An Evaluation of Postmarketing Reports with an Outcome of Death in the US FDA Adverse Event Reporting System

Causality Assessment Between Drugs and Fatal Cerebral Haemorrhage Using Electronic Medical Records: Comparative Evaluation of Disease-Specific and Conventional Methods

INTRODUCTION

A new algorithm for causality assessment of drugs and fatal cerebral haemorrhage (ACAD-FCH) was published in 2021. However, its use in clinical practice has not been verified.

OBJECTIVES

This study aimed to explore the practical value of the ACAD-FCH when applying information available in clinical practice.

METHODS

The medical records of patients who died at the University of Tokyo Hospital in 2020 were reviewed, and cases with intracranial haemorrhage were selected. Two evaluators independently assessed these cases using three methods (the ACAD-FCH, Naranjo algorithm, and WHO-UMC scale). The number of 'Yes', 'No', and 'No information/Do not know' responses to each question by both evaluators were summed and compared. Inter-rater reliability was evaluated for each method using agreement rates and kappa coefficients with 95% confidence intervals (CI).

RESULTS

Among 316 deaths, 24 cases with intracranial haemorrhage were evaluated. The proportion of ‛No information/Do not know' responses for each question was 35.6% (95% CI 31.4-40.6%) for the ACAD-FCH and 66.9% (95% CI 62.5-71.1%) for the Naranjo algorithm. The respective agreement rates and kappa coefficients were 0.917 (0.798-1.00) and 0.867 (0.675-1.00) for the ACAD-FCH, 0.708 (0.512-0.904) and 0.139 (-0.236 to 0.513) for the Naranjo algorithm, and 0.50 (0.284-0.716) and 0.326 (0.110-0.541) for the WHO-UMC scale, respectively.

CONCLUSION

Our findings suggest the utility of the ACAD-FCH when assessing death cases with intracranial haemorrhage. However, larger studies including intra-rater assessments are warranted for further validation of this algorithm.

Characterization of Pediatric Reports in the US Food and Drug Administration Adverse Event Reporting System from 2010-2020: A Cross-Sectional Study

INTRODUCTION

The Food and Drug Administration Adverse Event Reporting System (FAERS) is a database of adverse event (AE) and medication error reports for drugs and therapeutic biologics. Examining trends of reported individual case safety reports (ICSRs) provides context for evaluating safety concerns.

OBJECTIVE

Characterize pediatric FAERS ICSRs and compare trends (1) to adult reports; (2) within pediatric subgroups.

METHODS

This cross-sectional study examined FAERS ICSRs received between January 1, 2010, through December 31, 2020. Stratified age bands were neonates, infants, younger children, older children, adolescents, and adults. We characterized groups by patient demographic information, suspect products, AEs, and reporter type.

RESULTS

From 2010 to 2020, there were 11,258,995 FAERS ICSRs; 3.1% described pediatric patients. Compared to adults, pediatric ICSRs had higher proportions of all serious outcomes except death. Within pediatric subgroups, neonates had the highest proportions of serious outcomes (96.2%) compared to infants, younger children, older children, and adolescents (79.8%, 67.9%, 59.5%, and 52.7%, respectively). Younger pediatric age groups were more likely to have weight information than older age groups but were less likely to include gender information. The most frequently reported AE was off label use for pediatrics and drug ineffective for adults. Products and AEs reported also differed among pediatric subgroups. Neonates, infants, and adolescents had entirely distinct sets of top five product-event combinations.

CONCLUSION

Pediatric ICSRs represent a minority of FAERS reports but have distinctly different attributes relative to adult ICSRs. Reporting trends also vary within pediatric subgroups, which highlights the need for unique considerations for pediatric safety surveillance.

Alprazolam-related deaths in Scotland, 2004-2020

BACKGROUND

The benzodiazepine drug alprazolam, a fast-acting tranquiliser, cannot be prescribed on the National Health Service in the United Kingdom. Illicit alprazolam supply and consumption have increased. Concern about increasing numbers of alprazolam-related fatalities started circulating in 2018. However, statistics on this issue are very limited. This study examined patterns in such mortality in Scotland.

METHODS

Statistics on deaths where alprazolam was mentioned in the 'cause of death' were obtained from official mortality registers. Anonymised Scottish case-level data were obtained. Data were examined in respect of the characteristics of decedents and deaths using descriptive statistics.

RESULTS

Scotland registered 370 deaths in 2004-2020; 366 of these occurred in 2015-2020: most involved males (77.1%); mean age 39.0 (SD 12.6) years. The principal underlying cause of death was accidental poisoning: opiates/opioids (77.9%); sedatives/hypnotics (15.0%). Two deaths involved alprazolam alone. Main drug groups implicated: opiates/opioids (94.8%), 'other benzodiazepines' (67.2%), gabapentinoids (42.9%), stimulants (30.1%), antidepressants (15.0%). Two-thirds (64.2%) involved combinations of central nervous system (CNS) depressants.

DISCUSSION

Alprazolam-related deaths are likely due to an increasing illicit supply. The fall in deaths in 2019-2020 is partially due to increased use of designer benzodiazepines. Treatment for alprazolam dependence is growing. Clinicians need to be aware of continuing recreational alprazolam use. When such consumption occurs with CNS depressants, overdose and death risks increase.

CONCLUSIONS

More awareness of alprazolam contributing to deaths, especially in conjunction with other CNS depressants, is needed by consumers and clinicians. Improved monitoring of illicit supplies could identify emerging issues of medicines' abuse.

Drug-Related Deaths in China: An Analysis of a Spontaneous Reporting System

Background: Adverse drug reactions with an outcome of death represent the most serious consequences and are inherently important for pharmacovigilance. The nature and characteristics of drug-related deaths are to a large extent unknown in the Chinese population. This study aims to characterize drug-related deaths by analysis of individual case safety reports (ICSRs) with an outcome of death in China.

Methods: The characteristics of death ICSRs were analyzed by descriptive statistics of a large multi-provincial pharmacovigilance database in China.

Results: There were 1,731 ICSRs with an outcome of death, representing 0.95% of all serious cases and 0.05% of all reported ICSRs. Most death ICSRs (78.57%) were reported by medical institutions. Only 16.00% of death ICSRs were reported by manufacturers or distributors. The reporting rate of death ICSRs in the age group of 0–4 years was significantly higher than patients aged 5–64 years. Patients aged over 64 years had the highest reporting rate of death ICSRs. Male patients generally had a higher reporting rate of death ICSRs than female patients. However, the reporting rate of female patients exceeded that of male patients in the age group of 20–34 years. Among 3,861 drugs implicated, ceftriaxone sodium with 146 (3.78%) records of death ranked first. Dexamethasone with 131 (3.39%) records of death ranked second. Qingkailing, an injectable traditional Chinese medicine with 75 (1.94%) records of death, ranked the fifth most frequently implicated medicine.

Conclusion: Young children and elderly patients have a higher risk of drug-related deaths than patients aged 5–64 years. Female patients generally have a lower risk of drug-related deaths than male patients. However, female patients of reproductive age (aged 20–34 years) have a higher risk of drug-related deaths than male patients, hinting that physiological changes and drug uses for child bearing, giving birth, or birth control may significantly increase the risk of death for female patients aged 20–34 years. This paper suggests more research on the safe use of drugs for young children, elderly patients, and female patients of reproductive ages. Pharmacovigilance databases can be valuable resources for comprehensive understanding of drug-related problems.

Privacy-Preserving Anonymity for Periodical Releases of Spontaneous Adverse Drug Event Reporting Data: Algorithm Development and Validation

Background

Spontaneous reporting systems (SRSs) have been increasingly established to collect adverse drug events for fostering adverse drug reaction (ADR) detection and analysis research. SRS data contain personal information, and so their publication requires data anonymization to prevent the disclosure of individuals’ privacy. We have previously proposed a privacy model called MS(k, θ*)-bounding and the associated MS-Anonymization algorithm to fulfill the anonymization of SRS data. In the real world, the SRS data usually are released periodically (eg, FDA Adverse Event Reporting System [FAERS]) to accommodate newly collected adverse drug events. Different anonymized releases of SRS data available to the attacker may thwart our single-release-focus method, that is, MS(k, θ*)-bounding.

Objective

We investigate the privacy threat caused by periodical releases of SRS data and propose anonymization methods to prevent the disclosure of personal privacy information while maintaining the utility of published data.

Methods

We identify potential attacks on periodical releases of SRS data, namely, BFL-attacks, mainly caused by follow-up cases. We present a new privacy model called PPMS(k, θ*)-bounding, and propose the associated PPMS-Anonymization algorithm and 2 improvements: PPMS+-Anonymization and PPMS++-Anonymization. Empirical evaluations were performed using 32 selected FAERS quarter data sets from 2004Q1 to 2011Q4. The performance of the proposed versions of PPMS-Anonymization was inspected against MS-Anonymization from some aspects, including data distortion, measured by normalized information loss; privacy risk of anonymized data, measured by dangerous identity ratio and dangerous sensitivity ratio; and data utility, measured by the bias of signal counting and strength (proportional reporting ratio).

Results

The best version of PPMS-Anonymization, PPMS++-Anonymization, achieves nearly the same quality as MS-Anonymization in both privacy protection and data utility. Overall, PPMS++-Anonymization ensures zero privacy risk on record and attribute linkage, and exhibits 51%-78% and 59%-82% improvements on information loss over PPMS+-Anonymization and PPMS-Anonymization, respectively, and significantly reduces the bias of ADR signal.

Conclusions

The proposed PPMS(k, θ*)-bounding model and PPMS-Anonymization algorithm are effective in anonymizing SRS data sets in the periodical data publishing scenario, preventing the series of releases from disclosing personal sensitive information caused by BFL-attacks while maintaining the data utility for ADR signal detection.

Leveraging Case Narratives to Enhance Patient Age Ascertainment from Adverse Event Reports

INTRODUCTION

Missing age presents a significant challenge when evaluating individual case safety reports (ICSRs) in the FDA Adverse Event Reporting System (FAERS). When age is missing in an ICSR's structured field, it may be in the report's free-text narrative.

OBJECTIVES

This study aimed to evaluate the performance and assess the potential impact of a rule-based natural language processing (NLP) tool that utilizes a text string search to identify patients' numerical age from unstructured narratives.

METHODS

Using FAERS ICSRs from 2002 to 2018, we evaluated the annual proportion of ICSRs with age missing in the structured field before and after NLP application. Reviewers manually identified patients' age from ICSR narratives (gold standard) from a random sample of 1500 ICSRs. The gold standard was compared to the NLP-identified age.

RESULTS

During the study period, the percentage of ICSRs missing age in the structured field increased from 21.9 to 43.8%. The NLP tool performed well among the random sample: sensitivity 98.5%, specificity 92.9%, positive predictive value (PPV) 94.9%, and F-measure 96.7%. It also performed well for the subset of ICSRs missing age in the structured field; when applied to these cases, NLP identified age for an additional one million ICSRs (10% of the total number of ICSRs from 2002 to 2018) and decreased the percentage of ICSRs missing age to 27% overall.

CONCLUSIONS

NLP has potential utility to extract patients' age from ICSR narratives. Use of this tool would enhance pharmacovigilance and research using FAERS data.

Academic collaborations with industry: lessons for the future

Academic centers and industry partners have had love-hate relationships for more than a century. Despite many examples of socially beneficial collaborations between academia and industry, it has become increasingly difficult to find an arrangement where neither clinicians/researchers working with industry nor industry itself is demonized. Regardless, we must incentivize innovation. Preclinical research is primarily funded by the government, whereas 70% of clinical research is supported by industry. Due to external political pressure and industry's concern about lack of control over content, industry's support of continuing medical education (CME) has shrunk to 10% from 40% and has led to diversion of funding to non-CME events. Despite scrutiny of clinical faculty members' interactions with industry, corporate philanthropy is much sought after by academic institutions. Developing new therapeutics requires both academia and industry to transparently and ethically partner with creation of innovative start-ups, sharing of non-proprietary clinical trial data, and in postmarketing surveillance. The search continues for truly symbiotic relationships between academia and industry.

Lessons to be Learnt from Real-World Studies on Immune-Related Adverse Events with Checkpoint Inhibitors: A Clinical Perspective from Pharmacovigilance

The advent of immune checkpoint inhibitors (ICIs) caused a paradigm shift both in drug development and clinical practice; however, by virtue of their mechanism of action, the excessively activated immune system results in a multitude of off-target toxicities, the so-called immune-related adverse events (irAEs), requiring new skills for timely diagnosis and a multidisciplinary approach to successfully manage the patients. In the recent past, a plethora of large-scale pharmacovigilance analyses have characterized various irAEs in terms of spectrum and clinical features in the real world. This review aims to summarize and critically appraise the current landscape of pharmacovigilance studies, thus deriving take-home messages for oncologists. A brief primer to study design, conduction, and data interpretation is also offered. As of February 2020, 30 real-world postmarketing studies have characterized multiple irAEs through international spontaneous reporting systems, namely WHO Vigibase and the US FDA Adverse Event Reporting System. The majority of studies investigated a single irAE and provided new epidemiological evidence about class-specific patterns of irAEs (i.e. anti-cytotoxic T-lymphocyte antigen 4 [CTLA-4] versus anti-programmed cell death 1 [PD-1] receptor, and its ligand [PD-L1]), kinetics of appearance, co-occurrences (overlap) among irAEs, and fatality rate. Oncologists should be aware of both strengths and limitations of these pharmacovigilance analyses, especially in terms of data interpretation. Optimal management (including rechallenge), predictivity of irAEs (as potential biomarkers of effectiveness), and comparative safety of ICIs (also in terms of combination regimens) represent key research priorities for next-generation real-world studies.