Empirical estimation of under-reporting in the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS)

The temporal association between adverse drug reactions and antirheumatic drugs utilisation in Western Australia: a retrospective study from real-world data (1995-2015)

BACKGROUND/OBJECTIVES

Adverse drug reactions (ADRs) can result in morbidity, mortality, and higher healthcare costs. Given the limited information available on ADRs associated with antirheumatic medications, this study aims to analyse and compare ADR reporting for these drugs in the pharmacovigilance datasets of Western Australia (WA) and the United States (US).

METHODS

Therapeutic Goods Administration provided WA pharmacovigilance data of selected antirheumatic drugs to from 1995 to 2015. The proportional reporting ratio (PRR) for WA case reports was compared to corresponding USA pharmacovigilance data by assessing the disproportionality of each ADR. clinically significant or true ADRs were determined using the Evans 2001 criteria (n > 2, chi-square > 4, PRR > 2).

RESULTS

A total of 232 reports were found in WA, mostly on sixty-nine women aged 45 to 69. Methotrexate, leflunomide, azathioprine, sulfasalazine, and infliximab had the highest reported ADRs, related to gastrointestinal disorders. Patients who used biological agents in WA had 2.7 times the likelihood of reporting true ADRs compared to conventional antirheumatic drugs. The ADR rates in the two datasets were comparable over the study period.

CONCLUSIONS

The PRR values of ADRs were consistent between WA and US databases. Methotrexate and infliximab use were commonly associated with ADR reports in WA females, with incidence rates comparable to the US; while patients using biological agents were more likely to report true ADRs than those on conventional antirheumatic drugs in WA.

Mining Real-World Big Data to Characterize Adverse Drug Reaction Quantitatively: Mixed Methods Study

BACKGROUND

Adverse drug reactions (ADRs), which are the phenotypic manifestations of clinical drug toxicity in humans, are a major concern in precision clinical medicine. A comprehensive evaluation of ADRs is helpful for unbiased supervision of marketed drugs and for discovering new drugs with high success rates.

OBJECTIVE

In current practice, drug safety evaluation is often oversimplified to the occurrence or nonoccurrence of ADRs. Given the limitations of current qualitative methods, there is an urgent need for a quantitative evaluation model to improve pharmacovigilance and the accurate assessment of drug safety.

METHODS

In this study, we developed a mathematical model, namely the Adverse Drug Reaction Classification System (ADReCS) severity-grading model, for the quantitative characterization of ADR severity, a crucial feature for evaluating the impact of ADRs on human health. The model was constructed by mining millions of real-world historical adverse drug event reports. A new parameter called Severity_score was introduced to measure the severity of ADRs, and upper and lower score boundaries were determined for 5 severity grades.

RESULTS

The ADReCS severity-grading model exhibited excellent consistency (99.22%) with the expert-grading system, the Common Terminology Criteria for Adverse Events. Hence, we graded the severity of 6277 standard ADRs for 129,407 drug-ADR pairs. Moreover, we calculated the occurrence rates of 6272 distinct ADRs for 127,763 drug-ADR pairs in large patient populations by mining real-world medication prescriptions. With the quantitative features, we demonstrated example applications in systematically elucidating ADR mechanisms and thereby discovered a list of drugs with improper dosages.

CONCLUSIONS

In summary, this study represents the first comprehensive determination of both ADR severity grades and ADR frequencies. This endeavor establishes a strong foundation for future artificial intelligence applications in discovering new drugs with high efficacy and low toxicity. It also heralds a paradigm shift in clinical toxicity research, moving from qualitative description to quantitative evaluation.

Angiotensin Receptor Blocker-Related Sprue-like Enteropathy: Review of Food and Drug Administration Adverse Event Reporting System

BACKGROUND

Sprue-like enteropathy (SE) related to olmesartan use was first reported in 2012. In 2017, the manufacturer of Benicar paid $300 million for 2300 claims for olmesartan-related SE.

OBJECTIVE

A study in 2019 suggested that SE was related to olmesartan and with the possibility of angiotensin receptor blocker (ARB) class effect. To further characterize this condition, our group examined reports of ARB-related SE to Food and Drug Administration Adverse Event Reporting System (FAERS).

METHODS

All reports of ARB-related SE from January 2017 to December 2021 were downloaded from the FAERS database. Gastrointestinal adverse events including SE were reviewed. Reporter categories included physicians, pharmacists, other health care professionals, consumers, and attorneys.

RESULTS

A total of 106 590 reports of ARB-related adverse effects were analyzed. Sprue-like enteropathy was identified in 4337 cases (4.1% of total reports). Of these, 4240 cases (98.0%) of ARB-related SE were reported in patients using products with olmesartan, and 97 cases of SE were reported for all other ARBs (eprosartan, losartan, telmisartan, irbesartan, valsartan, and candesartan). Reports of olmesartan-related SE increased rapidly in 2017, continued at a high rate in 2018 and 2019, and essentially stopped in 2020 and 2021.

CONCLUSIONS AND RELEVANCE

Reports to FAERS for ARB-related SE are mostly related to olmesartan. There was a steep decline in reports of olmesartan-related SE following the lawsuit with potential of lawyer interference. There are reports of SE related to ARBs other than olmesartan, with increased physician awareness and the potential to discover a class effect with future studies.

Novel anti-psoriasis agent-associated cardiotoxicity, analysis of the FDA adverse event reporting system (FAERS)

INTRODUCTION

Psoriasis is a chronic skin condition characterized by hyperproliferation of epidermal keratinocytes, resulting in erythematous and scaling lesions. The US Food and Drug Administration (FDA) has approved nine biologic agents to address the burden of psoriasis, but their cardiovascular risks remain poorly studied.

METHODS

This retrospective pharmacovigilance study utilized the FDA Adverse Event Reporting System (FAERS) database to analyze adverse events associated with newly approved therapeutic agents for psoriasis. We employed disproportionally signal analysis, calculating the reporting odds ratio (ROR) with a 95% confidence interval.

RESULTS

Among the vast FAERS database, which contained >25 million adverse events, a total of 334,399 events were associated with newly approved therapeutic agents for psoriasis. Cardiac adverse events accounted for 3852 cases, including pericarditis, atrial fibrillation, and coronary artery disease. Secukinumab had the highest number of reported adverse events, followed by brodalumab, while tildrakizumab had the lowest. Coronary artery disease was the most reported adverse event (1438 cases), followed by pericarditis (572 cases) and atrial fibrillation (384 cases). Secukinumab had the highest incidence of coronary artery disease, pericarditis, and atrial fibrillation. Risankizumab was significantly associated with an increased risk of coronary artery disease and atrial fibrillation, while tildrakizumab and Ixekizumab were associated with atrial fibrillation. Secukinumab was associated with an elevated risk of pericarditis.

CONCLUSIONS

The study uncovers the cardiovascular adverse effects related to biologic agents used in psoriasis treatment. These findings emphasize the importance of monitoring and evaluating the cardiovascular safety profiles of biological agents used in psoriasis treatment.

Thyroid Hyperplasia and Neoplasm Adverse Events Associated With Glucagon-Like Peptide-1 Receptor Agonists in the Food and Drug Administration Adverse Event Reporting System: Retrospective Analysis

Background

Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are one of the most commonly used drugs for type 2 diabetes mellitus. Clinical guidelines recommend GLP-1 RAs as an adjunct to diabetes therapy in patients with chronic kidney disease, presence or risk of atherosclerotic cardiovascular disease, and obesity. The weight loss observed in clinical trials has been explored further in healthy individuals, putting GLP-1 RAs on track to be the next weight loss treatment.

Objective

Although the adverse event profile is relatively safe, most GLP-1 RAs come with a labeled boxed warning for the risk of thyroid cancers, based on animal models and some postmarketing case reports in humans. Considering the increasing popularity of this drug class and its expansion into a new popular indication, a further review of the most recent postmarketing safety data was warranted to quantify thyroid hyperplasia and neoplasm instances.

Methods

GLP-1 RA patient reports from the US Food and Drug Administration (FDA) Adverse Event Reporting System database were analyzed using reporting odds ratios and 95% CIs.

Results

In this study, we analyzed over 18 million reports from the US FDA Adverse Event Reporting System and provided evidence of significantly increased propensity for thyroid hyperplasias and neoplasms in patients taking GLP-1 RA monotherapy when compared to patients taking sodium-glucose cotransporter-2 (SGLT-2) inhibitor monotherapy.

Conclusions

GLP-1 RAs, regardless of indication, are associated with an over 10-fold increase in thyroid neoplasm and hyperplasia adverse event reporting when compared to SGLT-2 inhibitors.

Medication-overuse headache: A pharmacovigilance study in France

BACKGROUND

Overusing medication for primary headaches or other medical conditions can lead to dependency and medication-overuse headache (MOH) as an adverse drug reaction (ADR).

OBJECTIVES

To analyse reports of ADRs associated with MOH recorded in the French national pharmacovigilance database (FPVD).

METHODS

This retrospective study selected all MOH cases reported in the FPVD from January 2000 to June 2023. A search of the High-Level Group Term "headache" was performed for drugs classified under ATC codes for the musculoskeletal and nervous systems. Specific keywords were searched in report narratives to further reduce their number. Voluntary intoxication reports were excluded. Only MOH cases according to the International Classification of Headache Disorders or with a medical diagnosis of MOH were considered.

RESULTS

Among the 2674 reports associated with the HLGT "headache", for 649 ATC drug codes, only 234 reports correspond to MOH, primarily notified by physicians. The median age was 45 years (IQR: 32-56), with 74.4% females and approximately 61.0% having pre-existing primary headaches. In all, 53.4% of the reports were classified as serious. Among patients, 84.2% had an isolated "headache" as the ADR. One drug was suspected in 47.4% of cases, two drugs in 29.1%, and three or more in 23.5%. In total, 473 suspected drugs, corresponding to 104 active ingredients, were involved, including analgesics (63.0%), in particular, acetaminophen-containing drugs, opioids, triptans and ergots, and non-steroidal anti-inflammatory drugs (12.7%). Antiepileptics and psycholeptics were found in 6.6% and 6.1% of cases, respectively. Drug withdrawal was successful in 84.6% of drug-discontinuation cases. Warnings about MOH are mentioned in the summary of product characteristics (SmPCs) for triptans, ergots, and certain acetaminophen-containing drugs, but not other drug classes.

CONCLUSIONS

Certain drug classes show a high reporting rate of MOH and caution should be exercised when prescribing these drugs. Notably, warnings about MOH must be mentioned in the SmPC of all concerned drug classes.

Adverse drug events associated with linezolid administration: a real-world pharmacovigilance study from 2004 to 2023 using the FAERS database

Introduction: Linezolid is an oxazolidinone antibiotic that is active against drug-resistant Gram-positive bacteria and multidrug-resistant Mycobacterium tuberculosis. Real-world studies on the safety of linezolid in large populations are lacking. This study aimed to determine the adverse events associated with linezolid in real-world settings by analyzing data from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Methods: We retrospectively extracted reports on adverse drug events (ADEs) from the FAERS database from the first quarter of 2004 to that of 2023. By using disproportionality analysis including reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), along with the multi-item gamma Poisson shrinker (MGPS), we evaluated whether there was a significant association between linezolid and ADE. The time to onset of ADE was further analyzed in the general population and within each age, weight, reporting population, and weight subgroups. Results: A total of 11,176 reports of linezolid as the "primary suspected" drug and 263 significant adverse events of linezolid were identified, including some common adverse events such as thrombocytopenia (n = 1,139, ROR 21.98), anaemia (n = 704, ROR 7.39), and unexpected signals that were not listed on the drug label such as rhabdomyolysis (n = 90, ROR 4.33), and electrocardiogram QT prolonged (n = 73, ROR 4.07). Linezolid-induced adverse reactions involved 27 System Organ Class (SOC). Gender differences existed in ADE signals related to linezolid. The median onset time of all ADEs was 6 days, and most ADEs (n = 3,778) occurred within the first month of linezolid use but some may continue to occur even after a year of treatment (n = 46). Conclusion: This study reports the time to onset of adverse effects in detail at the levels of SOC and specific preferred term (PT). The results of our study provide valuable insights for optimizing the use of linezolid and reducing potential side effects, expected to facilitate the safe use of linezolid in clinical settings.

Mining and analysis of adverse event signals of Cariprazine based on the real-world data of FAERS database

OBJECTIVE

This study aims to analyze the adverse events (AEs) of Cariprazine based on the FAERS database, providing evidence for its safety surveillance.

METHODS

For signal quantification of Cariprazine-related AEs, we used disproportionality analysis including the Ratio of Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) algorithms.

RESULTS

We selected Cariprazine-related AE reports from the FAERS database from the fourth quarter of 2015 to the first quarter of 2023, and performed a detailed data analysis. Out of a total of 12,278,580 case reports, 3659 were found to be directly related to Cariprazine. We identified 140 Preferred Terms (PT) to describe these AEs, finding that they involved 27 organ systems. Specifically, AEs related to eye disorders such as Cataract cortical, Cataract nuclear, Accommodation disorder, Lenticular opacities, Oculogyric crisis, Dyschromatopsia were not explicitly mentioned in the drug's leaflet, indicating the presence of new ADR signals.

CONCLUSION

Analysis of the FAERS database identified AEs associated with Cariprazine, notably in eye disorders not previously documented in the drug's official leaflet. These findings emphasize the need for continuous post-market surveillance and awareness among healthcare professionals regarding potential new ADR signals.

Contrastive analysis on the safety of brand and generic nebivolol: a real-world pharmacovigilance study based on the FDA adverse event reporting system

Background: The equivalence of generic drugs to their brand-name counterparts is a controversial issue. Current literature indicates disparities between the generic nebivolol (GN) and the brand nebivolol (BN). Aim: The study is designed to investigate the safety difference between GN and BN and provide reference information for clinical practice. Methods: We reviewed adverse event (AE) reports that recorded nebivolol as the primary suspect drug in the FDA Adverse Event Reporting System (FAERS) database from 2004 to 2022, conducted a disproportional analysis to detect signals for the GN and BN respectively, and compared the AE heterogeneity between them using the Breslow-Day test. Results: A total of 2613 AE reports of nebivolol were recorded in the FAERS database from 2004 to 2022, of which 2,200 were classified as BN, 346 as GN, and 67 unclassifiable AE reports were excluded. The signals of 37 AEs distributed in cardiac, gastrointestinal, psychiatric, and nervous systems were detected in disproportional analysis. 33 out of 37 AEs were positive signals, with 21 not previously listed on the drug label, indicating an unrecognized risk with nebivolol. In the heterogeneity analysis of AE signals between GN and BN, the GN generally showed a higher AE signal value than BN, especially 15 AEs distributed in the cardiac, neurological, and psychiatric systems that showed statistically significantly higher risk by taking GN. Conclusion: Our study shows some previously overlooked adverse effects of nebivolol. It suggests that the risk of GN's adverse effects may be higher than those in BN, which deserves further attention and investigation by healthcare professionals, regulators, and others.

Descriptive analysis on disproportionate medication errors and associated patient characteristics in the Food and Drug Administration's Adverse Event Reporting System

BACKGROUND

Medication errors (MEs) are a major public health concern which can cause harm and financial burden within the healthcare system. Characterizing MEs is crucial to develop strategies to mitigate MEs in the future.

OBJECTIVES

To characterize ME-associated reports, and investigate signals of disproportionate reporting (SDRs) on MEs in the Food and Drug Administration's Adverse Event Reporting System (FAERS).

METHODS

FAERS data from 2004 to 2020 was used. ME reports were identified with the narrow Standardised Medical Dictionary for Regulatory Activities® (MedDRA®) Query (SMQ) for MEs. Drug names were converted to the Anatomical Therapeutic Chemical (ATC) classification. SDRs were investigated using the reporting odds ratio (ROR).

RESULTS

In total 488 470 ME reports were identified, mostly (59%) submitted by consumers and mainly (55%) associated with females. Median age at time of ME was 57 years (interquartile range: 37-70 years). Approximately 1 out of 3 reports stated a serious health outcome. The most prevalent reported drug class was "antineoplastic and immunomodulating agents" (25%). The most common ME type was "incorrect dose administered" (9%). Of the 1659 SDRs obtained, adalimumab was the most common drug associated with MEs, noting a ROR of 1.22 (95% confidence interval: 1.21-1.24).

CONCLUSION

This study offers a first of its kind characterization of MEs as reported to FAERS. Reported MEs are frequent and may be associated with serious health outcomes. This FAERS data provides insights on ME prevention and offers possibilities for additional in-depth analyses.

Evaluation of four machine learning models for signal detection

Background

Logistic regression-based signal detection algorithms have benefits over disproportionality analysis due to their ability to handle potential confounders and masking factors. Feature exploration and developing alternative machine learning algorithms can further strengthen signal detection.

Objectives

Our objective was to compare the signal detection performance of logistic regression, gradient-boosted trees, random forest and support vector machine models utilizing Food and Drug Administration adverse event reporting system data.

Design

Cross-sectional study.

Methods

The quarterly data extract files from 1 October 2017 through 31 December 2020 were downloaded. Due to an imbalanced outcome, two training sets were used: one stratified on the outcome variable and another using Synthetic Minority Oversampling Technique (SMOTE). A crude model and a model with tuned hyperparameters were developed for each algorithm. Model performance was compared against a reference set using accuracy, precision, F1 score, recall, the receiver operating characteristic area under the curve (ROCAUC), and the precision-recall curve area under the curve (PRCAUC).

Results

Models trained on the balanced training set had higher accuracy, F1 score and recall compared to models trained on the SMOTE training set. When using the balanced training set, logistic regression, gradient-boosted trees, random forest and support vector machine models obtained similar performance evaluation metrics. The gradient-boosted trees hyperparameter tuned model had the highest ROCAUC (0.646) and the random forest crude model had the highest PRCAUC (0.839) when using the balanced training set.

Conclusion

All models trained on the balanced training set performed similarly. Logistic regression models had higher accuracy, precision and recall. Logistic regression, random forest and gradient-boosted trees hyperparameter tuned models had a PRCAUC ⩾ 0.8. All models had an ROCAUC ⩾ 0.5. Including both disproportionality analysis results and additional case report information in models resulted in higher performance evaluation metrics than disproportionality analysis alone.

Drug-induced QT prolongation and torsade de pointes: a real-world pharmacovigilance study using the FDA Adverse Event Reporting System database

Introduction: Drug-induced QT prolongation and (or) Torsade de Pointes (TdP) is a well-known serious adverse reaction (ADR) for some drugs, but the widely recognized comprehensive landscape of culprit-drug of QT prolongation and TdP is currently lacking. Aim: To identify the top drugs reported in association with QT prolongation and TdP and provide information for clinical practice. Method: We reviewed the reports related to QT prolongation and TdP in the FDA Adverse Event Reporting System (FAERS) database from January 1, 2004 to December 31, 2022, and summarized a potential causative drug list accordingly. Based on this drug list, the most frequently reported causative drugs and drug classes of QT prolongation and TdP were counted, and the disproportionality analysis for all the drugs was conducted to in detect ADR signal. Furthermore, according to the positive-negative distribution of ADR signal, we integrated the risk characteristic of QT prolongation and TdP in different drugs and drug class. Results: A total of 42,713 reports in FAERS database were considered to be associated with QT prolongation and TdP from 2004 to 2022, in which 1,088 drugs were reported as potential culprit-drugs, and the largest number of drugs belonged to antineoplastics. On the whole, furosemide was the most frequently reported drugs followed by acetylsalicylic acid, quetiapine, citalopram, metoprolol. In terms of drug classes, psycholeptics was the most frequently reported drug classes followed by psychoanaleptics, analgesics, beta blocking agents, drugs for acid related disorders. In disproportionality analysis, 612 drugs showed at least one positive ADR signals, while citalopram, ondansetron, escitalopram, loperamide, and promethazine were the drug with the maximum number of positive ADR signals. However, the positive-negative distribution of ADR signals between different drug classes showed great differences, representing the overall risk difference of different drug classes. Conclusion: Our study provided a real-world overview of QT prolongation and TdP to drugs, and the presentation of the potential culprit-drug list, the proportion of reports, the detection results of ADR signals, and the distribution characteristics of ADR signals may help understand the safety profile of drugs and optimize clinical practice.

Development and application of pharmacological statin-associated muscle symptoms phenotyping algorithms using structured and unstructured electronic health records data

Importance

Statins are widely prescribed cholesterol-lowering medications in the United States, but their clinical benefits can be diminished by statin-associated muscle symptoms (SAMS), leading to discontinuation.

Objectives

In this study, we aimed to develop and validate a pharmacological SAMS clinical phenotyping algorithm using electronic health records (EHRs) data from Minnesota Fairview.

Materials and Methods

We retrieved structured and unstructured EHR data of statin users and manually ascertained a gold standard set of SAMS cases and controls using the published SAMS-Clinical Index tool from clinical notes in 200 patients. We developed machine learning algorithms and rule-based algorithms that incorporated various criteria, including ICD codes, statin allergy, creatine kinase elevation, and keyword mentions in clinical notes. We applied the best-performing algorithm to the statin cohort to identify SAMS.

Results

We identified 16 889 patients who started statins in the Fairview EHR system from 2010 to 2020. The combined rule-based (CRB) algorithm, which utilized both clinical notes and structured data criteria, achieved similar performance compared to machine learning algorithms with a precision of 0.85, recall of 0.71, and F1 score of 0.77 against the gold standard set. Applying the CRB algorithm to the statin cohort, we identified the pharmacological SAMS prevalence to be 1.9% and selective risk factors which included female gender, coronary artery disease, hypothyroidism, and use of immunosuppressants or fibrates.

Discussion and Conclusion

Our study developed and validated a simple pharmacological SAMS phenotyping algorithm that can be used to create SAMS case/control cohort to enable further analysis which can lead to the development of a SAMS risk prediction model.

Thyroid hyperplasia and neoplasm adverse events associated with GLP-1 receptor agonists in FDA Adverse Event Reporting System

Glucagon receptor-like peptide receptor agonists, GLP-1 RAs, are one of the most commonly used drugs for type-2 diabetes mellitus. The clinical guidelines recommend GLP-1 RAs as adjunct to diabetes therapy in patients with chronic kidney disease, presence or risk of atherosclerotic cardiovascular disease, obesity, and other cardiometabolic conditions. The weight loss seen in clinical trials has been explored further in healthy individuals, putting GLP-1 RAs on track to be the next weight loss treatment. Although the adverse event profile is relatively safe, most GLP-1 RAs come with a labeled black boxed warning of the risk of thyroid cancers, based on animal models and some postmarketing case reports in humans. Considering the increasing popularity of this drug class and its expansion into a new popular indication, a further review of most recent postmarketing safety data is warranted to quantify thyroid hyperplasia and neoplasms instances. In this study we analyzed over eighteen million reports from United States Food and Drug Administration Adverse Event Reporting System and identified 17,653 relevant GLP-1 RA monotherapy reports to provide the evidence of significantly increased propensity for thyroid hyperplasias and neoplasms in patients taking GLP-1 RA as monotherapy when compared to patients taking sodium-glucose cotransporter-2 inhibitor monotherapy.

Parasitic infections related to anti-type 2 immunity monoclonal antibodies: a disproportionality analysis in the food and drug administration's adverse event reporting system (FAERS)

Introduction: Monoclonal antibodies (mAbs) targeting immunoglobulin E (IgE) [omalizumab], type 2 (T2) cytokine interleukin (IL) 5 [mepolizumab, reslizumab], IL-4 Receptor (R) α [dupilumab], and IL-5R [benralizumab]), improve quality of life in patients with T2-driven inflammatory diseases. However, there is a concern for an increased risk of helminth infections. The aim was to explore safety signals of parasitic infections for omalizumab, mepolizumab, reslizumab, dupilumab, and benralizumab. Methods: Spontaneous reports were used from the Food and Drug Administration's Adverse Event Reporting System (FAERS) database from 2004 to 2021. Parasitic infections were defined as any type of parasitic infection term obtained from the Standardised Medical Dictionary for Regulatory Activities® (MedDRA®). Safety signal strength was assessed by the Reporting Odds Ratio (ROR). Results: 15,502,908 reports were eligible for analysis. Amongst 175,888 reports for omalizumab, mepolizumab, reslizumab, dupilumab, and benralizumab, there were 79 reports on parasitic infections. Median age was 55 years (interquartile range 24-63 years) and 59.5% were female. Indications were known in 26 (32.9%) reports; 14 (53.8%) biologicals were reportedly prescribed for asthma, 8 (30.7%) for various types of dermatitis, and 2 (7.6%) for urticaria. A safety signal was observed for each biological, except for reslizumab (due to lack of power), with the strongest signal attributed to benralizumab (ROR = 15.7, 95% Confidence Interval: 8.4-29.3). Conclusion: Parasitic infections were disproportionately reported for mAbs targeting IgE, T2 cytokines, or T2 cytokine receptors. While the number of adverse event reports on parasitic infections in the database was relatively low, resulting safety signals were disproportionate and warrant further investigation.

Indication and adverse event profiles of denosumab and zoledronic acid: based on U.S. FDA adverse event reporting system (FAERS)

Objective: To investigate adverse events (AEs) associated with denosumab (Dmab) and zoledronic acid (ZA), compare their association strengths, and explore potential applications to provide clinical reference. Methods: We collected data from FAERS from January 2004 to November 2022 and mined AE signals for Dmab and ZA using ROR values. We compared signal intensity for same AEs and investigated off-label use. We also examined their AEs in adjuvant therapy for breast and prostate cancer. Results: 154,735 reports of primary suspect drugs were analyzed in the FAERS database (Dmab: 117,857; ZA: 36,878). Dmab and ZA had 333 and 1,379 AE signals, with 189 overlaps. The AEs of Dmab included death (ROR:3.478), osteonecrosis of jaw (ROR:53.025), back pain (ROR:2.432), tooth disorder (ROR:16.18), bone pain (ROR:6.523). For ZA, the AEs included osteonecrosis (ROR:104.866), death (ROR: 3.645), pain (ROR:3.963), osteonecrosis of jaw (ROR: 91.744), tooth extraction (ROR: 142.143). Among overlap signals, Dmab showed higher strength in exostosis of the jaw (ROR: 182.66 vs. 5.769), atypical fractures (ROR: 55.589 vs. 9.123), and atypical femur fractures (ROR:49.824 vs. 4.968). And ZA exhibited stronger associations in abscess jaw (ROR: 84.119 vs. 11.12), gingival ulceration (ROR: 74.125 vs. 4.827), increased bone formation (ROR: 69.344 vs. 3.218). Additionally, we identified 528 off-label uses for Dmab and 206 for ZA, with Dmab mainly used in prostate cancer (1.04%), breast cancer (1.03%), and arthritis (0.42%), while ZA in breast cancer (3.21%), prostate cancer (2.48%), and neoplasm malignant (0.52%). For Dmab in breast cancer treatment, AEs included death (11.6%), disease progression (3.3%), and neutropenia (2.7%), while for ZA included death (19.8%), emotional disorder (12.9%), osteomyelitis (11.7%). For prostate cancer treatment, Dmab`s AEs were death (8.9%), prostate cancer metastatic (1.6%), renal impairment (1.7%), while ZA`s included death (34.4%), general physical health deterioration (19.9%), and hemoglobin decreased (18.9%). Conclusion: Our analysis of FAERS database provided postmarketing surveillance data and revealed different strengths of reported AE signals between Dmab and ZA in some of their common AEs. It's also worth noting that both drugs have potential off-label applications, which could introduce new AEs. This highlights the necessity for safety monitoring when using Dmab and ZA off-label.

Development and Application of a Data-Driven Signal Detection Method for Surveillance of Adverse Event Variability Across Manufacturing Lots of Biologics

INTRODUCTION

Postmarketing drug safety surveillance research has focused on the product-patient interaction as the primary source of variability in clinical outcomes. However, the inherent complexity of pharmaceutical manufacturing and distribution, especially of biologic drugs, also underscores the importance of risks related to variability in manufacturing and supply chain conditions that could potentially impact clinical outcomes. We propose a data-driven signal detection method called HMMScan to monitor for manufacturing lot-dependent changes in adverse event (AE) rates, and herein apply it to a biologic drug.

METHODS

The HMMScan method chooses the best-fitting candidate from a family of probabilistic Hidden Markov Models to detect temporal correlations in per lot AE rates that could signal clinically relevant variability in manufacturing and supply chain conditions. Additionally, HMMScan indicates the particular lots most likely to be related to risky states of the manufacturing or supply chain condition. The HMMScan method was validated on extensive simulated data and applied to three actual lot sequences of a major biologic drug by combining lot metadata from the manufacturer with AE reports from the US FDA Adverse Event Reporting System (FAERS).

RESULTS

Extensive method validation on simulated data indicated that HMMScan is able to correctly detect the presence or absence of variable manufacturing and supply chain conditions for contiguous sequences of 100 lots or more when changes in these conditions have a meaningful impact on AE rates. Applying the HMMScan method to FAERS data, two of the three actual lot sequences examined exhibited evidence of potential manufacturing or supply chain-related variability.

CONCLUSIONS

HMMScan could be utilized by both manufacturers and regulators to automate lot variability monitoring and inform targeted root-cause analysis. Broad application of HMMScan would rely on a well-developed data input pipeline. The proposed method is implemented in an open-source GitHub repository.

The INGENIOUS trial: Impact of pharmacogenetic testing on adverse events in a pragmatic clinical trial

Adverse drug events (ADEs) account for a significant mortality, morbidity, and cost burden. Pharmacogenetic testing has the potential to reduce ADEs and inefficacy. The objective of this INGENIOUS trial (NCT02297126) analysis was to determine whether conducting and reporting pharmacogenetic panel testing impacts ADE frequency. The trial was a pragmatic, randomized controlled clinical trial, adapted as a propensity matched analysis in individuals (N = 2612) receiving a new prescription for one or more of 26 pharmacogenetic-actionable drugs across a community safety-net and academic health system. The intervention was a pharmacogenetic testing panel for 26 drugs with dosage and selection recommendations returned to the health record. The primary outcome was occurrence of ADEs within 1 year, according to modified Common Terminology Criteria for Adverse Events (CTCAE). In the propensity-matched analysis, 16.1% of individuals experienced any ADE within 1-year. Serious ADEs (CTCAE level ≥ 3) occurred in 3.2% of individuals. When combining all 26 drugs, no significant difference was observed between the pharmacogenetic testing and control arms for any ADE (Odds ratio 0.96, 95% CI: 0.78-1.18), serious ADEs (OR: 0.91, 95% CI: 0.58-1.40), or mortality (OR: 0.60, 95% CI: 0.28-1.21). However, sub-group analyses revealed a reduction in serious ADEs and death in individuals who underwent pharmacogenotyping for aripiprazole and serotonin or serotonin-norepinephrine reuptake inhibitors (OR 0.34, 95% CI: 0.12-0.85). In conclusion, no change in overall ADEs was observed after pharmacogenetic testing. However, limitations incurred during INGENIOUS likely affected the results. Future studies may consider preemptive, rather than reactive, pharmacogenetic panel testing.

Drugs That Interact With Colchicine Via Inhibition of Cytochrome P450 3A4 and P-Glycoprotein: A Signal Detection Analysis Using a Database of Spontaneously Reported Adverse Events (FAERS)

BACKGROUND

Colchicine has a narrow therapeutic index. Its toxicity can be increased due to concomitant exposure to drugs inhibiting its metabolic pathway; these are cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp).

OBJECTIVE

To examine clinical outcomes associated with colchicine drug interactions using the spontaneous reports of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS).

METHODS

We conducted a disproportionality analysis using FAERS data from January 2004 through June 2020. The reporting odds ratio (ROR) and observed-to-expected ratio (O/E) with shrinkage for adverse events related to colchicine's toxicity (ie, rhabdomyolysis/myopathy, agranulocytosis, hemorrhage, acute renal failure, hepatic failure, arrhythmias, torsade de pointes/QT prolongation, and cardiac failure) were compared between FAERS reports.

RESULTS

A total of 787 reports included the combined mention of colchicine, an inhibitor of both CYP3A4 and P-gp drug, and an adverse event of interest. Among reports that indicated the severity, 61% mentioned hospitalization and 24% death. A total of 37 ROR and 34 O/E safety signals involving colchicine and a CYP3A4/P-gp inhibitor were identified. The strongest ROR signal was for colchicine + atazanavir and rhabdomyolysis/myopathy (ROR = 35.4, 95% CI: 12.8-97.6), and the strongest O/E signal was for colchicine + atazanavir and agranulocytosis (O/E = 3.79, 95% credibility interval: 3.44-4.03).

CONCLUSION AND RELEVANCE

This study identifies numerous safety signals for colchicine and CYP3A4/P-gp inhibitor drugs. Avoiding the interaction or monitoring for toxicity in patients when co-prescribing colchicine and these agents is highly recommended.

A Summary of the Rare Reports of Osteonecrosis of the Jaw Associated With Tumor Necrosis-α Inhibitors in the United States Food and Drug Administration's Adverse Event Reporting System Database

PURPOSE

Recent case reports highlight an association between osteonecrosis of the jaw (ONJ) and antitumor necrosis factor (anti-TNF) medications. Our study reviewed and described reports of anti-TNF associated ONJ reported to the United States of America's Food and Drug Administration Adverse Event Reporting System to explore this potential adverse drug reaction further.

METHODS

Using the Food and Drug Administration Adverse Event Reporting System database, we identified reported cases of ONJ between 2010 and 2021. Cases were included in our study if they reported any prior or concomitant anti-TNF medication use. Additionally, only adults (age 18+) and reports from health-care professionals were included. Cases lacking subject age or gender were excluded. After duplicates were removed, a dataset was created and demographics were described including age, gender, and indication for use. Naranjo scoring was conducted to assess adverse drug reaction probability. Subject demographics were then separately described for cases without reported denosumab or bisphosphonate therapy history and compared to those with reported history or concomitant denosumab or bisphosphonate therapy.

RESULTS

Over twenty thousand cases of ONJ were reported. Forty-four potential cases (0.22%) of anti-TNF medication-associated ONJ were identified and reviewed. Of these, female gender comprised 77.3% (35 cases) and there was an average age of 61.3 years ± 13.7 years. Twenty cases (45.5%) had no prior/concomitant bisphosphonate or denosumab therapy. Of these, 55% (11 cases) were female and the average age was 54.5 ± 17.3 years. Rheumatoid arthritis was the most frequent indication for use (5 cases, 25%) followed by inflammatory bowel disease (IBD) and psoriatic arthritis (4 cases each, 20%) in this cohort.

CONCLUSIONS

Twenty potential cases of anti-TNF-associated ONJ without prior or concomitant medications known to be associated with ONJ were identified and described. Interestingly, male gender was more frequent and subjects were younger in these cases compared to those with prior/concomitant bisphosphonates or denosumab therapy. Naranjo scoring indicated a probable interaction for three cases. Further studies are needed to clarify the association of ONJ and anti-TNF therapy, including investigating potential mechanisms and reporting future cases with sufficient detail to assess possible confounding factors.

The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review

BACKGROUND

Adverse drug events (ADEs) are a considerable public health burden resulting in disability, hospitalization, and death. Even those ADEs deemed nonserious can severely impact a patient's quality of life and adherence to intervention. Monitoring medication safety, however, is challenging. Social media may be a useful adjunct for obtaining real-world data on ADEs. While many studies have been undertaken to detect adverse events on social media, a consensus has not yet been reached as to the value of social media in pharmacovigilance or its role in pharmacovigilance in relation to more traditional data sources.

OBJECTIVE

The aim of the study is to evaluate and characterize the use of social media in ADE detection and pharmacovigilance as compared to other data sources.

METHODS

A scoping review will be undertaken. We will search 11 bibliographical databases as well as Google Scholar, hand-searching, and forward and backward citation searching. Records will be screened in Covidence by 2 independent reviewers at both title and abstract stage as well as full text. Studies will be included if they used any type of social media (such as Twitter or patient forums) to detect any type of adverse event associated with any type of medication and then compared the results from social media to any other data source (such as spontaneous reporting systems or clinical literature). Data will be extracted using a data extraction sheet piloted by the authors. Important data on the types of methods used (such as machine learning), any limitations of the methods used, types of adverse events and drugs searched for and included, availability of data and code, details of the comparison data source, and the results and conclusions will be extracted.

RESULTS

We will present descriptive summary statistics as well as identify any patterns in the types and timing of ADEs detected, including but not limited to the similarities and differences in what is reported, gaps in the evidence, and the methods used to extract ADEs from social media data. We will also summarize how the data from social media compares to conventional data sources. The literature will be organized by the data source for comparison. Where possible, we will analyze the impact of the types of adverse events, the social media platform used, and the methods used.

CONCLUSIONS

This scoping review will provide a valuable summary of a large body of research and important information for pharmacovigilance as well as suggest future directions of further research in this area. Through the comparisons with other data sources, we will be able to conclude the added value of social media in monitoring adverse events of medications, in terms of type of adverse events and timing.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/47068.

The use and safety risk of repurposed drugs for COVID-19 patients: lessons learned utilizing the Food and Drug Administration's Adverse Event Reporting System

Objectives

This study was designed to assess the disproportionality analyses of adverse drug reactions (ADRs) related to hydroxychloroquine and remdesivir and how ADR reporting fluctuated during the COVID-19 pandemic.

Methods

A retrospective observational study was conducted utilizing the Food and Drug Administration's Adverse Event Reporting System (FAERS) data between 2019 and 2021. The study was conducted in two phases. In the first phase, all reports associated with the drugs of interest were evaluated to assess all related adverse drug reactions. In the second phase, specific outcomes of interest (i.e., QT prolongation and renal and hepatic events) were determined to study their association with the drugs of interest. A descriptive analysis was conducted for all adverse reactions related to the drugs being studied. In addition, disproportionality analyses were conducted to compute the reporting odds ratio, the proportional reporting ratio, the information component, and the empirical Bayes geometric mean. All analyses were conducted using RStudio.

Results

A total of 9,443 ADR reports related to hydroxychloroquine; 6,160 (71.49) patients were female, and higher percentage of patients of both sexes were over the age of 65 years. QT prolongation (1.48%), pain (1.38%), and arthralgia (1.25%) were most frequently reported ADRs during the COVID-19 pandemic. The association of QT prolongation with use of hydroxychloroquine was statistically significant (ROR 47.28 [95% CI 35.95-62.18]; PRR 42.41 [95% CI 32.25-55.78]; EBGM 16.08; IC 4.95) compared with fluoroquinolone. The outcome was serious medical events in 48.01% of ADR reports; 27.42% required hospitalization and 8.61% resulted in death. Of 6,673 ADR reports related to remdesivir, 3,928 (61.13%) patients were male. During 2020, the top three ADR reports were elevated liver function tests (17.26%), acute kidney injury (5.95%) and death (2.84%). Additionally, 42.71% of ADR reports indicated serious medical events; 19.69% resulted in death and 11.71% indicated hospitalization. The ROR and PRR of hepatic and renal events associated with remdesivir were statistically significant, (4.81 [95% CI 4.46-5.19] and 2.96 [95% CI 2.66-3.29], respectively.

Conclusion

Our study showed that several serious ADRs were reported with the use of hydroxychloroquine, which resulted in hospitalization and death. Trends with the use of remdesivir were similar, but to a lesser extent. Therefore, this study showed us that off-label use should be based on thorough evidence-based evaluation.

Performance of subgrouped proportional reporting ratios in the US Food and Drug Administration (FDA) adverse event reporting system

BACKGROUND

Many signal detection algorithms give the same weight to information from all products and patients, which may result in signals being masked or false positives being flagged as potential signals. Subgrouped analysis can be used to help correct for this.

RESEARCH DESIGN AND METHODS

The publicly available US Food and Drug Administration Adverse Event Reporting System quarterly data extract files from 1 January 2015 through 30 September 2017 were utilized. A proportional reporting ratio (PRR) analysis subgrouped by either age, sex, ADE report type, seriousness of ADE, or reporter was compared to the crude PRR analysis using sensitivity, specificity, precision, and c-statistic.

RESULTS

Subgrouping by age (n = 78, 34.5% increase), sex (n = 67, 15.5% increase), and reporter (n = 64, 10.3% increase) identified more signals than the crude analysis. Subgrouping by either age or sex increased both the sensitivity and precision. Subgrouping by report type or seriousness resulted in fewer signals (n = 50, -13.8% for both). Subgrouped analyses had higher c-statistic values, with age having the highest (0.468).

CONCLUSIONS

Subgrouping by either age or sex produced more signals with higher sensitivity and precision than the crude PRR analysis. Subgrouping by these variables can unmask potentially important associations.

Anti-TNF-α therapy induced psoriasis in rheumatoid arthritis patients according to FDA postmarketing surveillance data

Rheumatoid arthritis, RA, is a chronic autoimmune disease characterized by joint pain, tenderness, swelling, and stiffness. This disease affects nearly 1% of the world population. RA predominates in females and typically develops between the ages of 30 and 50 years. Common therapeutics for the treatment of RA include immune system suppressants such as tumor necrosis factor, or TNF, inhibitors. There is growing concern related to multiple clinical cases reporting an unexpected onset of psoriasis following the use of TNF inhibitors. This adverse event is counterintuitive since some tumor necrosis factor inhibitors are indicated for the treatment of plaque psoriasis. In this study, we analyzed over 880 thousand postmarketing safety reports from patients being treated for RA with a single therapeutic and provided evidence for a statistically significant association of psoriasis adverse events with TNF inhibitor use as compared to methotrexate. Additionally, we quantified the reported odds ratios and their 95% confidence intervals between four individual TNF inhibitors and found that the degree of association with psoriasis was variable among the drugs studied, with certolizumab pegol exhibiting the highest reported risk.

Real-World Data in Pharmacovigilance Database Provides a New Perspective for Understanding the Risk of Clostridium difficile Infection Associated with Antibacterial Drug Exposure

Antibacterial drug exposure (ADE) is a well-known potential risk factor for Clostridium difficile infection (CDI), but it remains controversial which certain antibacterial drugs are associated with the highest risk of CDI occurrence. To summarize CDI risk associated with ADE, we reviewed the CDI reports related to ADE in the FDA Adverse Event Reporting System database and conducted disproportionality analysis to detect adverse reaction (ADR) signals of CDI for antibacterial drugs. A total of 8063 CDI reports associated with ADE were identified, which involved 73 antibacterial drugs. Metronidazole was the drug with the greatest number of reports, followed by vancomycin, ciprofloxacin, clindamycin and amoxicillin. In disproportionality analysis, metronidazole had the highest positive ADR signal strength, followed by vancomycin, cefpodoxime, ertapenem and clindamycin. Among the 73 antibacterial drugs, 58 showed at least one positive ADR signal, and ceftriaxone was the drug with the highest total number of positive signals. Our study provided a real-world overview of CDI risk for AED from a pharmacovigilance perspective and showed risk characteristics for different antibacterial drugs by integrating its positive-negative signal distribution. Meanwhile, our study showed that the CDI risk of metronidazole and vancomycin may be underestimated, and it deserves further attention and investigation.

Development and Application of Pharmacological Statin-Associated Muscle Symptoms Phenotyping Algorithms Using Structured and Unstructured Electronic Health Records Data

Background

Statins are widely prescribed cholesterol-lowering medications in the US, but their clinical benefits can be diminished by statin-associated muscle symptoms (SAMS), leading to discontinuation. In this study, we aimed to develop and validate a pharmacological SAMS clinical phenotyping algorithm using electronic health records (EHRs) data from Minnesota Fairview.

Methods

We retrieved structured and unstructured EHR data of statin users and manually ascertained a gold standard set of SAMS cases and controls using the SAMS-CI tool from clinical notes in 200 patients. We developed machine learning algorithms and rule-based algorithms that incorporated various criteria, including ICD codes, statin allergy, creatine kinase elevation, and keyword mentions in clinical notes. We applied the best performing algorithm to the statin cohort to identify SAMS.

Results

We identified 16,889 patients who started statins in the Fairview EHR system from 2010-2020. The combined rule-based (CRB) algorithm, which utilized both clinical notes and structured data criteria, achieved similar performance compared to machine learning algorithms with a precision of 0.85, recall of 0.71, and F1 score of 0.77 against the gold standard set. Applying the CRB algorithm to the statin cohort, we identified the pharmacological SAMS prevalence to be 1.9% and selective risk factors which included female gender, coronary artery disease, hypothyroidism, use of immunosuppressants or fibrates.

Conclusion

Our study developed and validated a simple pharmacological SAMS phenotyping algorithm that can be used to create SAMS case/control cohort for further analysis such as developing SAMS risk prediction model.

A New Drug Safety Signal Detection and Triage System Integrating Sequence Symmetry Analysis and Tree-Based Scan Statistics with Longitudinal Data

Purpose

Development and evaluation of a drug-safety signal detection system integrating data-mining tools in longitudinal data is essential. This study aimed to construct a new triage system using longitudinal data for drug-safety signal detection, integrating data-mining tools, and evaluate adaptability of such system.

Patients and Methods

Based on relevant guidelines and structural frameworks in Taiwan's pharmacovigilance system, we constructed a triage system integrating sequence symmetry analysis (SSA) and tree-based scan statistics (TreeScan) as data-mining tools for detecting safety signals. We conducted an exploratory analysis utilizing Taiwan's National Health Insurance Database and selecting two drug classes (sodium-glucose co-transporter-2 inhibitors (SGLT2i) and non-fluorinated quinolones (NFQ)) as chronic and episodic treatment respectively, as examples to test feasibility of the system.

Results

Under the proposed system, either cohort-based or self-controlled mining with SSA and TreeScan was selected, based on whether the screened drug had an appropriate comparator. All detected alerts were further classified as known adverse drug reactions (ADRs), events related to other causes or potential signals from the triage algorithm, building on existing drug labels and clinical judgement. Exploratory analysis revealed greater numbers of signals for NFQ with a relatively low proportion of known ADRs; most were related to indication, patient characteristics or bias. No safety signals were found. By contrast, most SGLT2i signals were known ADRs or events related to patient characteristics. Four were potential signals warranting further investigation.

Conclusion

The proposed system facilitated active and systematic screening to detect and classify potential safety signals. Countries with real-world longitudinal data could adopt it to streamline drug-safety surveillance.

Evaluating the Impact of Black Box Warning Updates on the Reporting of Drug-Related Adverse Events: a Cross Sectional Study of the FAERS Database

BACKGROUND

The Food and Drug Administration (FDA)'s Adverse Event Reporting System (FAERS) is a post-marketing surveillance system which relies on spontaneous reports of adverse drug reactions (ADRs). Our objective was to evaluate how black box warning (BBW) updates impact ADR reporting rates.

RESEARCH DESIGN AND METHODS

We searched MEDWATCH for all BBW updates issued between January 2014 and December 2016 and categorized them as new, major, and minor. Rates of relevant ADR reports from the FAERS database in the 4 years preceding and following a BBW update were assessed among the different BBW categories.

RESULTS

Forty BBW updates were included (16 major, 3 new, and 21 minor). A meaningful increase in the proportion of relevant ADRs of all ADRs reported following BBW updates was documented for 53% of new or major updates and 24% of minor updates (p = 0.06). The median percentage of reported relevant ADRs increased by 5% following new and major BBW updates and decreased by 30% following minor BBW updates (p = 0.3).

CONCLUSIONS

Reporting of adverse events to the FAERS database is affected by the severity and timing of related BBW updates, highlighting the drawbacks of spontaneous reporting systems. Regulators should promote proactive pharmacovigilance strategies to cope with these limitations.

Immune checkpoint inhibitor-induced pure red cell aplasia: Case series and large-scale pharmacovigilance analysis

INTRODUCTION

Impressive advances in immunotherapy, especially immune checkpoint inhibitors (ICIs), have made great progress in treating multiple cancers. However, ICIs can also cause serious, even incurable, immune-related adverse events (irAEs), most often in patients with colitis, dermatitis, hepatitis, and thyroiditis. Rare autoimmune hematologic toxicities have been reported in the literature but are poorly described. Pure red cell aplasia (PRCA) induced by ICIs is a life-threatening autoimmune disease; however, only a few cases have been reported in the literature.

OBJECTIVE

To characterize and evaluate PRCA associated with different ICI regimens in a public database and to review the relevant literature.

METHODS

We described a case series of patients experiencing PRCA while on ICIs. We also mined the Food and Drug Administration's Adverse Event Reporting System (FAERS) and used reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms to analyze the data of the suspected adverse events of PRCA induced by ICIs between January 2011 and June 2022.

RESULTS

Fifteen patients with PRCA events while on ICIs were included in our case series. In FAERS, a total of 41 individual case safety reports (ICSRs) with different ICI regimens were retrieved, among which 28 (68.3%) were related to monotherapy and three (7.3%) involved a fatal outcome. Signals of PRCA for all four ICI monotherapies (nivolumab, pembrolizumab, durvalumab, and atezolizumab) and ICI combination therapy (ipilimumab/nivolumab) were detected. Ipilimumab/nivolumab presented a higher reporting signal than nivolumab.

CONCLUSIONS

There is a significant reporting signal of PRCA with several ICI agents. Clinicians should be aware of and monitor this potentially fatal adverse event.

Vitamin D supplementation is effective for olanzapine-induced dyslipidemia

Olanzapine is an atypical antipsychotic drug that is clinically applied in patients with schizophrenia. It increases the risk of dyslipidemia, a disturbance of lipid metabolic homeostasis, usually characterized by increased low-density lipoprotein (LDL) cholesterol and triglycerides, and accompanied by decreased high-density lipoprotein (HDL) in the serum. In this study, analyzing the FDA Adverse Event Reporting System, JMDC insurance claims, and electronic medical records from Nihon University School of Medicine revealed that a co-treated drug, vitamin D, can reduce the incidence of olanzapine-induced dyslipidemia. In the following experimental validations of this hypothesis, short-term oral olanzapine administration in mice caused a simultaneous increase and decrease in the levels of LDL and HDL cholesterol, respectively, while the triglyceride level remained unaffected. Cholecalciferol supplementation attenuated these deteriorations in blood lipid profiles. RNA-seq analysis was conducted on three cell types that are closely related to maintaining cholesterol metabolic balance (hepatocytes, adipocytes, and C2C12) to verify the direct effects of olanzapine and the functional metabolites of cholecalciferol (calcifediol and calcitriol). Consequently, the expression of cholesterol-biosynthesis-related genes was reduced in calcifediol- and calcitriol-treated C2C12 cells, which was likely to be mediated by activating the vitamin D receptor that subsequently inhibited the cholesterol biosynthesis process via insulin-induced gene 2 regulation. This clinical big-data-based drug repurposing approach is effective in finding a novel treatment with high clinical predictability and a well-defined molecular mechanism.

Artificial Intelligence-Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study

Background

The use of patient health and treatment information captured in structured and unstructured formats in computerized electronic health record (EHR) repositories could potentially augment the detection of safety signals for drug products regulated by the US Food and Drug Administration (FDA). Natural language processing and other artificial intelligence (AI) techniques provide novel methodologies that could be leveraged to extract clinically useful information from EHR resources.

Objective

Our aim is to develop a novel AI-enabled software prototype to identify adverse drug event (ADE) safety signals from free-text discharge summaries in EHRs to enhance opioid drug safety and research activities at the FDA.

Methods

We developed a prototype for web-based software that leverages keyword and trigger-phrase searching with rule-based algorithms and deep learning to extract candidate ADEs for specific opioid drugs from discharge summaries in the Medical Information Mart for Intensive Care III (MIMIC III) database. The prototype uses MedSpacy components to identify relevant sections of discharge summaries and a pretrained natural language processing (NLP) model, Spark NLP for Healthcare, for named entity recognition. Fifteen FDA staff members provided feedback on the prototype's features and functionalities.

Results

Using the prototype, we were able to identify known, labeled, opioid-related adverse drug reactions from text in EHRs. The AI-enabled model achieved accuracy, recall, precision, and F1-scores of 0.66, 0.69, 0.64, and 0.67, respectively. FDA participants assessed the prototype as highly desirable in user satisfaction, visualizations, and in the potential to support drug safety signal detection for opioid drugs from EHR data while saving time and manual effort. Actionable design recommendations included (1) enlarging the tabs and visualizations; (2) enabling more flexibility and customizations to fit end users' individual needs; (3) providing additional instructional resources; (4) adding multiple graph export functionality; and (5) adding project summaries.

Conclusions

The novel prototype uses innovative AI-based techniques to automate searching for, extracting, and analyzing clinically useful information captured in unstructured text in EHRs. It increases efficiency in harnessing real-world data for opioid drug safety and increases the usability of the data to support regulatory review while decreasing the manual research burden.

Landscape of DILI-related adverse drug reaction in China Mainland

Drug-induced liver injury (DILI) is a type of bizarre adverse drug reaction (ADR) damaging liver (L-ADR) which may lead to substantial hospitalizations and mortality. Due to the general low incidence, detection of L-ADR remains an unsolved public health challenge. Therefore, we used the data of 6.673 million of ADR reports from January 1st, 2012 to December 31st, 2016 in China National ADR Monitoring System to establish a new database of L-ADR reports for future investigation. Results showed that totally 114,357 ADR reports were retrieved by keywords searching of liver-related injuries from the original heterogeneous system. By cleaning and standardizing the data fields by the dictionary of synonyms and English translation, we resulted 94,593 ADR records reported to liver injury and then created a new database ready for computer mining. The reporting status of L-ADR showed a persistent 1.62-fold change over the past five years. The national population-adjusted reporting numbers of L-ADR manifested an upward trend with age increasing and more evident in men. The annual reporting rate of L-ADR in age group over 80 years old strikingly exceeded the annual DILI incidence rate in general population, despite known underreporting situation in spontaneous ADR reporting system. The percentage of herbal and traditional medicines (H/TM) L-ADR reports in the whole number was 4.5%, while 80.60% of the H/TM reports were new findings. There was great geographical disparity of reported agents, i.e. more cardiovascular and antineoplastic agents were reported in higher socio-demographic index (SDI) regions and more antimicrobials, especially antitubercular agents, were reported in lower SDI regions. In conclusion, this study presented a large-scale, unbiased, unified, and computer-minable L-ADR database for further investigation. Age-, sex- and SDI-related risks of L-ADR incidence warrant to emphasize the precise pharmacovigilance policies within China or other regions in the world.

Characterization and corroboration of safety signals identified from the US Food and Drug Administration Adverse Event Reporting System, 2008-19: cross sectional study

OBJECTIVE

To characterize potential drug safety signals identified from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS), from 2008 to 2019, to determine how often these signals resulted in regulatory action by the FDA and whether these actions were corroborated by published research findings or public assessments by the Sentinel Initiative.

DESIGN

Cross sectional study.

SETTING

USA.

POPULATION

Safety signals identified from the FAERS and publicly reported by the FDA between 2008 and 2019; and review of the relevant literature published before and after safety signals were reported in 2014-15. Literature searches were performed in November 2019, Sentinel Initiative assessments were searched in December 2021, and data analysis was finalized in December 2021.

MAIN OUTCOME MEASURES

Safety signals and resulting regulatory actions; number and characteristics of published studies, including corroboration of regulatory action as evidenced by significant associations (or no associations) between the drug related to the signal and the adverse event.

RESULTS

From 2008 to 2019, 603 potential safety signals identified from the FAERS were reported by the FDA (median 48 annually, interquartile range 41-61), of which 413 (68.5%) were resolved as of December 2021 (372 of 399 (93.2%) signals ≥3 years old were resolved). Among the resolved safety signals, 91 (22.0%) led to no regulatory action and 322 (78.0%) resulted in regulatory action, including 319 (77.2%) changes to drug labeling and 59 (14.3%) drug safety communications or other public communications from the FDA. For a subset of 82 potential safety signals reported in 2014-15, a literature search identified 1712 relevant publications; 1201 (70.2%) were case reports or case series. Among these 82 safety signals, 76 (92.7%) were resolved, of which relevant published research was identified for 57 (75.0%) signals and relevant Sentinel Initiative assessments for four (5.3%) signals. Regulatory actions by the FDA were corroborated by at least one relevant published research study for 17 of the 57 (29.8%) resolved safety signals; none of the relevant Sentinel Initiative assessments corroborated FDA regulatory action.

CONCLUSIONS

Most potential safety signals identified from the FAERS led to regulatory action by the FDA. Only a third of regulatory actions were corroborated by published research, however, and none by public assessments from the Sentinel Initiative. These findings suggest that either the FDA is taking regulatory actions based on evidence not made publicly available or more comprehensive safety evaluations might be needed when potential safety signals are identified.

Mechanism of bisphosphonate-related osteonecrosis of the jaw (BRONJ) revealed by targeted removal of legacy bisphosphonate from jawbone using competing inert hydroxymethylene diphosphonate

Bisphosphonate-related osteonecrosis of the jaw (BRONJ) presents as a morbid jawbone lesion in patients exposed to a nitrogen-containing bisphosphonate (N-BP). Although it is rare, BRONJ has caused apprehension among patients and healthcare providers and decreased acceptance of this antiresorptive drug class to treat osteoporosis and metastatic osteolysis. We report here a novel method to elucidate the pathological mechanism of BRONJ by the selective removal of legacy N-BP from the jawbone using an intra-oral application of hydroxymethylene diphosphonate (HMDP) formulated in liposome-based deformable nanoscale vesicles (DNV). After maxillary tooth extraction, zoledronate-treated mice developed delayed gingival wound closure, delayed tooth extraction socket healing and increased jawbone osteonecrosis consistent with human BRONJ lesions. Single cell RNA sequencing of mouse gingival cells revealed oral barrier immune dysregulation and unresolved proinflammatory reaction. HMDP-DNV topical applications to nascent mouse BRONJ lesions resulted in accelerated gingival wound closure and bone socket healing as well as attenuation of osteonecrosis development. The gingival single cell RNA sequencing demonstrated resolution of chronic inflammation by increased anti-inflammatory signature gene expression of lymphocytes and myeloid-derived suppressor cells. This study suggests that BRONJ pathology is related to N-BP levels in jawbones and demonstrates the potential of HMDP-DNV as an effective BRONJ therapy.

An optimized microplate-based method to evaluate complement-dependent hemolysis mediated by intravenous immunoglobulins (IVIG)

Hemolytic reactions can cause serious complications after administration of Intravenous Immunoglobulin (IVIG), due to passive transfer of anti-A and anti-B IgG antibodies (isoagglutinins). A maximum allowable amount of isoagglutinins is established in the US and EU for licensed IVIG, as measured by a specified direct hemagglutination test (DHAT). Despite this limit, reports of hemolysis have increased over time, raising the question of how well the DHAT predicts clinically significant hemolysis. This study was undertaken to develop a microplate-based complement-dependent hemolysis assay (CDHA) that reproducibly measures functional hemolytic activity of IVIG, for assessment of IVIG products. An IVIG working reference reagent (NIBSC 14/160) was qualified as an assay control and for quantitation purposes. Hemolytic activities of 36 IVIG product lots encompassing seven brands and including 6 clinically hemolytic lots were measured. Hemolytic activity varied among IVIG product brands, and to a lesser extent, from lot-to-lot for individual brands. Correlation between the CDHA and DHAT was not robust which may reflect imprecision of the DHAT method or additional variables that influence complement-dependent hemolysis after opsonization. In conclusion, the CDHA provides a simple, specific, and sensitive tool for IVIG product characterization and investigation of hemolytic events by manufacturers, researchers, and regulatory authorities.

A data-driven pipeline to extract potential adverse drug reactions through prescription, procedures and medical diagnoses analysis: application to a cohort study of 2,010 patients taking hydroxychloroquine with an 11-year follow-up

Context

Real-life data consist of exhaustive data which are not subject to selection bias. These data enable to study drug-safety profiles but are underused because of their temporality, necessitating complex models (i.e., safety depends on the dose, timing, and duration of treatment). We aimed to create a data-driven pipeline strategy that manages the complex temporality of real-life data to highlight the safety profile of a given drug.

Methods

We proposed to apply the weighted cumulative exposure (WCE) statistical model to all health events occurring after a drug introduction (in this paper HCQ) and performed bootstrap to select relevant diagnoses, drugs and interventions which could reflect an adverse drug reactions (ADRs). We applied this data-driven pipeline on a French national medico-administrative database to extract the safety profile of hydroxychloroquine (HCQ) from a cohort of 2,010 patients.

Results

The proposed method selected eight drugs (metopimazine, anethole trithione, tropicamide, alendronic acid & colecalciferol, hydrocortisone, chlormadinone, valsartan and tixocortol), twelve procedures (six ophthalmic procedures, two dental procedures, two skin lesions procedures and osteodensitometry procedure) and two medical diagnoses (systemic lupus erythematous, unspecified and discoid lupus erythematous) to be significantly associated with HCQ exposure.

Conclusion

We provide a method extracting the broad spectrum of diagnoses, drugs and interventions associated to any given drug, potentially highlighting ADRs. Applied to hydroxychloroquine, this method extracted among others already known ADRs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01628-3.

• The challenge of drug-safety signal detection methods is to handle four types of difficulties:

○ The data source, the study of long-term adverse drug reactions or effects not suspected by healthcare professionals, requires the use of a real-life data source.

○ The consideration of a broad spectrum of potential adverse drug reactions (ADRs), and not only candidate ADRs.

○ The temporal impact (meaning that safety depends on the dose, date and duration of treatment).

○ The difference between true ADRs and disease natural course.

• We aimed to create a data-driven pipeline strategy, without any assumption of any ADRs, which take into account the complex temporality of real-life data to provide the safety profile of a given drug.

• Our pipeline used three sources of real-life data to establish a safety profile of a given drug: drug prescriptions, procedures and medical diagnoses.

• We successfully applied our data-driven pipeline strategy to hydroxychloroquine (HCQ). Our pipeline enabled us to find diagnoses, drugs and interventions related to HCQ and which could reflect an ADR due to HCQ or the disease itself.

• This data-driven pipeline strategy may be of interest to other experts involved in the pharmacovigilance discipline.

Intracranial Hemorrhage Following Anticoagulant Treatment in Denmark: Spontaneous Adverse Drug Reaction Reports Versus Real-World Data

INTRODUCTION

In Denmark, physicians are legally obliged to report serious adverse drug reactions (ADRs), such as intracranial hemorrhage (ICH) following anticoagulant (AC) treatment, to the Danish Medicines Agency. We were therefore puzzled to discover a high number of reports concerning ICHs following treatment with the direct oral anticoagulants (DOACs) dabigatran, rivaroxaban, and apixaban compared with warfarin. This was surprising, as all DOACs have been found to be associated with a lower risk of ICH compared with warfarin in phase III randomized controlled trials.

OBJECTIVES

The primary aim of the study was to estimate the level of underreporting of ICH as an ADR following treatment with warfarin, dabigatran, rivaroxaban, and apixaban.

METHODS

This observational study covered a 5-year period (2014-2018). Using nationwide registries held by the Danish Health Data Authority, the number of users, exposure time in person-years, and related ICH events for each of the study drugs were estimated. Data on ADR-ICH reports were extracted from the interactive ADR overviews held by the Danish Medicines Agency.

RESULTS

From 2014 to 2018, 97.0% of the identified warfarin-related ICH events were not reported as ADRs. For the DOACs, the level of underreporting ranged from 88.8 to 90.8%.

CONCLUSION

We found a heavy and differentiated level of underreporting of ICH as an ADR following treatment with the four study drugs.

Current Situation of Medication Errors in Saudi Arabia: A Nationwide Observational Study

OBJECTIVES

Medication errors are common and highly preventable events that significantly affect patients' health. This nationwide study primarily aims to quantify the rate and level of harm from the reported medication errors and to determine the medication process stages in which the reported errors occurred.

METHODS

This retrospective observational study concerns medication errors reported to the General Department of Pharmaceutical Care database from March 2018 to June 2019. The database stores all aspects of medication error information, including patient, medication, and error information, along with the job position of the staff involved and contributing factors. The medication use process was categorized into these stages: ordering/prescribing, transcribing, dispensing, administering, and monitoring. We recorded each medication error based on categories from the U.S. National Coordinating Council for Medication Error Reporting and Prevention.

RESULTS

A total of 71,332 medication error events were reported to the database. Physicians made 63,120 (88.5%) reported errors, and pharmacists most frequently detected the errors (75.9%). The majority of reported errors appeared at the prescribing phase (84.8%), followed by the transcribing (5.8%) and dispensing (5.7%) phases. A total of 4182 (5.8%) errors reached the patient. Health care professionals' work overload and lack of experience were associated with 31.6% and 22.7% of the reported errors, respectively.

CONCLUSIONS

Our study highlights the concern regarding medication errors and their low reporting by indicating that pharmacists reported and detected the majority of errors. Promoting a no-blame culture and education for health professionals is vital for improving the error-reporting rate.

Implementation of virtual clinical pharmacy services by incorporating medical professionals and pharmacy students: A novel patient-oriented system to advance healthcare in India

The healthcare sector is continuously evolving in pace to meet the medical needs of the society. Even though therapeutic reforms are happening, medication discrepancies are the prime cause of hospitalization. This has generated an invincible demand for clinical pharmacy services. Accordingly, a program that collaborates the clinical preceptor and students of department of pharmacy practice with the hospital's medical team, has been established. Any individual who has doubts on medicines can inquire through Dr MED, a virtual clinical pharmacy platform. The operating procedure of the program is presented in the article, where the program's coordinator and the pharmacy students play a significant role in sorting out the queries and finding out the evidences. On the other hand, the medical team composed of physicians and clinical pharmacists acts as a supporting component. Finally, the decision on how and what to respond to the inquirer is upon the opinions put forward by the medical team. Moreover, the system also addresses all the clinical concerns confined to medicines that ultimately enhances the patient's treatment outcome.

Postmarketing safety surveillance data reveals protective effects of botulinum toxin injections against incident anxiety

Randomized controlled trials (RCTs) have shown an antidepressant effect of glabellar botulinum toxin (BoNT) injections. In the FDA Adverse Event Reporting System (FAERS) database, BoNT injection is associated with reduced incidence rates of depression across various non-psychiatric indications, which confirms the previous findings independently of specific expectations to an antidepressant effect of BoNT. The rationale of using BoNT to treat depression is to interrupt proprioceptive body feedback that may reinforce negative emotions. Negative emotions also occur in other mental disorders, suggesting a transdiagnostic therapeutic potential of BoNT in psychiatry. Here we report an analysis of the FAERS database, in which we found that, compared to alternative treatments, BoNT injections were associated with lower incidence of anxiety symptoms and related disorders. Among seven indications/injection sites, we found this protective effect of BoNT in cosmetic use/facial muscles, migraine/facial and head muscles, spasms and spasticity/upper and lower limbs, torticollis and neck pain/neck muscles, and sialorrhea/parotid and submandibular glands (reporting odds ratios 0.79-0.27). These findings are encouraging for possible future RCTs on the use of BoNT as a treatment for anxiety and related disorders.

Cardiotoxicity in cancer immune-checkpoint therapy: Mechanisms, clinical evidence, and management strategies

Immune-checkpoint inhibitors (ICIs), a unique antibody-based therapeutic strategy, have revolutionized the treatment landscape of solid and hematological cancers. Despite the proven benefits of ICIs, the cardiotoxicity from unspecific immune activation (uncommon but potentially fatal) is a continuing concern. Accumulating preclinical research has demonstrated that ICIs initiate inflammation in the myocardium, while clinically significant cardiotoxicity were reported in few patients receiving ICI therapy, probably due to the low incidence and unspecific symptoms. The subtle signs and symptoms (e.g., chest pain, dizziness, and dyspnea) were likely attributed to cancer and/or non-cardiac events by previous studies, thus limiting the understanding of the incidence, outcomes, risk factors, and management of ICI-related cardiotoxicity. The heterogeneous clinical presentation and complex diagnostic procedure further make it challenging to accurately identify ICI-related cardiac events in clinical trials. Therefore, ICI-related cardiotoxicity, whose incidence is probably underestimated, has not been well recognized. In this article, we provide an overview of potential mechanisms underlying ICI-related cardiotoxicity and review accumulating clinical evidence of ICI-related cardiotoxicity, with a focus on myocarditis. Moreover, we discuss possible strategies to manage ICI-related cardiotoxicity and highlight the importance of developing cardio-oncology.

Selective serotonin reuptake inhibitors and manic switch: A pharmacovigilance and pharmacodynamical study

BACKGROUND

There is still no approved mechanism of manic switch in bipolar disorder, yet many selective serotonin reuptake inhibitors were accused for this important adverse event. Therefore, we aimed to investigate to estimate SSRI's risk for reporting mania and elevated mood using FEARS database and investigate receptor mechanisms involved.

METHODS

Mania and relevant side effects approved by FDA were screened in this dataset from the first quarter of 2004 to the third quarter of 2020. Disproportionality analysis were performed to estimate reporting odds ratio (ROR) and linear regressions were conducted to investigate relationship between ROR and Ki values. Receptor occupancy ratios were calculated from in vitro receptor binding profiles. The pharmacodynamical profile was extracted from the International Union of Basic and Clinical Pharmacology and the British Pharmacology Society dataset. Child and adolescent population was also investigated separately.

RESULTS

The analysis showed that the odds of a spontaneous report of mania in the FAERS database involving an SSRI were higher than the odds that such a report involved other types of drugs (ROR: 5.324 [CI: 3.773; 7.514]). The largest effect size in this estimation was found in fluvoxamine (ROR: 13.957 [CI: 10.391; 18.747]). Significant effects were found in regression analysis for Ki values of H1 and M1 receptors on ROR. Receptor occupation was not found to have an effect on ROR.

CONCLUSION

Lower degress of Ki values on M1 and H1 may be plausible pharmacological mechanism. Further pharmacological data and clinical assessments may be important to validate this safety signal.

Hospital Adverse Event Reporting Systems: A Systematic Scoping Review of Qualitative and Quantitative Evidence

INTRODUCTION

Reducing the incidence of reportable events with undesirable effects (REUE) is a priority in the hospital environment, which is why reporting systems have been implemented to identify and manage them. Information is required regarding the performance of reporting systems, barriers, or facilitators for reporting and strategies that improve passive reporting.

METHODOLOGY

Systematic scoping review of the literature that included studies performed in the population exposed to the occurrence of REUE in the health system (teams, patients, and family). A search was performed in Cochrane Database of Systematic Reviews, Epistemonikos, MEDLINE (PubMed), MEDLINE In-Process and MEDLINE Daily Update, EMBASE, LILACS, and databases of the World Health Organization and Pan-American Health Organization.

RESULTS

Fifteen studies were found, 1 systematic review, 2 clinical trials, 8 observational studies, 3 qualitative studies, and 1 mixed study. In 4 of them, the effectiveness of active versus passive reporting systems was compared. The measures to improve the passive systems were education about REUE, simplification of the reporting format, activities focused on increasing the motivation for self-report, adoption of self-report as an obligatory institutional policy, and using specific report formats for each service.

CONCLUSIONS

There is information that allows to find differences between the performance of the active and passive reporting systems. The reviewed research articles found that passive techniques significantly underreported adverse events. It is recommended that institutions adopt both active and passive techniques in adverse event surveillance. New studies should be directed to answer the comparative efficiency of the reporting systems.

Renal Safety Profile of EGFR Targeted Therapies: A Study from VigiBase® the WHO Global Database of Individual Case Safety Reports

Kidney EGFR expression together with reported cases of glomerular diseases in the context of anti-EGFR drug administration raise concerns about the renal safety profile of these drugs. This issue is addressed in a case/non-case study carried out on VigiBase®, the WHO global database of individual case safety reports (ICRS). Disproportionality analysis of renal adverse effects related to the selected anti-EGFR drugs, erlotinib, gefitinib, afatinib, osimertinib, cetuximab and panitumumab, was assessed using the reporting odds ratio (ROR). Nine hundred and eighty-nine ICRSs were included. A signal of disproportionate reporting (SDR) was found for afatinib (ROR = 2.70; 95% CI [2.22-3.29]) and erlotinib (ROR = 1.73; 95% CI [1.46-2.04]) with acute kidney injury, and for afatinib (ROR = 2.41; 95% CI [1.78-3.27]), cetuximab (ROR = 1.42; 95% CI [1.14-1.78]) and erlotinib (ROR = 2.23; 95% CI [1.80-2.77]) with renal failure. The preferred term "diarrhoea" was frequently reported in the included cases. An SDR was found for erlotinib with haemolytic and uremic syndrome (ROR = 4.01; 95% CI [1.80-8.94]) and thrombotic microangiopathy (ROR = 4.94; 95% CI [2.80-8.72]). No SDR was seen for glomerular or tubule-interstitial diseases. This study showed that the anti-EGFR drug renal toxicity is mainly related to renal failure in the context of digestive toxicity.

Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review

Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key use cases in which artificial intelligence (AI) could be leveraged to reduce the frequency of ADEs. We focused on modern machine learning techniques and natural language processing. 78 articles were included in the scoping review. Studies were heterogeneous and applied various AI techniques covering a wide range of medications and ADEs. We identified several key use cases in which AI could contribute to reducing the frequency and consequences of ADEs, through prediction to prevent ADEs and early detection to mitigate the effects. Most studies (73 [94%] of 78) assessed technical algorithm performance, and few studies evaluated the use of AI in clinical settings. Most articles (58 [74%] of 78) were published within the past 5 years, highlighting an emerging area of study. Availability of new types of data, such as genetic information, and access to unstructured clinical notes might further advance the field.

Safety Profile of Ibrutinib: An Analysis of the WHO Pharmacovigilance Database

As ibrutinib has become a standard of care in B-cell malignancies in monotherapy or in combination with other agents, definition of its safety profile appears essential. The aim of this study was to further characterize the safety profile of ibrutinib through the identification of potential safety signals in a large-scale pharmacovigilance database. All serious individual case safety reports (ICSRs) in patients aged ≥18 years involving ibrutinib suspected in the occurrence of serious adverse drug reactions or drug interacting from November 13th, 2013 to December 31st, 2020 were extracted from VigiBase, the World Health Organization global safety database. Disproportionality reporting was assessed using the information component (IC) and the proportional reporting ratio (PRR), with all other anticancer drugs used as the reference group. To mitigate the confounding of age, two subgroups were considered: patients aged<75 years and ≥75 years. A signal of disproportionate reporting (SDR) was defined if both IC and PRR were significant. A total of 16,196 ICSRs were included. The median age of patients was 72.9 years, 42.6% of ICSRs concerned patients aged ≥75 years, and 64.2% male patients. More than half (56.2%) of ICSRs resulted in hospitalization or prolonged hospitalization. Among 713 SDRs, 36 potential safety signals emerged in ibrutinib-treated patients, mainly ischemic heart diseases, pericarditis, uveitis, retinal disorders and fractures. All potential safety signals having arisen in this analysis may support patient care and monitoring of ongoing clinical trials. However, owing to the mandatory limitations of this study, our results need further confirmation using population-based studies.