WHODrug: A Global, Validated and Updated Dictionary for Medicinal Information

Efficacy and Safety of 4-Month Rifapentine-Based Tuberculosis Treatments in Persons with Diabetes

A previous study demonstrated noninferior efficacy of 4-month rifapentine/moxifloxacin regimen for tuberculosis (TB) treatment compared with the standard regimen. We explored results among study participants with diabetes. Among 2,516 randomized participants, 181 (7.2%) had diabetes. Of 166 participants with diabetes in the microbiologically eligible analysis group, 26.3% (15/57) had unfavorable outcomes in the control regimen, 13.8% (8/58) in the rifapentine/moxifloxacin regimen, and 29.4% (15/51) in the rifapentine regimen. The difference in proportion of unfavorable outcomes between the control and rifapentine/moxifloxacin arms in the microbiologically eligible analysis group was -12.5% (95% CI -27.0% to 1.9%); the difference between the control and rifapentine arms was 3.1% (95% CI -13.8% to 20.0%). Safety outcomes were similar in the rifapentine/moxifloxacin regimen and control arms. Among participants with TB and diabetes, the rifapentine/moxifloxacin arm had fewest unfavorable outcomes and was safe. Our findings indicate that the rifapentine/moxifloxacin regimen can be used in persons with TB and diabetes.

Clinical Relatedness and Stability of vigiVec Semantic Vector Representations of Adverse Events and Drugs in Pharmacovigilance

INTRODUCTION

Individual case reports are essential to identify and assess previously unknown adverse effects of medicines. On these reports, information on adverse events (AEs) and drugs are encoded in hierarchical terminologies. Encoding differences may hinder the retrieval and analysis of clinically related reports relevant to a topic of interest. Recent studies have explored the use of data-driven semantic vector representations to support analysis of pharmacovigilance data.

OBJECTIVE

This study aims to evaluate the stability and clinical relatedness of vigiVec, a semantic vector representation for codes of AEs and drugs.

METHODS

vigiVec is a published adaptation to pharmacovigilance of the publicly available Word2Vec model, applied to structured data instead of free text. It provides vector representations for MedDRA® Preferred Terms and WHODrug Global active ingredients, learned from reporting patterns in VigiBase, the WHO global database of adverse event reports for medicines and vaccines. For this study, a 20-dimensional Skip-gram architecture with window size 250 was used. Our evaluation focused on nearest neighbors identified by the cosine similarity of vigiVec vector representations. Clinical relatedness was measured through term intruder detection, whereby a medical doctor was tasked to identify a randomly selected term-the intruder-included among the four nearest neighbors to a specific AE or drug. Stability was measured as the average overlap in the ten nearest neighbors for each AE or drug, in repeated fittings of vigiVec.

RESULTS

Among the ten nearest neighbors, 1.8 AEs on average belonged to the same MedDRA High Level Term (HLT; e.g., coagulopathies), and 1.3 drugs belonged to the same Anatomical Therapeutic Chemical level 3 (ATC-3; e.g., opioids). In the intruder detection task, when neighbors and intruders were both chosen from the same HLT, the intruder detection rate was 46%. When selected from different HLTs, it was 79%. By random chance, we should expect 20% (1 in 5). Corresponding rates for drugs were 42% in same ATC-3 and 65% in different ATC-3. The stability of nearest neighbors was 80% for AEs and 64% for drugs.

CONCLUSION

Nearest neighbors identified with vigiVec are stable and show high level of clinical relatedness. They are often from different parts of the existing hierarchies and complement these.

Establishing links between drug registers and essential medicines lists

Access to essential medicines is still suboptimal in many countries. Recent studies examining the registration of medicines at the country level show that a considerable proportion of essential medicines do not have any corresponding products registered for use at the country level and therefore cannot be available at all times. Conversely, many non-essential medicines are registered by regulatory authorities for local markets, potentially facilitating inappropriate drug use and antimicrobial resistance. Addressing this public health gap requires linking the data on national drug registers with national essential medicines lists. Achieving this linkage will necessitate the development of common data variables and standards for both drug registers and essential medicines lists. This linkage would provide medicines regulators and health policy-makers with information on the gaps in the registration of essential medicines and allow them to take steps to prioritize registration of these medicines. This approach would improve availability of essential medicines for public health priorities and prevent over-registration of unnecessary medicines.

Post-marketing pharmacovigilance study of inclisiran: mining and analyzing adverse event data from the FDA Adverse Event Reporting System database

BACKGROUND

Inclisiran, the newest lipid-lowering drug, has not shown significant safety problems in major clinical studies. However, its recent market introduction and limited clinical use have produced few reports of adverse reactions, leaving a comprehensive understanding of its long-term safety yet to be established.

AIM

The aim of the study was to conduct a signal detection analysis of adverse events (AEs) associated with inclisiran using FDA Adverse Event Reporting System (FAERS) datasets.

METHOD

Data on AEs associated with inclisiran were collected from the FAERS database from 2021 to 2023. Signal detection was conducted using the reporting odds ratio (ROR) and the information component (IC). The analysis was standardized using the Medical Dictionary for Regulatory Activities (MedDRA) and focused on System Organ Classes (SOCs) and Preferred Terms.

RESULTS

Of 17,307,196 AE reports, 2976 were relevant to inclisiran. The male-to-female ratio of these events was 0.74:1, predominantly in patients aged 45 to 74 years. A total of 102 AE signals associated with inclisiran were identified in 15 SOCs. Among these, 86 involved muscle injuries, liver injuries, diabetes, neurocognitive dysfunction, and other events not listed on the drug label.

CONCLUSION

The findings confirm all AEs documented on the drug label and in current clinical trials while also revealing new AEs such as muscle pain, elevated liver enzymes, increased blood glucose levels, and neurocognitive dysfunction. This study contributes to real-world research data, providing valuable references for rational drug use.

Reporting of late-onset immune-related adverse events with immune checkpoint inhibitors in VigiBase

BACKGROUND

To date, evidence on late-onset immune-related adverse events (irAEs) with immune checkpoint inhibitors (ICIs) is limited to a small number of clinical cases. This study aimed to identify drug- and patient-related characteristics potentially associated with the reporting of late-onset irAEs with ICIs in VigiBase, the WHO global database of individual case safety reports (ICSRs).

METHODS

Observational study comparing deduplicated ICSRs with ICIs reporting late-onset irAEs (occurred >90 days after ICI discontinuation) versus ICSRs with ICIs not reporting late-onset irAEs, collected in VigiBase from 2011 to December 31, 2022. Logistic regression was used to model the relationship between drug-related and patient-related characteristics of ICSRs and the reporting of late-onset irAEs. Significance was determined for variables with the lower bound of the 95% CI of the reporting OR (ROR) higher than 1 and a p value <0.05.

RESULTS

The study population consisted of 6006 ICSRs with ICI-related irAEs (4574, 76.2%, originated from Europe; 3900, 64.9%, involved males; median patient age was 67 years, IQR 59-74 years). Of these, 344 (5.7%) ICSRs reported a total of 388 late-onset irAEs, among which the most frequent were thyroiditis (n=45), pneumonitis (n=37), interstitial lung disease (n=25), hepatitis (n=23) and vitiligo (n=19). Median time to onset since ICI discontinuation was 167 days (IQR 115-294 days), with negligible proportion (3.2%) of co-reported antineoplastic agents during the discontinuation period. Logistic regression models showed disproportionate reporting of late-onset irAEs with ICI combination therapy (ROR 2.33, 95% CI 1.19 to 4.57), reporting of multiple irAEs (ROR 3.96, 95% CI 2.85 to 5.52), reporting of cutaneous irAEs (ROR 1.83, 95% CI 1.24 to 2.71), and melanoma (ROR 1.47, 95% CI 1.04 to 2.06).

CONCLUSIONS

This global pharmacovigilance study provides the largest case series of late-onset irAEs with ICIs to date and identifies characteristics of ICSRs associated with disproportionate reporting. Dedicated prospective observational studies focused on long-term sequelae, quality of life and survival of patients developing late-onset irAEs with ICIs should be planned to confirm whether these reporting characteristics are predictors of actual occurrence. Furthermore, translational research should be encouraged to clarify the molecular mechanisms underlying late-onset irAE development.

Greater recalled pain and movement-evoked pain are associated with longer 400-meter walk and repeat stair climb time: the Study of Muscle, Mobility and Aging

Background

Musculoskeletal pain frequently accompanies the development of mobility disability and falls in old age. To better understand this, we aimed to quantify the impact of different pain measures-recalled pain and movement-evoked pain-on 400-meter walk and stair climb time in older adults participating in the Study of Muscle, Mobility and Aging (SOMMA).

Methods

In SOMMA (N=879, age=76.3 ± 5.0 years, 59% women, 84% Non-Hispanic White), participants completed usual pace 400m walk (avg=6.6 ± 1.2 min.) and repeat stair climb tests (avg=26.6 ± 7.2 sec.). Assessments of recalled pain included the Brief Pain Inventory short form (BPI-sf), total lower body pain (lower back, hips, knees, feet/ankles), stiffness (hip or knee), and Neuropathy Total Symptom Score (NTSS-6). Movement-evoked pain was assessed separately before and after the 400m walk and repeat stair climb tasks. Multivariable linear regression modeled the associations of pain with time to complete the tasks, reported as β[95%CI] expressed per SD increment of pain measure or β[95%CI] per pain categories, adjusted for age, sex, race, ethnicity, body mass index, prescription medications, and depressive symptoms.

Results

Greater degree of any pain measure was associated with longer physical performance time, though intercorrelations between recalled pain measures varied (r=0.13-0.57, p<0.05 for all). For each SD increment in lower body pain, participants had longer walk time (by 10.5 sec [6.1, 14.8]) and stair climb (by 0.6 sec [0.1, 1.1]). Compared to participants with no change in pain upon movement, walk time was longer in those with more pain upon movement (19.5 sec [10.3, 28.7]) (p<0.001) but not those with less pain upon movement; stair climb showed similar patterns.

Conclusions

Recalled and movement-evoked pain measures were weakly correlated with one another but similarly associated with time to complete 400m walk and stair climb tests. Different pain assessments capture different functional domains of pain but have similar associations with physical performance in these older adults.

Drug-Drug Interactions and the Clinical Tolerability of Colchicine Among Patients With COVID-19: A Secondary Analysis of the COLCORONA Randomized Clinical Trial

Importance

Colchicine has many drug-drug interactions with commonly prescribed medications. Only pharmacokinetic studies have provided data on colchicine drug-drug interactions.

Objective

To evaluate the clinical tolerability of colchicine according to the presence or absence of a drug-drug interaction.

Design, Setting, and Participants

A secondary analysis of the COLCORONA trial was performed. The COLCORONA trial was a randomized, double-blind, placebo-controlled trial conducted in Brazil, Canada, Greece, South Africa, Spain, and the US between March 23, 2020, and January 20, 2021. The COLCORONA trial included ambulatory patients with COVID-19 with at least 1 high-risk characteristic and compared the effects of colchicine (0.5 mg twice daily for 3 days, then 0.5 mg daily thereafter) with placebo for 27 days. Data analysis was performed from February 24, 2023, to June 20, 2024.

Exposure

In this secondary analysis, baseline medications that had interactions with colchicine were identified using a previously published expert classification.

Main Outcomes and Measures

The primary outcome for this analysis was the composite of serious and nonserious treatment-related and treatment-unrelated gastrointestinal adverse events. The secondary outcomes were other adverse events and the composite of death or hospital admission due to COVID-19 infection. Logistic regression models adjusted for age, sex, estimated glomerular filtration rate, diabetes, heart failure, and myocardial infarction were assessed for effect modification of the association between the randomization arm and the outcomes of interest by drug-drug interaction status.

Results

The cohort included 2205 participants in the colchicine arm and 2227 in the placebo arm (median age, 54 [IQR, 47-61] years; 2389 [54%] women). The most common colchicine drug-drug interactions were rosuvastatin (12%) and atorvastatin (10%). In fully adjusted models, the odds of any gastrointestinal adverse event were 1.80 (95% CI, 1.51-2.15) times higher in the colchicine arm than the placebo arm among people without a drug-drug interaction and 1.68 (95% CI, 1.24-2.26) times higher in the colchicine arm than the placebo arm among people with a drug-drug interaction (P = .69 for interaction). Drug-drug interaction status did not significantly modify the effect of colchicine on the composite of COVID-19 hospitalization or death (odds ratio, 0.91; 95% CI, 0.59-1.40 for drug-drug interaction and 0.84; 95% CI, 0.60-1.19 for no drug-drug interaction; P = .80 for interaction).

Conclusions and Relevance

In this secondary analysis of the COLCORONA trial, operational classification of drug interactions system class 3 or 4 drug-drug interactions did not appear to significantly increase the risk of colchicine-related adverse effects.

Trial Registration

ClinicalTrials.gov Identifier: NCT04322682.

Signal mining of adverse reactions in the antiemetic drug ondansetron during pregnancy: A real-world analysis of the FDA adverse event reporting system (FAERS)

BACKGROUND

The aim of this study is to assess the risks associated with the use of ondansetron in pregnant women in real-world based on the Food and Drug Administration adverse Event Reporting System (FAERS).

METHODS

The FAERS data from the 2017Q1 to the 2023Q1, which was used by the ratio-of-reporting (ROR) and Bayesian confidence interval progressive neural network (BCPNN) to assess the safety of ondansetron in pregnancy.

RESULTS

A total of 15,727 pregnancy population reports were reported, with a total of 1,064 reports of adverse reactions with ondansetron as the primary suspected drug. Ondansetron was involved in a total of 10 system organ classifications (SOCs) of signal generation, and the top three signal intensities were Congenital, familial, and genetic disorders (ROR = 19.1, ROR025 = 17.03; IC = 1.23, IC025 = 1.16), Ear and labyrinth disorders (ROR = 17.11, ROR025 = 12.46; IC = 1.22, IC025 = 1.03), and Cardiac disorders (ROR = 9.48, ROR025 = 8.38; IC = 1.12, IC025 = 1.03); signals of adverse reactions obtained of 216, of which the main ones were Anhedonia (IC = 1.34, IC025 = 1.08), Injury (IC = 1.34, IC025 = 1.19), Left-to-right cardiac shunt (IC = 1.33, IC025 = 1.05).

CONCLUSION

The adverse reactions of Ondansetron involve multiple systems and organs, which should cause clinical vigilance. However, due to the limitations of the data, the causal relationship and risk level of adverse reactions cannot be accurately inferred.

Safety of Monoclonal Antibodies Inhibiting PCSK9 in Pregnancy: Disproportionality Analysis in VigiBase®

Safety data on the use of monoclonal antibodies inhibiting proprotein convertase subtilisin/kexin type 9 in pregnancy are scarce. This study queried VigiBase®, the World Health Organization global pharmacovigilance database, to search for signals of disproportionate reporting for pregnancy outcomes with alirocumab and evolocumab. As of November 22, 2023, there were 45 safety reports of exposure to evolocumab (N = 31) and alirocumab (N = 14) in pregnancy. Most of them originated from Europe (N = 25, 55.6%) and were more frequently reported by healthcare professionals (N = 35, 77.8%). Median patient age was 37 years (25th-75th percentiles; 32-41 years). Drug exposure occurred during pregnancy in 36 (80.0%) safety reports, via paternal exposure during pregnancy in four (8.9%), during lactation in three (6.7%), and in two safety reports the time of drug exposure remained unknown. Twenty safety reports (57.8%) merely reported drug exposure, while 19 (42.2%) also reported pregnancy outcomes, however, without specific maternal toxicities or patterns of birth defects. Spontaneous abortion was reported in eight safety reports without representing a signal of disproportionate reporting compared with either the full database (reporting odds ratio, ROR, 0.06 95% confidence interval, CI 0.03-0.12) or statins (ROR 0.16, 95% CI 0.08-0.32). In conclusion, this study showed that, currently, there are no signals of increased reporting of spontaneous abortion with alirocumab and evolocumab compared with the full database and statins in VigiBase®. Notwithstanding, lack of disproportionality is not synonymous with safety and, as disproportionality analyses depend on the number of safety reports that progressively accumulate in VigiBase®, they should be repeated at regular intervals to confirm the results of the present study.

Enhancing Transparency in Defining Studied Drugs: The Open-Source Living DiAna Dictionary for Standardizing Drug Names in the FAERS

INTRODUCTION

In refining drug safety signals, defining the object of study is crucial. While research has explored the effect of different event definitions, drug definition is often overlooked. The US FDA Adverse Event Reporting System (FAERS) records drug names as free text, necessitating mapping to active ingredients. Although pre-mapped databases exist, the subjectivity and lack of transparency of the mapping process lead to a loss of control over the object of study.

OBJECTIVE

We implemented the DiAna dictionary, systematically mapping individual free-text instances to their corresponding active ingredients and linking them to the World Health Organization Anatomical Therapeutic Chemical (WHO-ATC) classification.

METHODS

We retrieved all drug names reported to the FAERS (2004-December 2022). Using existing vocabularies and string editing, we automatically mapped free text to ingredients. We manually revised the mapping and linked it to the ATC classification.

RESULTS

We retrieved 18,151,842 reports, with 74,143,411 drug entries. We manually checked the first 14,832 terms, up to terms occurring over 200 times (96.88% of total drug entries), to 6282 unique active ingredients. Automatic unchecked translations extend the standardization to 346,854 terms (98.94%). The DiAna dictionary showed a higher sensitivity compared with RxNorm alone, particularly for specific drugs (e.g., rimegepant, adapalene, drospirenone, umeclidinium). The most prominent drug classes in the FAERS were immunomodulating (37.40%) and neurologic drugs (29.19%).

CONCLUSION

The DiAna dictionary, as a dynamic open-source tool, provides transparency and flexibility, enabling researchers to actively shape drug definitions during the mapping phase. This empowerment enhances accuracy, reproducibility, and interpretability of results.

Harmonization of individual case safety reports transmission requirements among PAHO reference authorities: a review of their current regulation

To perform optimal monitoring of the safety profile in the postmarketing phase, Marketing Authorization Holders and National Regulatory Authorities (NRAs) must evaluate the adverse drug reactions (ADRs) that occurred and characterize their nature, frequency, and severity. Management is possible through Individual Case Safety Reports (ICSRs), which are the reports of organized and processed data. Globally, the International Council for Harmonisation (ICH) E2B guideline suggests harmonized activities for the ICSR electronic content and transmission. In America, the Pan American Health Organization (PAHO) is the agency responsible to implement cooperation among its members, which are recognized as National Regulatory Authorities of Reference (NRARs) such as Argentina, Brazil, Canada, Chile, Colombia, Cuba, Mexico, and the United States. PAHO published the 'Good Pharmacovigilance Practices for the Americas' suggesting improvement and harmonization in the region. After reviewing the regulatory framework, it is assumed that all NRARs have a regulated ICSR transmission system (i.e. a systematic vigilance system for collecting, analyzing, and disseminating information from ADRs). However, significant differences exist, such as the requirement for social media vigilance, expedited and non-expedited ICSRs, coding, severity, and transmission. The volume of ICSRs has significantly increased, due to using electronic standards managed by the NRAs, which facilitates early identification of new ADRs, allowing the implementation of novel minimization activities, contributing to the continuous assessment of the benefit-risk balance of medicines. Nevertheless, there is still area for improvement, especially in Latin America.

Safety of selinexor as the only exportin 1 (XPO1) inhibitor so far: a post-marketing study based on the world Health Organization pharmacovigilance database (Vigibase)

BACKGROUND

Exportin 1 (XPO1) inhibitors are being developed as a new agent for anti-cancer therapies. This study aimed to broadly portray the adverse event (AE) profile of selinexor, an XPO1 inhibitor, in actual clinical practice.

RESEARCH DESIGN AND METHODS

Disproportionality analyses were conducted by calculating the information component and reporting odds ratio in VigiBase over different reporting periods. All selinexor-related AEs were classified by system organ class (SOC) and preferred term (PT) according to the Medical Dictionary for Regulatory Activities.

RESULTS

A total of 116,443 AEs were identified in 2,608 patients that received selinexor. Patients with cardiac disorders had a higher propensity for death. Thirteen SOCs and 125 PTs were identified as having a potential connection with selinexor. Notably, 29 suspected signals detected in our study were defined as significant AEs by the European Medicines Agency, including febrile neutropenia, pancytopenia, and acute kidney injury. Attention should be paid to these AEs, despite most toxicities being manageable and reversible.

CONCLUSIONS

This study highlights a number of AEs associated with selinexor. Most toxicities are reversible but require careful management. The benefit of selinexor still outweighs the potential risks, indicating XPO1 inhibitors as promising agents.

Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study

INTRODUCTION

Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals.

OBJECTIVE

The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process.

METHODS

Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals.

RESULTS

Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15-60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development.

CONCLUSIONS

Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research.

Strengthening the Pharmacovigilance System in Mexico: Implementation of VigiFlow and VigiLyze, as ICSR and Signal Detection Management Systems

Pharmacovigilance (PV) activities aim to identify potential risks of medicines and vaccines after they have been authorised in the market by collecting and analysing information on suspected adverse events from different stakeholders. These can be captured and transmitted electronically in the form of Individual Case Safety Reports (ICSRs). Hence, up-to-date ICSRs management systems, like VigiFlow and signal detection and management systems as VigiLyze, have an important role in the PV system of a country. In 2019, after various attempts to establish a PV database that could fulfil the needs of the country, Mexico's National Regulatory Authority, COFEPRIS (Federal Commission for the Prevention against Sanitary Risks) decided to implement these tools. This has been a successful project that is still ongoing, it has involved national and international organisations, and has required the participation and integration of different components of the national PV system. The implementation of these tools has allowed COFEPRIS to increase its reporting trends and quality of reporting, while contributing to make more efficient interactions and processes with PV stakeholders, even during the COVID-19 pandemic. It has also allowed them to strengthen their commitment to the WHO-Programme for International Drug Monitoring, while highlighting opportunities for improvement in the national PV scenario and in the PV tools themselves. The aim of this article is to describe the implementation process, give an overview of current results regarding ICSR data and processes, and highlight the achievements, challenges, and opportunities for improvement after the three years since the beginning of the project.

The Study of Muscle, Mobility and Aging (SOMMA): A Unique Cohort Study About the Cellular Biology of Aging and Age-related Loss of Mobility

BACKGROUND

The Study of Muscle, Mobility and Aging (SOMMA) aims to understand the biological basis of many facets of human aging, with a focus on mobility decline, by creating a unique platform of data, tissues, and images.

METHODS

The multidisciplinary SOMMA team includes 2 clinical centers (University of Pittsburgh and Wake Forest University), a biorepository (Translational Research Institute at Advent Health), and the San Francisco Coordinating Center (California Pacific Medical Center Research Institute). Enrollees were age ≥70 years, able to walk ≥0.6 m/s (4 m); able to complete 400 m walk, free of life-threatening disease, and had no contraindications to magnetic resonance or tissue collection. Participants are followed with 6-month phone contacts and annual in-person exams. At baseline, SOMMA collected biospecimens (muscle and adipose tissue, blood, urine, fecal samples); a variety of questionnaires; physical and cognitive assessments; whole-body imaging (magnetic resonance and computed tomography); accelerometry; and cardiopulmonary exercise testing. Primary outcomes include change in walking speed, change in fitness, and objective mobility disability (able to walk 400 m in 15 minutes and change in 400 m speed). Incident events, including hospitalizations, cancer diagnoses, fractures, and mortality are collected and centrally adjudicated by study physicians.

RESULTS

SOMMA exceeded its goals by enrolling 879 participants, despite being slowed by the COVID-19 pandemic: 59.2% women; mean age 76.3 ± 5.0 years (range 70-94); mean walking speed 1.04 ± 0.20 m/s; 15.8% identify as other than Non-Hispanic White. Over 97% had data for key measurements.

CONCLUSIONS

SOMMA will provide the foundation for discoveries in the biology of human aging and mobility.

Montelukast and Nightmares: Further Characterisation Using Data from VigiBase

INTRODUCTION

Montelukast is a medicine indicated for use in asthma. Psychiatric disorders including nightmares have not been described in clinical trials but during recent years have been included in the product information as having been reported post-marketing, without further description of the events. Previous descriptions in the scientific literature were based on limited numbers of reports or lacked detailed case information.

OBJECTIVE

The study aim was to further characterise post-marketing adverse drug reactions for nightmares, suspected to be induced by montelukast, to facilitate safer use of the medicine by providing additional information to patients and healthcare professionals.

METHODS

We clinically reviewed reports of nightmares with montelukast present in VigiBase, World Health Organization's global database of suspected adverse reactions to medicinal products, developed and maintained by the Uppsala Monitoring Centre, until 3 May, 2020.

RESULTS

There were 1118 reports of nightmares with montelukast in VigiBase, which provided valuable descriptions of the nightmares as well as information about the impact on the daily lives, with many cases describing a severe impact of the nightmares. About half of the reports were classified as serious. Two thirds concerned children, with the largest age group represented being children aged 5-10 years. In most cases, the nightmares disappeared upon discontinuation of the drug but for some patients it took a long time until the nightmares ceased.

CONCLUSIONS

The nature and potential severity of this adverse drug reaction, as described in these reports, present important knowledge for patients and healthcare providers that could help reduce drug-induced harm. This study highlights the value of post-marketing reports for further characterisation of known adverse drug reactions. The benefit-risk balance should be continuously monitored while patients are taking montelukast.

Post-Marketing Safety Profile of Vortioxetine Using a Cluster Analysis and a Disproportionality Analysis of Global Adverse Event Reports

Introduction

Vortioxetine, a multimodal serotonergic drug, is widely used as treatment for major depressive disorder. Although on the market since late 2013, the data of the relative safety of vortioxetine, especially compared to selective serotonin reuptake inhibitors, are still scarce.

Objective

The aim of this study was to explore the adverse event reporting pattern of vortioxetine through a cluster analysis. Furthermore, to compare the adverse event reporting pattern for vortioxetine with that of the selective serotonin reuptake inhibitors.

Methods

Individual case safety reports for vortioxetine in VigiBase up to 1 November, 2019 were subjected to consensus clustering, to identify and describe natural groupings of reports based on their reported adverse events. A vigiPoint exploratory analysis compared vortioxetine to the selective serotonin reuptake inhibitors in terms of relative frequencies for a wide range of covariates, including patient sex and age, reported drugs and adverse events, and reporting country. Important differences were identified using odds ratios with adaptive statistical shrinkage.

Results

Thirty-six clusters containing at least five reports were identified and analysed. The two largest clusters included 48% of the vortioxetine reports and appeared to represent gastrointestinal adverse events and hypersensitivity adverse events. Other distinct clusters were related to, respectively, fatigue, aggression/suicidality, convulsion, medication errors, arthralgia/myalgia, increased weight, paraesthesia and anticholinergic effects. Some of these clusters are not labelled for vortioxetine, such as arthralgia/myalgia and paraesthesia, but are known adverse events for selective serotonin reuptake inhibitors. A vigiPoint analysis revealed a higher proportion of reports from consumers and non-health professionals for vortioxetine as well as higher relative reporting rates of gastrointestinal symptoms, pruritus and mood-related symptoms, consistent with the cluster analysis.

Conclusions

A pattern of co-reported adverse events that is consistent with labelled adverse events for vortioxetine and the safety profile for selective serotonin reuptake inhibitors in general was revealed. Clusters of unlabelled adverse events were identified that reflect clinical entities that might represent signals of previously unknown adverse events. More extensive analyses of spontaneous reports may help to further understand the reporting pattern of adverse events.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01139-y.

Automated Drug Coding Using Artificial Intelligence: An Evaluation of WHODrug Koda on Adverse Event Reports

INTRODUCTION

Coding medicinal products described on adverse event (AE) reports to specific entries in standardised drug dictionaries, such as WHODrug Global, is a time-consuming step in case processing activities despite its potential for automation. Many organisations are already partially automating drug coding using text-processing methods and synonym lists, however addressing challenges such as misspellings, abbreviations or ambiguous trade names requires more advanced methods. WHODrug Koda is a drug coding engine using text-processing algorithms, built-in coding rules and machine learning to code drug verbatims to WHODrug Global.

OBJECTIVE

Our aim was to evaluate the drug coding performance of WHODrug Koda on AE reports from VigiBase, the World Health Organization's global database of individual case safety reports, in terms of level of automation and coding quality.

METHODS

Koda was evaluated on 4.8 million drug entries from VigiBase. Automation level was computed as the proportion of drug entries automatically coded by Koda and was compared to a simple case-insensitive text-matching algorithm. Coding quality was evaluated in terms of coding accuracy, by comparing Koda's prediction to the WHODrug entries found on the AE reports in VigiBase. To better understand the cases in which Koda's coding results did not match with the WHODrug entries in VigiBase, a manual assessment of 600 samples of disagreeing encodings was performed by two teams of expert drug coders.

RESULTS

Compared with a simple direct-match baseline, Koda can increase the automation level from 61% to 89%, while providing high coding quality with an accuracy of 97%.

CONCLUSIONS

Even though Koda was designed for use in clinical trials, Koda achieves automation level and coding quality for drug coding of AE reports comparable with the performance observed in a previous evaluation of Koda on clinical trial data. Koda can thus help organisations to automate their drug coding of AE reports to a large degree.

Consensus clustering for case series identification and adverse event profiles in pharmacovigilance

OBJECTIVE

To describe and evaluate vigiGroup - a consensus clustering algorithm which can identify groups of individual case reports referring to similar suspected adverse drug reactions and describe associated adverse event profiles, accounting for co-reported adverse event terms.

MATERIALS AND METHODS

Consensus clustering is achieved by grouping pairs of reports that are repeatedly placed together in the same clusters across a set of mixture model-based cluster analyses. The latter use empirical Bayes statistical shrinkage for improved performance. As baseline comparison, we considered a regular mixture model-based cluster analysis. Three randomly selected drugs in VigiBase, the World Health Organization's global database of Individual Case Safety Reports were analyzed: sumatriptan, ambroxol and tacrolimus. Clustering stability was assessed using the adjusted Rand index, ranging between -1 and +1, and clinical coherence was assessed through an intruder detection analysis.

RESULTS

For the three drugs considered, vigiGroup achieved stable and coherent results with adjusted Rand indices between +0.80 and +0.92, and intruder detection rates between 86% and 94%. Consensus clustering improved both stability and clinical coherence compared to mixture model-based clustering alone. Statistical shrinkage improved the stability of clusters compared to the baseline mixture model, as well as the cross-validated log-likelihood.

CONCLUSIONS

The proposed algorithm can achieve adequate stability and clinical coherence in clustering individual case reports, thereby enabling better identification of case series and associated adverse event profiles in pharmacovigilance. The use of empirical Bayes shrinkage and consensus clustering each led to meaningful improvements in performance.

Safety of medicines and vaccines - building next generation capability

The systematic safety surveillance of real-world use of medicinal products and related activities (pharmacovigilance) started in earnest as a scientific field only in the 1960s. While developments have occurred over the past 50 years, adding to its complexity and sophistication, the extent to which some of these advances have positively impacted the capability for ensuring patient safety is questionable. We review how the conduct of safety surveillance has changed, highlight recent scientific advances, and argue how they need to be harnessed to enhance pharmacovigilance in the future. Specifically, we describe five changes that we believe should and will need to happen globally in the coming years: (i) better, more diverse data used for safety; (ii) the switch from manual activities to automation; (iii) removal of limited value, extraneous transactional activities and replacement with sharpened focus on scientific efforts to improve patient safety; (iv) patient-involved and focussed safety; and (v) personalised safety.

Interstitial Lung Disease as an Adverse Drug Reaction in Japan: Exploration of Regulatory Actions as a Basis for High Reporting

Introduction

Increased post-marketing reports of interstitial lung disease in Japan have been recognized. An understanding of its regional groundings can be important for the global pharmacovigilance community.

Objective

The objective of this study was to explore the correlation between high rates of interstitial lung disease reporting and regulatory actions in Japan.

Methods

Post-marketing interstitial lung disease-related label changes and interstitial lung disease reports were classified by the anatomical therapeutic chemical classification groups of the suspected drugs. Regulatory actions for the top interstitial lung disease-reporting drugs were compared. The interstitial lung disease reporting patterns of protein kinase inhibitors were compared to those of methotrexate.

Results

Interstitial lung disease-related label changes predominantly occurred for drugs in the anatomical therapeutic chemical classification groups L, J, C, and herbal medicines. Interstitial lung disease was reported most frequently for L group, especially for the protein kinase inhibitors. The regulatory actions for those drugs with the highest number of interstitial lung disease reports (methotrexate, protease kinase inhibitors, gemcitabine, docetaxel) plus monoclonal antibodies were analyzed. The ratio of interstitial lung disease reports to all reports over time was initially high in the re-examination period, while it was constantly low after the period expired. The increase in interstitial lung disease reporting was observed for the drugs for which interstitial lung disease was designated as a priority item in the use-results survey. Methotrexate had more interstitial lung disease reports with multiple suspected drugs and fewer reports with high completeness than the protease kinase inhibitors.

Conclusions

The high rates of interstitial lung disease reporting derived from mainly the anatomical therapeutic chemical classification group L drugs. Interstitial lung disease is the targeted adverse drug reaction in the use-results survey mandated in the re-examination of those drugs. This system provides at least one explanation for the high reporting of interstitial lung disease in Japan.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00968-7) contains supplementary material, which is available to authorized users.

Risk Factor Considerations in Statistical Signal Detection: Using Subgroup Disproportionality to Uncover Risk Groups for Adverse Drug Reactions in VigiBase

Introduction

In the treatment of the individual patient, a vision is to achieve the best possible balance between benefit and harm. Such tailored therapy relies upon the identification and characterisation of risk factors for adverse drug reactions. Information relevant to risk factor considerations can be captured in adverse event reports and could be utilised in statistical signal detection.

Objective

The aim of this study was to explore whether statistical screening of a broad range of risk factors within a global database of adverse event reports could uncover signals of risk groups for adverse drug reactions.

Methods

Subgroup disproportionality analysis was applied to 15.4 million reports entered in VigiBase, the World Health Organization (WHO) global database of individual case safety reports, up to August 2017. Disproportionality analyses for drug–adverse event pairs were performed (1) in the full database and (2) across a range of subgroups defined by the following covariates: patient age, sex, body mass index, pregnancy, underlying condition, reporting country, and geographical region. Drug–adverse event pairs disproportionately over-reported in such subgroups, but not in the full database, and with a substantial difference between the two observed-to-expected ratios, were highlighted as statistical signals. These were further prioritised, through filtering and sorting, for clinical assessment, whereafter clinically relevant signals were communicated to the pharmacovigilance community and the public.

Results

Assessments were performed for 354 prioritised statistical signals, resulting in seven communicated signals describing previously unrecognised potential risk groups related to age (elderly), sex (male and female), body mass index (underweight and obese), and geographical region (Asia), all except one for already established adverse drug reactions. Important aspects considered in the assessments included an evaluation of the disproportionate over-reporting in the subgroup by reviewing alternative explanations and reporting patterns for similar drugs/adverse events/subgroups, and a search for plausible mechanisms to support the risk hypothesis.

Conclusions

This study reveals that it is possible to uncover signals of risk groups for adverse drug reactions through incorporation of broad risk factor screening into statistical signal detection in a global database of adverse event reports. Our findings suggest the potential to use such statistical methodologies for risk characterisation in subpopulations of concern.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00957-w) contains supplementary material, which is available to authorized users.

A Feasibility Study of Drug-Drug Interaction Signal Detection in Regular Pharmacovigilance

Introduction

Adverse drug reactions related to drug–drug interactions cause harm to patients. There is a body of research on signal detection for drug interactions in collections of individual case reports, but limited use in regular pharmacovigilance.

Objective

The aim of this study was to evaluate the feasibility of signal detection of drug–drug interactions in collections of individual case reports of suspected adverse drug reactions.

Methods

This study was conducted in VigiBase, the WHO global database of individual case safety reports. The data lock point was 31 August 2016, which provided 13.6 million reports for analysis after deduplication. Statistical signal detection was performed using a previously developed predictive model for possible drug interactions. The model accounts for an interaction disproportionality measure, expressed suspicion of an interaction by the reporter, potential for interaction through cytochrome P450 activity of drugs, and reported information indicative of unexpected therapeutic response or altered therapeutic effect. Triage filters focused the preliminary signal assessment on combinations relating to serious adverse events with case series of no more than 30 reports from at least two countries, with at least one report during the previous 2 years. Additional filters sought to eliminate already known drug interactions through text mining of standard literature sources. Preliminary signal assessment was performed by a multidisciplinary group of pharmacovigilance professionals from Uppsala Monitoring Centre and collaborating organizations, whereas in-depth signal assessment was performed by experienced pharmacovigilance assessors.

Results

We performed preliminary signal assessment for 407 unique drug pairs. Of these, 157 drug pairs were considered already known to interact, whereas 232 were closed after preliminary assessment for other reasons. Ten drug pairs were subjected to in-depth signal assessment and an additional eight were decided to be kept under review awaiting additional reports. The triage filters had a major impact in focusing our preliminary signal assessment on just 14% of the statistical signals generated by the predictive model for drug interactions. In-depth assessment led to three signals communicated with the broader pharmacovigilance community, six closed signals and one to be kept under review.

Conclusion

This study shows that signals of adverse drug interactions can be detected through broad statistical screening of individual case reports. It further shows that signal assessment related to possible drug interactions requires more detailed information on the temporal relationship between different drugs and the adverse event. Future research may consider whether interaction signal detection should be performed not for individual adverse event terms but for pairs of drugs across a spectrum of adverse events.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00939-y) contains supplementary material, which is available to authorized users.

The Use of Subgroup Disproportionality Analyses to Explore the Sensitivity of a Global Database of Individual Case Safety Reports to Known Pharmacogenomic Risk Variants Common in Japan

INTRODUCTION

Genetic variations of enzymes that affect the pharmacokinetics and hence effects of medications differ between ethnicities, resulting in variation in the risk of adverse drug reactions (ADR) between different populations. Previous work has demonstrated that risk-group considerations can be incorporated into approaches of statistical signal detection. It is unknown whether databases of individual case safety reports (ICSRs) are sensitive to pharmacogenomic differences between populations.

OBJECTIVE

The aim of this study was to explore the sensitivity of a global database of ICSRs to known pharmacogenomic risk variants common in Japan.

METHODS

The data source was VigiBase, the global database of ICSRs, including all reports entered in the version frozen on 5 January 2020. Subgroup disproportionality analysis was used to compare ICSRs of two subgroups, Japan and rest of world (RoW). Reports for UGT1A1-metabolized irinotecan and the CYP2C19-metabolized drugs voriconazole, escitalopram and clopidogrel were selected for comparison between the subgroups based upon known genetic polymorphisms with high prevalence in Japan. Contrast between the subgroups was quantified by IC delta [Formula: see text]), a robust shrinkage observed-to-expected (OE) ratio on a log scale. Harmonic mean p values (HMP) were calculated for each drug to evaluate whether a list of pre-specified ADRs were collectively significantly over- (or under-)reported as hypothesized. Daily drug dosages were calculated for ICSRs with sufficient information, and dose distributions were compared between Japan and RoW and related to differences in regionally approved doses.

RESULTS

The predictions of over-reporting patterns for specific ADRs were observed and confirmed in bootstrap HMP analyses (p = 0.004 for irinotecan and p < 0.001 for each of voriconazole, escitalopram and clopidogrel) and compared with similar drugs with different metabolic pathways. The impact of proactive regulatory action, such as recommended dosing and therapeutic drug monitoring (TDM), was also observable within the global database. For irinotecan and escitalopram, there was evidence of use of lower dosages as recommended in the Japanese labels; for voriconazole, there was evidence of use of TDM with an over-reporting of terms related to drug level measurements and an under-reporting of liver toxicity.

CONCLUSIONS

Pharmaco-ethnic vulnerabilities caused by pharmacogenomic differences between populations may contribute to differences in ADR reporting between countries in a global database of ICSRs. Regional analyses within a global database can inform on the effectiveness of local risk minimization measures and should be leveraged to catalyse the conversion of real-world usage into safer use of drugs in ethnically tailored ways.

Signal Detection in EUROmediCAT: Identification and Evaluation of Medication-Congenital Anomaly Associations and Use of VigiBase as a Complementary Source of Reference

INTRODUCTION

Knowledge on the safety of medication use during pregnancy is often sparse. Pregnant women are generally excluded from clinical trials, and there is a dependence on post-marketing surveillance to identify teratogenic medications.

AIMS

This study aimed to identify signals of potentially teratogenic medications using EUROmediCAT registry data on medication exposure in pregnancies with a congenital anomaly, and to investigate the use of VigiBase reports of adverse events of medications in the evaluation of these signals.

METHODS

Signals of medication-congenital anomaly associations were identified in EUROmediCAT (21,636 congenital anomaly cases with 32,619 medication exposures), then investigated in a subset of VigiBase (45,749 cases and 165,121 exposures), by reviewing statistical reporting patterns and VigiBase case reports. Evidence from the literature and quantitative and qualitative aspects of both datasets were considered before recommending signals as warranting further independent investigation.

RESULTS

EUROmediCAT analysis identified 49 signals of medication-congenital anomaly associations. Incorporating investigation in VigiBase and the literature, these were categorised as follows: four non-specific medications; 11 likely due to maternal disease; 11 well-established teratogens; two reviewed in previous EUROmediCAT studies with limited additional evidence; and 13 with insufficient basis for recommending follow-up. Independent investigations are recommended for eight signals: pregnen (4) derivatives with limb reduction; nitrofuran derivatives with cleft palate and patent ductus arteriosus; salicylic acid and derivatives with atresia or stenosis of other parts of the small intestine and tetralogy of Fallot; carbamazepine with atrioventricular septal defect and severe congenital heart defect; and selective beta-2-adrenoreceptor agonists with posterior urethral valve and/or prune belly.

CONCLUSION

EUROmediCAT data should continue to be used for signal detection, accompanied by information from VigiBase and review of the existing literature to prioritise signals for further independent evaluation.

Drug-Drug Interactions Leading to Adverse Drug Reactions with Rivaroxaban: A Systematic Review of the Literature and Analysis of VigiBase

Rivaroxaban has become an alternative to vitamin K antagonists, which are considered to be at higher risk of drug-drug interactions (DDI) and more difficult to use. However, DDI do occur. We systematically reviewed studies that evaluated them and analysed DDI and subsequent adverse drug reactions (ADR) reported in spontaneous reports and VigiBase. We systematically searched articles that explored DDI with rivaroxaban up to 20 August 2018 via Medline, Embase and Google Scholar. Data from VigiBase came from spontaneous reports recovered up to 2 January 2018, where Omega was used to detect signals and identify potential interactions in terms of triplets with two drugs and one ADR. We identified 31 studies and 28 case reports. Studies showed significant variation in the pharmacokinetic for rivaroxaban, and an increased risk of haemorrhage or thromboembolic events due to DDI was highlighted in case reports. From VigiBase, a total of 21,261 triplets were analysed and the most reported was rivaroxaban–aspirin–gastrointestinal haemorrhage. In VigiBase, only 34.8% of the DDI reported were described or understood, and most were pharmacodynamic DDI. These data suggest that rivaroxaban should be considered to have significant potential for DDI, especially with CYP3A/P-gp modulators or with drugs that impair haemostasis.

Pre-Existing Cardiovascular Conditions as Clinical Predictors of Myocarditis Reporting with Immune Checkpoint Inhibitors: A VigiBase Study

Simple Summary

Up to 50% of myocarditis events developed in cancer patients upon treatment with immune checkpoint inhibitors (ICIs) are fatal. Therefore, identification of clinical risk factors predicting myocarditis onset during treatment with ICIs is important for the purpose of cardiac surveillance of high-risk patients. The aim of this retrospective matched case-control study was to assess whether pre-existing cardiovascular conditions were associated with the reporting of myocarditis with ICIs in VigiBase, the World Health Organization global database of suspected adverse drug reactions. Taking drugs labelled for the treatment of cardiovascular conditions as a proxy for concomitant cardiovascular risk factors and/or cardiovascular diseases, we found an association of moderate size between pre-existing cardiovascular conditions and the reporting of myocarditis with ICIs. Future prospective pharmacoepidemiological studies should assess the causal relationship between pre-existing cardiovascular conditions and myocarditis onset in a cohort of cancer patients followed during treatment with ICIs.

Abstract

Although rare, immune checkpoint inhibitor (ICI)-related myocarditis can be life-threatening, even fatal. In view of increased ICI prescription, identification of clinical risk factors for ICI-related myocarditis is of primary importance. This study aimed to assess whether pre-existing cardiovascular (CV) patient conditions are associated with the reporting of ICI-related myocarditis in VigiBase, the WHO global database of suspected adverse drug reactions (ADRs). In a (retrospective) matched case-control study, 108 cases of ICI-related myocarditis and 108 controls of ICI-related ADRs other than myocarditis were selected from VigiBase. Drugs labeled as treatment for CV conditions (used as a proxy for concomitant CV risk factors and/or CV diseases) were found to be associated more strongly with the reporting of ICI-related myocarditis than with other ICI-related ADRs (McNemar’s chi-square test of marginal homogeneity: p = 0.026, Cramer’s coefficient of effect size: Φ = 0.214). No significant association was found between pre-existing diabetes and ICI-related myocarditis reporting (McNemar’s test of marginal homogeneity: p = 0.752). These findings offer an invitation for future prospective pharmacoepidemiological studies to assess the causal relationship between pre-existing CV conditions and myocarditis onset in a cohort of cancer patients followed during ICI treatment.

Interactions between ocular and systemic disease using national register-based data in the Danish Excellence Centre in Ophthalmic Epidemiology (DECODE-EYE): study perspective

PURPOSE

The Danish Excellence Centre in Ophthalmic Epidemiology (DECODE-EYE) is a national research collaboration formed in order to study the real-life interaction between ocular and systemic disease based on the entire Danish population. Here, we aim to describe the study design and the methodology, which will be used.

METHODS

We will extract data from various healthcare registers and databases including the Danish Civil Registration System (unique personal identifier), the Danish National Patient Register (inpatient and outpatient visits), the Danish National Prescription Registry (redeemed prescription drugs), the National Health Service Register (data on health services in primary health care), the Danish Register of Cause of Death (data on cause of death), Statistics Denmark (demographic and socioeconomic data), the Danish Registry of Diabetic Retinopathy (level of diabetic retinopathy (DR) in diabetes patients) and the database of the Danish Association of the Blind (date and cause of blindness). Relevant registers will be linked by the unique personal identifier, and associations will be examined cross-sectional and/or longitudinally, in principle in 1:5 age- and gender-matched case-control cohort studies.

CONCLUSION

Denmark has a strong tradition in register-based healthcare research, given a high number of validated national registers and databases. DECODE-EYE will provide Danish, large-scale data on associations between ocular and systemic disease. With a target population of 5.8 million individuals, twelve separate studies (Protocols A-L) have initially been designed to be studied in the upcoming years. These will provide novel data on interactions between systemic disease and relevant ophthalmological end-points like blindness, DR, glaucoma, corneal disease, retinal vascular disease, cataract and intravitreal angiostatic treatment.