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

Tumor lysis syndrome signal with the combination of encorafenib and binimetinib for malignant melanoma: a pharmacovigilance study using data from the FAERS database

Objective

To investigate the potential association between tumor lysis syndrome (TLS) and drugs for the treatment of malignant melanoma (MM).

Methods

Reports of TLS recorded in the FDA Adverse Event Reporting System (FAERS) (January 2004-2023q3) were identified. Demographic and clinical characteristics were described, and disproportionality signals were assessed through the Reporting Odds Ratio (ROR) and Information Component (IC). The latency of TLS with anticancer drugs was described based on parametric models. Subgroup analysis was conducted to explore the differences of TLS signals in different age and sex.

Results

We found 5 (1.49%), 59 (17.61%), 79 (23.58%), 19 (5.67%), 13 (3.88%), 13 (3.88%), 33 (9.85%), 49 (14.63%), 16 (4.78%) TLS reports with pembrolizumab, nivolumab, ipilimumab, dabrafenib, vemurafenib, dacarbazine, "encorafenib and binimetinib", "nivolumab and ipilimumab", "dabrafenib and trametinib", respectively. The combination of encorafenib and binimetinib showed the strongest signal of TLS (IC025 = 3.98). The median days of latency of TLS with combination of encorafenib and binimetinib is 2 days, which was much shorter than nivolumab (22.0 days) and ipilimumab (21.5 days). TLS cases associated with drugs for MM were predominantly recorded in females and aged 25-65 years. After excluding confounding factors such as pre-existing diseases and co-treated drugs, the disproportionate signal of TLS with "encorafenib and binimetinib" remained strong.

Conclusions

Stronger disproportionate signal of TLS was detected in MM patients using the combination of encorafenib and binimetinib than other drugs. Further research is needed to investigate the underlying mechanisms and identify patient-related predisposing factors to support safe prescribing of the combination of encorafenib and binimetinib.

Subgroup disproportionality analysis of dementia-related adverse events with sacubitril/valsartan across geographical regions

This study aimed to evaluate the association between sacubitril/valsartan and dementia-related adverse events (AEs) in geographical subpopulations using subgroup disproportionality analysis. Cases from the FDA adverse event reporting system involving patients aged 60 or older with sacubitril/valsartan or angiotensin receptor blockers (ARBs) were analyzed. The adjusted reporting odds ratios (RORs) for dementia-related AEs were calculated for each continent. A total of 61,518 AEs associated with sacubitril/valsartan or ARBs were identified. Among these, 1441 were dementia-related AEs. In Asia, Europe, and Africa, the reporting risk of dementia-related AEs associated with sacubitril/valsartan was lower compared to ARBs (adjusted ROR, 0.57 [95% CI 0.31-1.01]; adjusted ROR, 0.89 [95% CI 0.69-1.14]; adjusted ROR, 0.40 [95% CI 0.27-0.61], respectively). In Latin America and Oceania, the reporting risk of dementia-related AEs associated with sacubitril/valsartan was similar to that associated with ARBs (adjusted ROR, 1.04 [95% CI 0.75-1.44]; adjusted ROR, 1.02 [95% CI 0.31-3.37], respectively). On the contrary, in North America, the reporting risk associated with sacubitril/valsartan was higher compared to ARBs (adjusted ROR, 1.29 [95% CI 1.10-1.53]). Although the ROR value did not meet the criteria for signal detection, the significantly greater than 1 ROR observed in North America suggests that caution may be warranted regarding potential dementia-related adverse events associated with sacubitril/valsartan.

Antidepressants and fetal death: A systematic review and disproportionality analysis in the WHO safety database (VigiBaseⓇ)

Recent research suggests that fetal exposure to antidepressants (ADs) is significantly associated with fetal death, including stillbirth. However, there has been limited investigation into the timing of AD exposure during pregnancy, the specific effect of each drug, and the possibility of indication bias. To address these gaps in knowledge, we conducted a systematic review of literature and disproportionality analyses using the WHO Safety Database (VigiBaseⓇ). The systematic review provided evidence for increased risks of fetal death with exposure to any selective serotonin reuptake inhibitor (SSRI) at any time of pregnancy, stillbirth with exposure to any AD during the first trimester, and stillbirth with exposure to any SSRI during the first trimester. Disproportionality analyses revealed significant associations with citalopram, clomipramine, paroxetine, sertraline, and venlafaxine. Combining both sets of results, we conclude that exposure to ADs, especially during the first trimester of pregnancy, seems to be associated with fetal mortality, and that ADs with highest placental transfer may be particularly involved. Further research should investigate the links between ADs during early pregnancy and fetal mortality.

The evolving role of disproportionality analysis in pharmacovigilance

INTRODUCTION

From 2009 to 2015, the IMI PROTECT conducted rigorous studies addressing questions about optimal implementation and significance of disproportionality analyses, leading to the development of Good Signal Detection Practices. The ensuing period witnessed the independent exploration of research paths proposed by IMI PROTECT, accumulating valuable experience and insights that have yet to be seamlessly integrated.

AREAS COVERED

This state-of-the-art review integrates IMI PROTECT recommendations with recent acquisitions and evolving challenges. It deals with defining the object of study, disproportionality methods, subgrouping, masking, drug-drug interaction, duplication, expectedness, the debated use of disproportionality results as risk measures, integration with other types of data.

EXPERT OPINION

Despite the ongoing skepticism regarding the usefulness of disproportionality analyses and individual case safety reports, their ability to timely detect safety signals regarding rare and unpredictable adverse reactions remains unparalleled. Moreover, recent exploration into their potential for characterizing safety signals revealed valuable insights concerning potential risk factors and the patient's perspective. To fully realize their potential beyond hypothesis generation and achieve a comprehensive evidence synthesis with other kinds of data and studies, each with their unique limitations and contributions, we need to investigate methods for more transparently communicating disproportionality results and mapping and addressing pharmacovigilance biases.

The REporting of A Disproportionality Analysis for DrUg Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Explanation and Elaboration

In pharmacovigilance, disproportionality analyses based on individual case safety reports are widely used to detect safety signals. Unfortunately, publishing disproportionality analyses lacks specific guidelines, often leading to incomplete and ambiguous reporting, and carries the risk of incorrect conclusions when data are not placed in the correct context. The REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance (READUS-PV) statement was developed to address this issue by promoting transparent and comprehensive reporting of disproportionality studies. While the statement paper explains in greater detail the procedure followed to develop these guidelines, with this explanation paper we present the 14 items retained for READUS-PV guidelines, together with an in-depth explanation of their rationale and bullet points to illustrate their practical implementation. Our primary objective is to foster the adoption of the READUS-PV guidelines among authors, editors, peer reviewers, and readers of disproportionality analyses. Enhancing transparency, completeness, and accuracy of reporting, as well as proper interpretation of their results, READUS-PV guidelines will ultimately facilitate evidence-based decision making in pharmacovigilance.

Detection Algorithms for Simple Two-Group Comparisons Using Spontaneous Reporting Systems

Medical science has often used adult males as the standard to establish pathological conditions, their transitions, diagnostic methods, and treatment methods. However, it has recently become clear that sex differences exist in how risk factors contribute to the same disease, and these differences also exist in the efficacy of the same drug. Furthermore, the elderly and children have lower metabolic functions than adult males, and the results of clinical trials on adult males cannot be directly applied to these patients. Spontaneous reporting systems have become an important source of information for safety assessment, thereby reflecting drugs' actual use in specific populations and clinical settings. However, spontaneous reporting systems only register drug-related adverse events (AEs); thus, they cannot accurately capture the total number of patients using these drugs. Therefore, although various algorithms have been developed to exploit disproportionality and search for AE signals, there is no systematic literature on how to detect AE signals specific to the elderly and children or sex-specific signals. This review describes signal detection using data mining, considering traditional methods and the latest knowledge, and their limitations.

Generalization of Odd Ramos-Louzada generated family of distributions: Properties, characterizations, and applications to diabetes and cancer survival datasets

Probability distributions offer the best description of survival data and as a result, various lifetime models have been proposed. However, some of these survival datasets are not followed or sufficiently fitted by the existing proposed probability distributions. This paper presents a novel Kumaraswamy Odd Ramos-Louzada-G (KumORL-G) family of distributions together with its statistical features, including the quantile function, moments, probability-weighted moments, order statistics, and entropy measures. Some relevant characterizations were obtained using the hazard rate function and the ratio of two truncated moments. In light of the proposed KumORL-G family, a five-parameter sub-model, the Kumaraswamy Odd Ramos-Louzada Burr XII (KumORLBXII) distribution was introduced and its parameters were determined with the maximum likelihood estimation (MLE) technique. Monte Carlo simulation was performed and the numerical results were used to evaluate the MLE technique. The proposed probability distribution's significance and applicability were empirically demonstrated using various complete and censored datasets on the survival times of cancer and diabetes patients. The analytical results showed that the KumORLBXII distribution performed well in practice in comparison to its sub-models and several other competing distributions. The new KumORL-G for diabetes and cancer survival data is found extremely efficient and offers an enhanced and novel technique for modeling survival datasets.

Association of temozolomide with progressive multifocal leukoencephalopathy: a disproportionality analysis integrated with network pharmacology

BACKGROUND

Temozolomide (TMZ) is an alkylating agent approved for the management of glioblastoma. The TMZ is not known for progressive multifocal leukoencephalopathy (PML). The main objective of the current study is to find out the association of TMZ with PML using disproportionality analysis of FDA Adverse Event Reporting System (FAERS) data integrated with network pharmacological approaches.

RESEARCH DESIGN AND METHODS

OpenVigil tool was used to query the FAERS database. The disproportionality measures were calculated. The network has been constructed using Cytoscape. Finally, the possible binding interactions were studied using Glide, Schrödinger Inc.

RESULTS

A total number of 3502 cases of PML were reported in the FAERS database. Out of these, 10 cases were found with TMZ. The subgroup analysis results have shown a greater number of cases in females. The network has indicated the involvement of human mitogen-activated protein kinase, 3-phosphoinositide-dependent protein kinase 1 protein, human mTOR complex protein, phosphatidylinositol 4,5-bisphosphate 3-kinase protein, and glycogen synthase kinase-3 beta protein. The docking results have indicated good interactions of TMZ with active site of glycogen synthase kinase-3 beta and mitogen-activated protein kinase 1 as compared to other identified targets.

CONCLUSION

The PML is identified as novel signal with temozolomide.

Pituitary-Related Adverse Events and Onset Patterns Caused by Immune Checkpoint Inhibitors: Analysis Using the Japanese Adverse Drug Event Report Database

Background and Objectives: One type of immune-related adverse event caused by immune checkpoint inhibitors (ICIs) is pituitary-related adverse events. The management of pituitary-related adverse events is important because they can be fatal if not treated promptly. Therefore, this study was conducted to investigate the onset of pituitary-related adverse events using the Japanese Adverse Drug Report (JADER) database. Materials and Methods: Cases registered in the JADER database from 2004 to 2019 were used. The target drugs were ipilimumab, nivolumab, pembrolizumab, avelumab, atezolizumab, and durvalumab, and the target adverse events were the high-level terms "Anterior pituitary hypofunction," "Anterior pituitary hyperfunction," "Posterior pituitary disorder," and "Pituitary neoplasm" in the Medical Dictionary for Regulatory Activities, Japanese version (MedDRA/J). The information component (IC) was used for signal detection and IC delta (ICΔ) was used for women-related signals. Onset timing and patterns were analyzed using the Weibull distribution. Results: Signals were detected with ipilimumab, nivolumab, pembrolizumab, and atezolizumab in "Anterior pituitary hypofunction," with ICs and 95% credible intervals (95%CrI) of 5.53 (5.30-5.69), 4.96 (4.79-5.08), 4.04 (3.76-4.25), and 2.40 (1.53-3.00). Significant signals were detected in women, except for atezolizumab. Additionally, the time of onset was classified as the wear-out failure type. Inverse signals were detected with ipilimumab and nivolumab in "Posterior pituitary disorder," with ICs (95%CrI) of -1.24 (-2.80--0.26), and -0.89 (-1.64--0.37). Conclusions: Anterior pituitary hypofunction is likely to occur with the long-term administration of ipilimumab, nivolumab, and pembrolizumab. Further investigation is needed to determine the differences in the tendencies to detect signals in the anterior and posterior pituitaries between ipilimumab and nivolumab.

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.

Effect of age on the risk of immune-related adverse events in patients receiving immune checkpoint inhibitors

Identifying patients at increased risk of immune-related adverse events (irAEs) facilitates safe application of immune checkpoint inhibitors (ICIs). This retrospective study aimed to determine the effect of age on the risk of irAEs in patients receiving ICIs and to identify potential mechanisms underlying age-related irAE risk differences. We analyzed reports of FDA Adverse Event Reporting System from July 1, 2014, to September 30, 2021. The information component ratio (ICΔ) was used to compare the irAE risk between older adults (> 65 years) and younger adults (25-65 years), of which the 95% confidential interval lower limit (ICΔ025) exceeding zero indicated significantly increased risk. We found that older adults had a significantly higher overall irAE risk than younger adults (ICΔ025 0.38), which was observed in almost all organ systems. We further analyzed the correlation between age-related irAE risks and age-related transcriptional changes to identify potential genes and pathways underlying age-related irAE risk differences. We found that genes significantly correlated with ICΔ were enriched in processes including extracellular matrix organization, regulation of myeloid leukocyte mediated immunity, and regulation of c-Jun N-terminal kinase (JNK) cascade. In addition, single-cell RNA sequencing analysis confirmed that genes involved in collagen-containing extracellular matrix and JNK cascade were significantly upregulated in myeloid cells from ICI-associated colitis tissues compared with ICI-treated colon tissues without colitis. In conclusion, older adults receiving ICIs have higher irAE risks than younger adults. Upregulation of genes involved in JNK cascade and collagen-containing extracellular matrix in myeloid cells may contribute to increased irAE risks in older adults.

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.

Identifying Safety Subgroups at Risk: Assessing the Agreement Between Statistical Alerting and Patient Subgroup Risk

INTRODUCTION

Identifying individual characteristics or underlying conditions linked to adverse drug reactions (ADRs) can help optimise the benefit-risk ratio for individuals. A systematic evaluation of statistical methods to identify subgroups potentially at risk using spontaneous ADR report datasets is lacking.

OBJECTIVES

In this study, we aimed to assess concordance between subgroup disproportionality scores and European Medicines Agency Pharmacovigilance Risk Assessment Committee (PRAC) discussions of potential subgroup risk.

METHODS

The subgroup disproportionality method described by Sandberg et al., and variants, were applied to statistically screen for subgroups at potential increased risk of ADRs, using data from the US FDA Adverse Event Reporting System (FAERS) cumulative from 2004 to quarter 2 2021. The reference set used to assess concordance was manually extracted from PRAC minutes from 2015 to 2019. Mentions of subgroups presenting potential differentiated risk and overlapping with the Sandberg method were included.

RESULTS

Twenty-seven PRAC subgroup examples representing 1719 subgroup drug-event combinations (DECs) in FAERS were included. Using the Sandberg methodology, 2 of the 27 could be detected (one for age and one for sex). No subgroup examples for pregnancy and underlying condition were detected. With a methodological variant, 14 of 27 examples could be detected.

CONCLUSIONS

We observed low concordance between subgroup disproportionality scores and PRAC discussions of potential subgroup risk. Subgroup analyses performed better for age and sex, while for covariates not well-captured in FAERS, such as underlying condition and pregnancy, additional data sources should be considered.

Statistical methods for exploring spontaneous adverse event reporting databases for drug-host factor interactions

BACKGROUND

Drug toxicity does not affect patients equally; the toxicity may only exert in patients who possess certain attributes of susceptibility to specific drug properties (i.e., drug-host interaction). This concept is crucial for personalized drug safety but remains under-studied, primarily due to methodological challenges and limited data availability. By monitoring a large volume of adverse event reports in the postmarket stage, spontaneous adverse event reporting systems provide an unparalleled resource of information for adverse events and could be utilized to explore risk disparities of specific adverse events by age, sex, and other host factors. However, well-formulated statistical methods to formally address such risk disparities are currently lacking.

METHODS

In this paper, we present a statistical framework to explore spontaneous adverse event reporting databases for drug-host interactions and detect risk disparities in adverse drug events by various host factors, adapting methods for safety signal detection. We proposed four different methods, including likelihood ratio test, normal approximation test, and two tests using subgroup ratios. We applied our proposed methods to simulated data and Food and Drug Administration (FDA) Adverse Event Reporting Systems (FAERS) and explored sex-/age-disparities in reported liver events associated with specific drug classes.

RESULTS

The simulation result demonstrates that two tests (likelihood ratio, normal approximation) can detect disparities in adverse drug events associated with host factors while controlling the family wise error rate. Application to real data on drug liver toxicity shows that the proposed method can be used to detect drugs with unusually high level of disparity regarding a host factor (sex or age) for liver toxicity or to determine whether an adverse event demonstrates a significant unbalance regarding the host factor relative to other events for the drug.

CONCLUSION

Though spontaneous adverse event reporting databases require careful data processing and inference, the sheer size of the databases with diverse data from different countries provides unique resources for exploring various questions for drug safety that are otherwise impossible to address. Our proposed methods can be used to facilitate future investigation on drug-host interactions in drug toxicity using a large number of reported adverse events.

Weight Gain During Antipsychotic Treatment in Children, Adolescents, and Adults: A Disproportionality Analysis in the Global Pharmacovigilance Database, Vigibase®

INTRODUCTION

While antipsychotic-induced weight gain has been widely described in adults, it has yet to be better characterized in children and adolescents.

OBJECTIVE

The aim of this study was to assess antipsychotic-induced weight-gain reporting in children and adolescents as compared to adults, and according to the type of antipsychotic.

METHODS

The study is an observational, case-non-case study using individual case safety reports from the WHO global pharmacovigilance database VigiBase^® from 1 January 2000 to 2 June 2021. Disproportionality in antipsychotic-related weight-gain reporting in children and adolescents compared to adults was evaluated based on reporting odds ratios (RORs) with corresponding 95% confidence intervals (CIs) through multivariate logistic regression modeling. Analysis was adjusted for sex, region of reporting, year of notification, reporter qualification, concomitant use of antidepressants, and use of more than one antipsychotic.

RESULTS

Among 282,224 antipsychotic-related spontaneous reports included in this analysis, we identified 16,881 (6.0%) weight-gain cases. Disproportionality in weight-gain reporting was found in children (adjusted ROR (aROR) 3.6; 95% CI 3.3-3.8) and in adolescents (aROR 2.3; 95% CI 2.2-2.4) compared to adults. Use of risperidone was associated with the highest increase in weight-gain reporting in children (aROR 4.9; 95% CI 3.9-6.1) and adolescents (aROR 3.6; 95% CI 3.1-4.1).

CONCLUSIONS

Compared to adults, weight-gain reporting with antipsychotics was disproportionally higher in the pediatric population, especially in children under 12 years of age. Considering the impact of weight gain on global morbidity and mortality, physicians should closely monitor weight gain in young patients, especially children on risperidone.

Immune Checkpoint Inhibitors and Pregnancy: Analysis of the VigiBase® Spontaneous Reporting System

In pregnancy, immune checkpoint pathways are involved in the maintenance of fetomaternal immune tolerance. Preclinical studies have shown that immune checkpoint inhibitors (ICIs) increase the risk of fetal death. Despite the fact that using ICIs in pregnant women and women of childbearing potential is not recommended, some case reports of ICI exposure in pregnancy have been published showing favorable fetal outcomes. This study aimed to gain further insight into ICI safety in pregnancy by querying VigiBase^®, the World Health Organization's spontaneous reporting system. We performed raw and subgroup disproportionality analyses using the reporting odds ratio and comparing ICIs with the entire database, other antineoplastic agents, and other antineoplastic agents gathered in VigiBase^® since 2011. Across 103 safety reports referring to ICI exposure during the peri-pregnancy period, 56 reported pregnancy-related outcomes, of which 46 were without concomitant drugs as potential confounding factors. No signals of disproportionate reporting were found for spontaneous abortion, fetal growth restriction, and prematurity. In light of the expanding indications of ICIs, continuous surveillance by clinicians and pharmacovigilance experts is warranted, along with pharmacoepidemiological studies on other sources of real-world evidence, such as birth records, to precisely assess ICI exposure during the peri-pregnancy period and further characterize relevant outcomes.

Potential safety signal of pregnancy loss with vascular endothelial growth factor inhibitor intraocular injection: A disproportionality analysis using the Food and Drug Administration Adverse Event Reporting System

Objectives: Intraocular administration of vascular endothelial growth factor (VEGF) inhibitors may be associated with pregnancy loss. However, little is known about intraocular anti-VEGF therapy during pregnancy. Here, we conducted a pharmacovigilance study using a spontaneous reporting database to evaluate the relationship between intraocular VEGF inhibitors and pregnancy loss. Methods: We used the JAPIC AERS database which is composed of the Food and Drug Administration Adverse Event Reporting System (FAERS) dataset preprocessed by the Japan Pharmaceutical Information Center (JAPIC) to investigate the VEGF inhibitors ranibizumab, aflibercept, and bevacizumab. Disproportionality analyses were conducted for VEGF inhibitors and pregnancy loss. The lower limit of the 95% confidence interval (CI) of the reporting odds ratio (ROR) > 1 and a minimum of three reported cases of pregnancy loss were the detection criteria used in the current study. Results: In the FAERS, 19 pregnancy loss cases were reported for ranibizumab with an ROR of 4.44 (95% CI: 2.42-8.16), 6 for intraocular bevacizumab with an ROR of 32.25 (95% CI: 3.88-267.9), and 4 for intraocular aflibercept with an ROR of 5.37 (95% CI: 1.34-21.49). All these drugs met the detection criteria. Conclusion: Potential safety signals of pregnancy loss were obtained from intraocular administration of VEGF inhibitors during pregnancy. These signals should be validated using a causal design study.

Assessing the quality of evidence on safety: specifications for application and suggestions for adaptions of the GRADE-criteria in the context of preparing a list of potentially inappropriate medications for older adults

Background

Systematic reviews that synthesize safety outcomes pose challenges (e.g. rare events), which raise questions for grading the strength of the body of evidence. This is maybe one reason why in many potentially inappropriate medication (PIM) lists the recommendations are not based on formalized systems for assessing the quality of the body of evidence such as GRADE.

In this contribution, we describe specifications and suggest adaptions of the GRADE system for grading the quality of evidence on safety outcomes, which were developed in the context of preparing a PIM-list, namely PRISCUS.

Methods

We systematically assessed each of the five GRADE domains for rating-down (study limitations, imprecision, inconsistency, indirectness, publication bias) and the criteria for rating-up, considering if special considerations or revisions of the original approach were indicated. The result was gathered in a written document and discussed in a group-meeting of five members with various background until consensus. Subsequently, we performed a proof-of-concept application using a convenience sample of systematic reviews and applied the approach to systematic reviews on 19 different clinical questions.

Results

We describe specifications and suggest adaptions for the criteria “study limitations”, imprecision, “publication bias” and “rating-up for large effect”. In addition, we suggest a new criterion to account for data from subgroup-analyses. The proof-of-concept application did not reveal a need for further revision and thus we used the approach for the systematic reviews that were prepared for the PRISCUS-list.

We assessed 51 outcomes. Each of the proposed adaptions was applied. There were neither an excessive number of low and very low ratings, nor an excessive number of high ratings, but the different methodological quality of the safety outcomes appeared to be well reflected.

Conclusion

The suggestions appear to have the potential to overcome some of the challenges when grading the methodological quality of harms and thus may be helpful for producers of evidence syntheses considering safety.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01715-5.

A new statistical approach for modeling the bladder cancer and leukemia patients data sets: Case studies in the medical sector

Statistical methods are frequently used in numerous healthcare and other related sectors. One of the possible applications of the statistical methods is to provide the best description of the data sets in the healthcare sector. Keeping in view the applicability of statistical methods in the medical sector, numerous models have been introduced. In this paper, we also introduce a novel statistical method called, a new modified-G family of distributions. Several mathematical properties of the new modified-G family are derived. Based on the new modified-G method, a new updated version of the Weibull model called, a new modified-Weibull distribution is introduced. Furthermore, the estimators of the parameters of the new modified-G distributions are also obtained. Finally, the applicability of the new modified-Weibull distribution is illustrated by analyzing two medical sets. Using certain analytical tools, it is observed that the new modified-Weibull distribution is the best choice to deal with the medical data sets.

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.

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.

Reporting of Acute Inflammatory Neuropathies with COVID-19 Vaccines: Subgroup Disproportionality Analyses in VigiBase

Since marketing authorization, cases of neuralgic amyotrophy (NA), facial paralysis/Bell’s palsy (FP/BP), and Guillain-Barré syndrome (GBS) were reported with COVID-19 vaccines of different technologies. This study aimed to assess whether NA, FP/BP, and GBS were more frequently reported in VigiBase with COVID-19 vaccines (of any technologies) than with other viral vaccines, over the full database and across potential risk groups by sex and age. The reporting odds ratio (ROR) with 95% confidence interval (95% CI) was used as the measure of disproportionality and subgroup disproportionality analyses were performed by sex and age. Out of 808,906 safety reports with COVID-19 vaccines, 57 (0.01%) reported NA, 3320 (0.4%) FP/BP, and 632 (0.1%) GBS. There were not signals of disproportionate reporting for NA and GBS with COVID-19 vaccines against other viral vaccines. FP/BP was disproportionately more frequently reported with COVID-19 vaccines than with other viral vaccines over the full database (ROR 1.12, 95%CI 1.07–1.17), in males (ROR 1.65, 95%CI 1.54–1.78) and in age subgroups 65–74 years (ROR 1.21, 95%CI 1.05–1.39) and ≥75 years (ROR 1.84, 95%CI 1.52–2.22). Albeit not proving causation, these findings might support clinicians in decision-making for patients potentially at risk for developing an acute inflammatory neuropathy with COVID-19 vaccines.

A meta-epidemiological study found lack of transparency and poor reporting of disproportionality analyses for signal detection in pharmacovigilance databases

OBJECTIVE

To review and appraise methods and reporting characteristics of pharmacovigilance disproportionality analyses.

STUDY DESIGN AND SETTING

We randomly selected 100 disproportionality analyses indexed in Medline found during a systematic literature search. We then extracted and synthetized methodological and reporting characteristics using 7 key items: 1) title transparency; 2) protocol pre-registration; 3) date of data extraction and analysis; 4) outcome, population, exposure and comparator definitions; 5) adjustment and stratification of results; 6) method and threshold for signal detection; 7) secondary and sensitivity analyses.

RESULTS

We found that methods used to generate disproportionality signals were extremely heterogeneous; there were nearly as many unique analyses as studies. The authors used various populations, methods, signal detection thresholds, adjustment or stratification variables, generally without justification for their choice or pre-specification in protocols. Moreover, 78% of studies failed to report methods for case, adverse drug reactions or comparator selection and 32 studies did not define the threshold for signal generation.

CONCLUSION

Our survey raises major concerns regarding all aspects of disproportionality analyses that could lead to misleading results and generate unjustified alarms. We advocate for a strong and transparent rationale for variable selection, choice of population and comparators pre-specified in a protocol and assessed by sensitivity analyses.

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.

Leveraging the Variability of Pharmacovigilance Disproportionality Analyses to Improve Signal Detection Performances

Background: A plethora of methods and models of disproportionality analyses for safety surveillance have been developed to date without consensus nor a gold standard, leading to methodological heterogeneity and substantial variability in results. We hypothesized that this variability is inversely correlated to the robustness of a signal of disproportionate reporting (SDR) and could be used to improve signal detection performances.

Methods: We used a validated reference set containing 399 true and false drug-event pairs and performed, with a frequentist and a Bayesian disproportionality method, seven types of analyses (model) for which the results were very unlikely to be related to actual differences in absolute risks of ADR. We calculated sensitivity, specificity and plotted ROC curves for each model. We then evaluated the predictive capacities of all models and assessed the impact of combining such models with the number of positive SDR for a given drug-event pair through binomial regression models.

Results: We found considerable variability in disproportionality analysis results, both positive and negative SDR could be generated for 60% of all drug-event pairs depending on the model used whatever their truthfulness. Furthermore, using the number of positive SDR for a given drug-event pair largely improved the signal detection performances of all models.

Conclusion: We therefore advocate for the pre-registration of protocols and the presentation of a set of secondary and sensitivity analyses instead of a unique result to avoid selective outcome reporting and because variability in the results may reflect the likelihood of a signal being a true adverse drug reaction.

Adverse Event Reporting with Immune Checkpoint Inhibitors in Older Patients: Age Subgroup Disproportionality Analysis in VigiBase

Simple Summary

Due to the changes that occur with aging in the immune system, older patients represent a subpopulation of concern for immune checkpoint inhibitor toxicity. This pharmacovigilance study aimed to assess whether older patient age (65 years and older) was a risk factor for increased reporting of adverse drug reactions with immune checkpoint inhibitors as compared to other antineoplastic drugs in VigiBase, the World Health Organization global database of spontaneous reporting. Disproportionality analysis by age subgroups (<18 years, 18–64 years, 65–74 years, 75–84 years and ≥85 years) did not highlight older patient age as risk factor for increased reporting of any specific toxicity with immune checkpoint inhibitors as compared to other antineoplastic drugs. A signal of disproportionate reporting emerged for eye disorders with immune checkpoint inhibitors in patients aged 18–64 years, which deserves further investigation aimed at elucidating risk factors and defining management strategies.

Abstract

Older patients represent a subpopulation of concern for immune checkpoint inhibitor (ICI) toxicity because of changes in the aging immune system and the potentially relevant clinical implications for their quality of life. Current evidence on ICI safety in older patients is conflicting. This study aimed to assess whether older patient age was a risk factor for increased reporting with ICIs as compared to other antineoplastic drugs in VigiBase, the World Health Organization database of suspected adverse drug reactions. Disproportionality analyses computing the reporting odds ratios (RORs) were performed by age subgroups (<18 years, 18–64 years, 65–74 years, 75–84 years and ≥85 years). There were not signals of disproportionate reporting with ICIs specifically detected in older patient age subgroups (≥65 years), which were not present in the disproportionality analysis over the entire dataset. A signal of disproportionate reporting with ICIs emerged for eye disorders only in the age subgroup 18–64 years (ROR 1.13, 95% confidence interval 1.05–1.23). These findings showed that adverse event reporting with ICIs in older patients was comparable to that in the overall patient cohort and prompt for the further investigation of eye disorders with ICIs to elucidating risk factors and defining management strategies.

Cyclin-dependent kinase 4/6 inhibitors and interstitial lung disease in the FDA adverse event reporting system: a pharmacovigilance assessment

PURPOSE

We assessed pulmonary toxicity of cyclin-dependent kinase (CDK)4/6 inhibitors by analyzing the publicly available FDA Adverse Event Reporting System (FAERS).

METHODS

Reports of interstitial lung disease (ILD) were characterized in terms of demographic information, including daily dose, latency, concomitant drugs known to be associated with ILD, and causality assessment (adapted WHO system). Disproportionality analyses were carried out by calculating reporting odds ratios (RORs) with 95% confidence interval (CI), accounting for major confounders, including notoriety and competition biases.

RESULTS

ILD reports (N = 161) represented 2.1% and 0.3% of all reports for abemaciclib and palbocilcib/ribociclib, respectively, with negligible proportion of concomitant pneumotoxic drugs. Increased reporting was found for CDK4/6 inhibitors when compared to other drugs (ROR = 1.50; 95%CI = 1.28-1.74), and abemaciclib vs other anticancer agents (4.70; 3.62-5.98). Sensitivity analyses confirmed a strong and consistent disproportionality for abemaciclib. Higher-than-expected reporting emerged for palbociclib (1.38; 1.07-1.77) and ribociclib (2.39; 1.34-3.92) only when removing Japan reports. ILD occurred at recommended daily doses, with median latency ranging from 50 (abemaciclib) to 253 (ribociclib) days. Causality was highly probable in 55% of abemaciclib cases, probable in 68% of palbociclib cases.

CONCLUSIONS

Increased reporting of ILD with CDK4/6 inhibitors calls for further comparative population-based studies to characterize and quantify the actual risk, taking into account drug- and patient-related risk factors. These findings strengthen the role of (a) timely pharmacovigilance to detect post-marketing signals through FAERS and other real-world data, (b) clinicians to assess early, on a case-by-case basis, the potential responsibility of CDK4/6 inhibitors when diagnosing a lung injury.

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.