) and proportional reporting ratios (PRRs) are commonly used in disproportionality analysis to detect safety signals. Therefore, adverse event reports from the vaccinated population may affect the detection of safety signals for the registered drugs. This study determined the impact of adverse event reports on the detection of safety signals for a COVID-19 prophylactic vaccine by analyzing the JADER database using disproportionality analysis.
PATIENTS AND METHODS
We extracted data from the JADER dataset, in which the COVID-19 vaccine was reported as a suspected drug, and selected the top 10 adverse events in terms of the number of reports. We then extracted the top 30 drugs by the amount of information in the selected 10 adverse events and compared the changes in the number of signal detections with and without the COVID-19 vaccine report data.
RESULTS
The total number of adverse events reported in the JADER database during the study period was 2,002,564. Of the total number of reports, 85,489 (4.3%) reported adverse events related to the COVID-19 vaccine. Of the top 30 drugs reported in the 10 selected adverse events, the ROR and PRR were found to be lower with the inclusion of COVID-19 vaccine data than without. Detection by ROR excluded 23 out of 245 drugs, and detection by PRR excluded 34 out of 204 drugs.
CONCLUSION
The rapid increase in the number of adverse event reports for the COVID-19 vaccine in JADER may affect the detection of safety signals by disproportionality analysis.
Topics: Humans; Adverse Drug Reaction Reporting Systems; COVID-19; COVID-19 Vaccines; Drug-Related Side Effects and Adverse Reactions; Japan
PubMed: 36593055
DOI: 10.21873/invivo.13085 -
Journal of Patient Safety Dec 2013Historically, the gold standard for detecting medical errors has been the voluntary incident reporting system. Voluntary reporting rates significantly underestimate the... (Comparative Study)
Comparative Study
BACKGROUND
Historically, the gold standard for detecting medical errors has been the voluntary incident reporting system. Voluntary reporting rates significantly underestimate the number of actual adverse events in any given organization. The electronic health record (EHR) contains clinical and administrative data that may indicate the occurrence of an adverse event and can be used to detect adverse events that may otherwise remain unrecognized. Automated adverse event detection has been shown to be efficient and cost effective in the hospital setting. The Automated Adverse Event Detection Collaborative (AAEDC) is a group of academic pediatric organizations working to identify optimal electronic methods of adverse event detection. The Collaborative seeks to aggregate and analyze data around adverse events as well as identify and share specific intervention strategies to reduce the rate of such events, ultimately to deliver higher quality and safer care. The objective of this study is to describe the process of automated adverse event detection, report early results from the Collaborative, identify commonalities and notable differences between 2 organizations, and suggest future directions for the Collaborative.
METHODS
In this retrospective observational study, the implementation and use of an automated adverse event detection system was compared between 2 academic children's hospital participants in the AAEDC, Children's National Medical Center, and Cincinnati Children's Hospital Medical Center. Both organizations use the EHR to identify potential adverse events as designated by specific electronic data triggers. After gathering the electronic data, a clinical investigator at each hospital manually examined the patient record to determine whether an adverse event had occurred, whether the event was preventable, and the level of harm involved.
RESULTS
The Automated Adverse Event Detection Collaborative data from the 2 organizations between July 2006 and October 2010 were analyzed. Adverse event triggers associated with opioid and benzodiazepine toxicity and intravenous infiltration had the greatest positive predictive value (range, 47%- 96%). Triggers associated with hypoglycemia, coagulation disturbances, and renal dysfunction also had good positive predictive values (range, 22%-74%). In combination, the 2 organizations detected 3,264 adverse events, and 1,870 (57.3%) of these were preventable. Of these 3,264 events, clinicians submitted only 492 voluntary incident reports (15.1%).
CONCLUSIONS
This work demonstrates the value of EHR-derived data aggregation and analysis in the detection and understanding of adverse events. Comparison and selection of optimal electronic trigger methods and recognition of adverse event trends within and between organizations are beneficial. Automated detection of adverse events likely contributes to the discovery of opportunities, expeditious implementation of process redesign, and quality improvement.
Topics: Automation; Child; District of Columbia; Electronic Health Records; Hospitals, Pediatric; Humans; Interinstitutional Relations; Medical Errors; Ohio; Patient Safety; Retrospective Studies; Risk Management
PubMed: 24257063
DOI: 10.1097/PTS.0000000000000055 -
Journal of Clinical Pharmacy and... Aug 2022As for adverse events (AEs) caused by everolimus, findings from clinical trials and post-marketing surveillance have reported interstitial lung disease, hyperglycaemia,...
WHAT IS KNOWN AND OBJECTIVES
As for adverse events (AEs) caused by everolimus, findings from clinical trials and post-marketing surveillance have reported interstitial lung disease, hyperglycaemia, cardiovascular disease, etc. However, these reports are limited to incidence, and detailed studies on the risk of occurrence, time to onset and post-event clinical outcomes are only related to hyperglycaemia. The purpose of this study was to perform a comprehensive analysis of adverse events during everolimus therapy in patients with renal cell carcinoma (RCC) using the Japanese Adverse Event Report database.
METHODS
Data reported between April 2004 and June 2021 in the Japanese Adverse Drug Event Report database were extracted for use. The reported odds ratio, time to onset and post-event course were analysed for the top 30 adverse events reported.
RESULTS AND DISCUSSION
Among the top 30 adverse events, 23 adverse event signals were detected and classified into seven categories: lung-related AEs, haematological-related AEs, cancer progression, blood glucose-related AEs, hepatic-related AEs, renal-related AEs and others. The lung-related adverse events category was the most common, and the proportion of fatal outcomes after the occurrence of two adverse events related to infectious pneumonia was more than 10%.
WHAT IS NEW AND CONCLUSION
A comprehensive survey of adverse events associated with everolimus administration using the pharmacovigilance database revealed that pulmonary and haematological AEs are frequently reported. The results suggest that attention should be paid to the occurrence of lung disorders because they may lead to fatal outcomes.
Topics: Carcinoma, Renal Cell; Drug-Related Side Effects and Adverse Reactions; Everolimus; Humans; Hyperglycemia; Japan; Kidney Neoplasms; Lung Diseases, Interstitial
PubMed: 35316861
DOI: 10.1111/jcpt.13648 -
AMIA Joint Summits on Translational... 2019Dietary supplement adverse events are potentially severe, yet knowledge regarding the safety of dietary supplements is limited. The CFSAN Adverse Event Reporting System...
Dietary supplement adverse events are potentially severe, yet knowledge regarding the safety of dietary supplements is limited. The CFSAN Adverse Event Reporting System (CAERS) contains records of adverse events attributed to supplements and is potentially useful for dietary supplement pharmacovigilance. This study investigates the feasibility of mining CAERS for dietary supplement adverse events as well as for monitoring the safety of dietary supplement products. Using three online resources, we mapped products in CAERS to their listed ingredients. We then ran four standard signal detection algorithms over the ingredient-adverse event and product-adverse event pairs extracted from CAERS and ranked the detected associations. Comparing 130 signals detected by all four algorithms with a dietary supplement resource, we found evidence for 73 (56%) associations. In addition, some detected product-adverse event signals were consistent with product safety information. We have made a database of the detected adverse events publicly available at https://github.com/zhang-informatics/DDSAE.
PubMed: 31258978
DOI: No ID Found -
Journal For Immunotherapy of Cancer Jul 2021Programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors can cause unique immune-related adverse effects due to non-specific immunological activation....
BACKGROUND
Programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors can cause unique immune-related adverse effects due to non-specific immunological activation. However, less is known about adverse effects of these drugs in the eye.
METHODS
Two adverse event databases were retrospectively reviewed. The two databases consisted of a routine adverse event database and a serious adverse event database of expeditiously submitted reports. Patients with any malignancy who had ocular adverse events while on PD-1/PD-L1 inhibitor treatment were included. Patients received nivolumab, pembrolizumab, atezolizumab or durvalumab alone or in combination with other anticancer agents per each trial's protocol. Databases were queried up to May 19, 2020.
RESULTS
In the routine adverse event database, 272 adverse events from 213 patients were reported and in the serious adverse event reporting database, 59 ocular adverse events from 47 patients were reported. A lower estimate of the prevalance from the routine adverse event database showed 259/7727 patients on study treatment arms reporting ocular adverse events (3.3% prevalence). Excluding trials that do not report lower grade adverse events to the routine adverse event database results in a higher end estimate of 242/3255 patients on study treatment arms reporting ocular adverse events (7.4% prevalence). Ocular events occurred early after drug initiation (routine database: median 6 weeks, IQR 0-16, serious adverse events database: median 11 weeks, IQR 6-21). The median Common Terminology Criteria for Adverse Events grade was grade 1 (mild) (IQR 1-2) and grade 2 (moderate) (IQR 2-3) for the routine database and the serious adverse events database, respectively. In-depth analysis of the serious adverse event reports revealed varying degrees of clinical workup, with 30/47 patients (64%) receiving ophthalmological evaluation and 16/47 (34%) of patients having to delay or discontinue treatment. However, 16/47 (34%) patients experienced resolution and 14/47 (30%) patients experienced at least some improvement.
CONCLUSIONS
This is one of the largest analyses of ocular adverse events in patients treated with PD-1/PD-L1 inhibitors in the USA. We found ocular adverse events are rare complications of PD-1/PD-L1 inhibitor therapy, can be severe enough to cause treatment discontinuation/delay, and may not always be appropriately evaluated by eye specialists. Standardized plans for ophthalmology evaluation and management of ocular toxicities are needed in studies of patients treated with PD-1/PD-L1 inhibitors.
Topics: Adult; Aged; Eye Diseases; Humans; Immune Checkpoint Inhibitors; Middle Aged; Programmed Cell Death 1 Receptor; Retrospective Studies
PubMed: 34226280
DOI: 10.1136/jitc-2020-002119 -
BMC Medical Research Methodology Dec 2018There is a high degree of variability in assessing the preventability of adverse drug events, limiting the ability to compare rates of preventable adverse drug events...
BACKGROUND
There is a high degree of variability in assessing the preventability of adverse drug events, limiting the ability to compare rates of preventable adverse drug events across different studies. We compared three methods for determining preventability of adverse drug events in emergency department patients and explored their strengths and weaknesses.
METHODS
This mixed-methods study enrolled emergency department patients diagnosed with at least one adverse drug event from three prior prospective studies. A clinical pharmacist and physician reviewed the medical and research records of all patients, and independently rated each event's preventability using a "best practice-based" approach, an "error-based" approach, and an "algorithm-based" approach. Raters discussed discordant ratings until reaching consensus. We assessed the inter-rater agreement between clinicians using the same assessment method, and between different assessment methods using Cohen's kappa with 95% confidence intervals (95% CI). Qualitative researchers observed discussions, took field notes, and reviewed free text comments made by clinicians in a "comment" box in the data collection form. We developed a coding structure and iteratively analyzed qualitative data for emerging themes regarding the application of each preventability assessment method using NVivo.
RESULTS
Among 1356 adverse drug events, a best practice-based approach rated 64.1% (95% CI: 61.5-66.6%) of events as preventable, an error-based approach rated 64.3% (95% CI: 61.8-66.9%) of events as preventable, and an algorithm-based approach rated 68.8% (95% CI: 66.1-71.1%) of events as preventable. When applying the same method, the inter-rater agreement between clinicians was 0.53 (95% CI: 0.48-0.59), 0.55 (95%CI: 0.50-0.60) and 0.55 (95% CI: 0.49-0.55) for the best practice-, error-, and algorithm-based approaches, respectively. The inter-rater agreement between different assessment methods using consensus ratings for each ranged between 0.88 (95% CI 0.85-0.91) and 0.99 (95% CI 0.98-1.00). Compared to a best practice-based assessment, clinicians believed the algorithm-based assessment was too rigid. It did not account for the complexities of and variations in clinical practice, and frequently was too definitive when assigning preventability ratings.
CONCLUSION
There was good agreement between all three methods of determining the preventability of adverse drug events. However, clinicians found the algorithmic approach constraining, and preferred a best practice-based assessment method.
Topics: Adverse Drug Reaction Reporting Systems; Algorithms; British Columbia; Data Collection; Drug-Related Side Effects and Adverse Reactions; Emergency Service, Hospital; Humans; Pharmacists; Physicians; Preventive Health Services; Reproducibility of Results; Tertiary Care Centers
PubMed: 30514232
DOI: 10.1186/s12874-018-0617-4 -
Cochlear Implants International Nov 2020Medical device performance and safety databases can be analyzed for patterns and novel opportunities for improving patient safety and/or device design. The objective...
Medical device performance and safety databases can be analyzed for patterns and novel opportunities for improving patient safety and/or device design. The objective of this analysis was to use supervised machine learning to explore patterns in reported adverse events involving cochlear implants. Adverse event reports for the top three CI manufacturers were acquired for the analysis. Four supervised machine learning algorithms were used to predict which adverse event description pattern corresponded with a specific cochlear implant manufacturer and adverse event type. U.S. government public database. Adult and pediatric cochlear patients. Surgical placement of a cochlear implant. Classification prediction accuracy (% correct predictions). Most adverse events involved patient injury ( = 16,736), followed by device malfunction ( = 10,760), and death ( = 16). The random forest, linear SVC, naïve Bayes and logistic algorithms were able to predict the specific CI manufacturer based on the adverse event narrative with an average accuracy of 74.8%, 86.0%, 88.5% and 88.6%, respectively. Using supervised machine learning algorithms, our classification models were able to predict the CI manufacturer and event type with high accuracy based on patterns in adverse event text descriptions.
Topics: Adult; Algorithms; Bayes Theorem; Child; Cochlear Implantation; Cochlear Implants; Databases, Factual; Equipment Failure Analysis; Female; Humans; Logistic Models; Machine Learning; Male; Public Reporting of Healthcare Data; United States; United States Food and Drug Administration
PubMed: 32623971
DOI: 10.1080/14670100.2020.1784569 -
Journal of Patient Safety Sep 2022Involvement in adverse events can negatively impact physician well-being. Because burnout is increasingly recognized as a threat to patient safety, we examined the...
OBJECTIVES
Involvement in adverse events can negatively impact physician well-being. Because burnout is increasingly recognized as a threat to patient safety, we examined the relationship between physician adverse event involvement and burnout as well as facilitators and barriers to support among physicians experiencing burnout.
METHODS
We surveyed physicians in the United States who are members of the networking platform, Doximity. We conducted quantitative and qualitative analyses investigating experiences with adverse events, the impact of adverse events, the type of support the physician sought and received after the event, and burnout.
RESULTS
Across specialties, involvement in an adverse event and burnout was common. Most respondents involved in an adverse event experienced emotional impact, but only a minority received support. Those reporting that the error resulted in emotional impact were more likely to experience burnout (adjusted odds ratio, 1.90; 95% confidence interval, 1.18-3.07); this association was mitigated by the most common form of support sought, peer support (adjusted odds ratio for burnout among those who received peer support versus those who did not, 0.65; 95% confidence interval, 0.52-0.82). Barriers to support after an adverse event include punitive culture and systems factors such as administrative bureaucracy. Facilitators that emerged include peer, professional, and spiritual support, mentorship, helping others, the learning environment, and improved/flexible working hours.
CONCLUSIONS
Physicians who experienced emotional repercussions from adverse events were more likely to report burnout compared with those who did not. Respondents proposed barriers and facilitators to support that have not been widely implemented. Peer support may help mitigate physician burnout related to adverse events.
Topics: Burnout, Professional; Counseling; Humans; Patient Safety; Physicians; Surveys and Questionnaires; United States
PubMed: 35482414
DOI: 10.1097/PTS.0000000000001008 -
Statistics in Medicine Mar 2014Dose-finding designs estimate the dose level of a drug based on observed adverse events. Relatedness of the adverse event to the drug has been generally ignored in all...
Dose-finding designs estimate the dose level of a drug based on observed adverse events. Relatedness of the adverse event to the drug has been generally ignored in all proposed design methodologies. These designs assume that the adverse events observed during a trial are definitely related to the drug, which can lead to flawed dose-level estimation. We incorporate adverse event relatedness into the so-called continual reassessment method. Adverse events that have 'doubtful' or 'possible' relationships to the drug are modelled using a two-parameter logistic model with an additive probability mass. Adverse events 'probably' or 'definitely' related to the drug are modelled using a cumulative logistic model. To search for the maximum tolerated dose, we use the maximum estimated toxicity probability of these two adverse event relatedness categories. We conduct a simulation study that illustrates the characteristics of the design under various scenarios. This article demonstrates that adverse event relatedness is important for improved dose estimation. It opens up further research pathways into continual reassessment design methodologies.
Topics: Arthritis, Rheumatoid; Clinical Trials, Phase I as Topic; Dihydropyridines; Dose-Response Relationship, Drug; Drug-Related Side Effects and Adverse Reactions; Humans; Logistic Models; Maximum Tolerated Dose
PubMed: 24122859
DOI: 10.1002/sim.6011 -
Biological & Pharmaceutical Bulletin 2019Opioid analgesics have greatly contributed to the advancement of pain management. However, although opioids have been appropriately used in Japan, they rarely induce...
Opioid analgesics have greatly contributed to the advancement of pain management. However, although opioids have been appropriately used in Japan, they rarely induce serious adverse events, such as respiratory depression. The present study aimed to investigate the temporal changes in the occurrence of opioid-related adverse events and deaths between 2004 and 2017 in Japan using the Japanese Adverse Drug Event Report (JADER) database. We analyzed the following points using data extracted from JADER website: 1) temporal changes in the number and proportion of opioid-related adverse event reports; 2) temporal changes in the number of morphine-, oxycodone-, and fentanyl-related adverse event reports per annual consumption; and 3) cases in which the reported outcome following opioid-related adverse events was death. Our results showed no dramatic changes in the overall incidence of opioid-related adverse events, despite the temporal changes in the annual consumption and shared component of each opioid during the survey period. However, the number and rate of fentanyl-related adverse events and their outcome "death" increased since 2010, being the highest among all adverse event including those related to morphine and oxycodone. Outcome "death" by fentanyl-related adverse events was caused mainly due to respiratory depression. These findings suggest that, although opioid-related adverse events can be controlled through proper monitoring and management by medical personnel in Japan, extra caution should be continuously paid for the rare but serious fentanyl-induced adverse events.
Topics: Adverse Drug Reaction Reporting Systems; Analgesics, Opioid; Databases, Factual; Fentanyl; Humans; Japan; Methadone; Morphine; Oxycodone; Tapentadol
PubMed: 31061323
DOI: 10.1248/bpb.b18-00997