The Reporting of a Disproportionality Analysis for Drug Safety Signal Detection Using Individual Case Safety Reports in PharmacoVigilance (READUS-PV): Development and Statement.

BACKGROUND AND AIM: Disproportionality analyses using reports of suspected adverse drug reactions are the most commonly used quantitative methods for detecting safety signals in pharmacovigilance. However, their methods and results are generally poorly reported in published articles and existing guidelines do not capture the specific features of disproportionality analyses. We here describe the development of a guideline (REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance [READUS-PV]) for reporting the results of disproportionality analyses in articles and abstracts. METHODS: We established a group of 34 international experts from universities, the pharmaceutical industry, and regulatory agencies, with expertise in pharmacovigilance, disproportionality analyses, and assessment of safety signals. We followed a three-step process to develop the checklist: (1) an open-text survey to generate a first list of items; (2) an online Delphi method to select and rephrase the most important items; (3) a final online consensus meeting. RESULTS: Among the panel members, 33 experts responded to round 1 and 30 to round 2 of the Delphi and 25 participated to the consensus meeting. Overall, 60 recommendations for the main body of the manuscript and 13 recommendations for the abstracts were retained by participants after the Delphi method. After merging of some items together and the online consensus meeting, the READUS-PV guidelines comprise a checklist of 32 recommendations, in 14 items, for the reporting of disproportionality analyses in the main body text and four items, comprising 12 recommendations, for abstracts. CONCLUSIONS: The READUS-PV guidelines will support authors, editors, peer-reviewers, and users of disproportionality analyses using individual case safety report databases. Adopting these guidelines will lead to more transparent, comprehensive, and accurate reporting and interpretation of disproportionality analyses, facilitating the integration with other sources of evidence.

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.

A Model for Monitoring Spontaneously Reported Medication Errors Using the Adjuvanted Recombinant Zoster Vaccine as an Example.

A European legislation was put in place for the reporting of medication errors, and guidelines were drafted to help stakeholders in the reporting, evaluation, and, ultimately, minimization of these errors. As part of pharmacovigilance reporting, a proper classification of medication errors is needed. However, this process can be tedious, time-consuming, and resource-intensive. To fulfill this obligation regarding medication errors, we developed an algorithm that classifies the reported errors in an automated way into four categories: potential medication errors, intercepted medication errors, medication errors without harm (i.e., not associated with adverse reaction(s)), and medication errors with harm (i.e., associated with adverse reaction(s)). A fifth category ("conflicting category") was created for reported cases that could not be unambiguously classified as either potential or intercepted medication errors. Our algorithm defines medication error categories based on internationally accepted terminology using the Medical Dictionary for Regulatory Activities (MedDRA®) preferred terms. We present the algorithm and the strengths of this automated way of reporting medication errors. We also give examples of visualizations using spontaneously reported vaccination error data associated with the adjuvanted recombinant zoster vaccine. For this purpose, we used a customized web-based platform that uses visualizations to support safety signal detection. The use of the algorithm facilitates and ensures a consistent way of categorizing medication errors with MedDRA® terms, thereby saving time and resources and avoiding the risk of potential mistakes versus manual classification. This allows further assessment and potential prevention of medication errors. In addition, the algorithm is easy to implement and can be used to categorize medication errors from different databases.

Finding Needles in the Haystack: Clinical Utility Score for Prioritisation (CUSP), an Automated Approach for Identifying Spontaneous Reports with the Highest Clinical Utility.

INTRODUCTION: Spontaneous reporting of adverse events has increased steadily over the past decades, and although this trend has contributed to improving post-marketing surveillance pharmacovigilance activities, the consequent amount of data generated is challenging to manually review during assessment, with each individual report requiring review by pharmacovigilance experts. This highlights a clear need for alternative or complementary methodologies to help prioritise review. OBJECTIVE: Here, we aimed to develop and test an automated methodology, the Clinical Utility Score for Prioritisation (CUSP), to assist pharmacovigilance experts in prioritising clinical assessment of safety data to improve the rapidity of case series review when case volumes are large. METHODS: The CUSP method was tested on a reference dataset of individual case safety reports (ICSRs) associated to five drug-event pairs that led to labelling changes. The selected drug-event pairs were of varying characteristics across the portfolio of GSK's products. RESULTS: The mean CUSP score for 'key cases' and 'cases of low utility' was 19.7 (median: 21; range: 7-27) and 17.3 (median: 19; range: 4-27), respectively. CUSP distribution for 'key cases' were skewed toward the higher range of scores compared with 'all cases'. The overall performance across each individual drug-event pair varied considerably, showing higher predictive power for 'key cases' for three of the drug-event pairs (average CUSP between these three: 22.8; range: 22.5-23.0) and lesser power for the remaining two (average CUSP between these two: 17.6; range: 14.5-20.7). CONCLUSION: Although several tools have been developed to assess ICSR completeness and regulatory utility, this is the first attempt to successfully develop an automated clinical utility scoring system that can support the prioritisation of ICSRs for clinical review.

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.

Post-Marketing Safety Surveillance for the Adjuvanted Recombinant Zoster Vaccine: Methodology.

A diligent, systematic, regular review of aggregate safety data is essential, particularly early after vaccine introduction, as this is when safety signals not identified during clinical development may emerge. In October 2017, the US Centers for Disease Control and Prevention Advisory Committee on Immunization Practices recommended the adjuvanted recombinant zoster vaccine (RZV; Shingrix, GSK) as the preferred vaccine for preventing herpes zoster (HZ) and related complications in immunocompetent adults aged ≥ 50 years. Subsequently, GSK experienced an unprecedented high demand for RZV. In this methodology paper, we summarize the enhanced measures undertaken to assess RZV safety during its early post-marketing experience in the USA, Canada and Germany. In addition to the routine signal-detection methods already in place for all vaccines, GSK established tailored and enhanced safety monitoring for RZV based on aggregate data of spontaneous reports and manufacturing data. Proactive, near real-time detection and evaluation of signals was a key objective. A dedicated in-house signal-detection tool customized for RZV was employed on a weekly (rather than the routine monthly) basis, allowing for a centralized, more frequent review of data on a single web-based platform. We also identified the background incidence rates of preselected medical events of interest in the first countries to introduce RZV (USA, Canada and Germany) to perform observed-to-expected analyses. This approach may offer a solution to the challenges associated with the assessment and monitoring of vaccine safety in an efficient and timely manner in the context of high vaccine uptake.

ADVANCE system testing: Estimating the incidence of adverse events following pertussis vaccination in healthcare databases with incomplete exposure data.

The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid vaccine benefit-risk monitoring using existing European healthcare databases. Incidence rate (IR) estimates of vaccination-associated adverse events that are needed to model vaccination risks can be calculated from existing healthcare databases when vaccination (exposure) data are available. We assessed different methods to derive IRs in risk periods following vaccination when exposure data are missing in one database, using estimated IRs and IRRs from other databases for febrile seizures, fever and persistent crying. IRs were estimated for children aged 0-5 years in outcome-specific risk and non-risk periods following the first dose of acellular pertussis (aP) vaccination in four primary care databases and one hospital database. We compared derived and observed IRs in each database using three methods: 1) multiplication of non-risk period IR for database i by IR ratio (IRR) obtained from meta-analysis of IRRs estimated using the self-controlled case-series method, from databases other than i; 2) same method as 1, but multiplying with background IR; and 3) meta-analyses of observed IRs from databases other than i. IRs for febrile seizures were lower in primary care databases than the hospital database. The derived IR for febrile seizures using data from primary care databases was lower than that observed in the hospital database, and using data from the hospital database gave a higher derived IR than that observed in the primary care database. For fever and persistent crying the opposite was observed. We demonstrated that missing IRs for a post-vaccination period can be derived but that the type of database and the method of event data capture can have an impact on potential bias. We recommend IRs are derived using data from similar database types (hospital or primary care) with caution as even this can give heterogeneous results.

ADVANCE system testing: Can safety studies be conducted using electronic healthcare data? An example using pertussis vaccination.

INTRODUCTION: The Accelerated Development of Vaccine benefit-risk Collaboration in Europe (ADVANCE) public-private collaboration, aimed to develop and test a system for rapid benefit-risk monitoring of vaccines using healthcare databases in Europe. The objective of this proof-of-concept (POC) study was to test the feasibility of the ADVANCE system to generate incidence rates (IRs) per 1000 person-years and incidence rate ratios (IRRs) for risks associated with whole cell- (wP) and acellular- (aP) pertussis vaccines, occurring in event-specific risk windows in children prior to their pre-school-entry booster. METHODS: The study population comprised almost 5.1 million children aged 1 month to <6 years vaccinated with wP or aP vaccines during the study period from 1 January 1990 to 31 December 2015. Data from two Danish hospital (H) databases (AUH and SSI) and five primary care (PC) databases from, UK (THIN and RCGP RSC), Spain (SIDIAP and BIFAP) and Italy (Pedianet) were analysed. Database-specific IRRs between risk vs. non-risk periods were estimated in a self-controlled case series study and pooled using random-effects meta-analyses. RESULTS: The overall IRs were: fever, 58.2 (95% CI: 58.1; 58.3), 96.9 (96.7; 97.1) for PC DBs and 8.56 (8.5; 8.6) for H DBs; convulsions, 7.6 (95% CI: 7.6; 7.7), 3.55 (3.5; 3.6) for PC and 12.87 (12.8; 13) for H; persistent crying, 3.9 (95% CI: 3.8; 3.9) for PC, injection-site reactions, 2.2 (95% CI 2.1; 2.2) for PC, hypotonic hypo-responsive episode (HHE), 0.4 (95% CI: 0.4; 0.4), 0.6 (0.6; 0.6) for PC and 0.2 (0.2; 0.3) for H; and somnolence: 0.3 (95% CI: 0.3; 0.3) for PC. The pooled IRRs for persistent crying, fever, and ISR, adjusted for age and healthy vaccinee period were higher after wP vs. aP vaccination, and lower for convulsions, for all doses. The IRR for HHE was slightly lower for wP than aP, while wP was associated with somnolence only for dose 1 and dose 3 compared with aP. CONCLUSIONS: The estimated IRs and IRRs were comparable with published data, therefore demonstrating that the ADVANCE system was able to combine several European healthcare databases to assess vaccine safety data for wP and aP vaccination.

Review of the initial post-marketing safety surveillance for the recombinant zoster vaccine.

BACKGROUND: The adjuvanted recombinant zoster vaccine (RZV) received its first marketing authorization in October 2017, for prevention of herpes zoster in individuals aged ≥50 years. METHODS: We summarized safety information, following RZV administration, received by GSK via spontaneous adverse event (AE) reports submitted by healthcare providers, vaccine recipients and other reporters. Observed-to-expected (O/E) analyses were performed for selected outcomes: reports of death, Guillain-Barré syndrome and Bell's palsy. Standard case definitions were used to assess individual case reports. Data mining, using proportional reporting ratio and time-to-onset signal detection methods, was employed to identify RZV-AE pairs with disproportionate reporting or unexpected time-to-onset distribution. RESULTS: Between October 13, 2017 and February 10, 2019, an estimated 9.3 million doses were distributed and GSK received 15,638 spontaneous AE reports involving RZV. Most reports were classified as non-serious (95.3%) and originated from the United States (81.7%), where the majority of doses were distributed. Among reports with age or sex reported, individuals were mainly 50-69-year-olds (62.1%) and female (66.7%). Of all reports, 3,579 (22.9%) described vaccination errors, of which 82.7% were without associated symptoms. Of all vaccination error reports, most described errors of vaccine preparation and reconstitution (29.7%), inappropriate schedule or incomplete course of administration (26.7%), incorrect route of administration (16.4%), and storage errors (12.9%). The most commonly reported symptoms were consistent with the known RZV reactogenicity profile observed in clinical trials, including injection site reactions, pyrexia, chills, fatigue, headache. O/E analyses for selected outcomes and data mining analyses for all reported AEs did not identify any unexpected patterns. CONCLUSIONS: Review of the initial data from the post-marketing safety surveillance showed that the safety profile of RZV is consistent with that previously observed in pre-licensure clinical trials. Other studies are ongoing and planned, to continue generating real-world safety data and further characterize RZV.

Tree-based scan statistic - Application in manufacturing-related safety signal detection.

BACKGROUND AND OBJECTIVES: Over the last decades, medicinal regulations have been put into place and have considerably improved manufacturing practices. Nevertheless, safety issues may still arise. Using the simulation described in this manuscript, our aim is to develop adequate detection methods for manufacturing-related safety signals, especially in the context of biological products. METHODS: Pharmaceutical companies record the entire batch genealogies, from seed batches over intermediates to final product (FP) batches. We constructed a hierarchical tree based on this genealogy information and linked it to the spontaneous safety data available for the FP batch numbers. The tree-based scan statistic (TBSS) was used on simulated data as a proof of concept to locate the source that may have subsequently generated an excess of specific adverse events (AEs) within the manufacturing steps, and to evaluate the method's adjustment for multiple testing. All calculations were performed with a customized program in SAS v9.2. RESULTS: The TBSS generated a close to expected number of false positive signals, demonstrating that it adjusted for multiple testing. Overall, the method detected 71% of the simulated signals at the correct production step when a 6-fold increase in reports with AEs of interest (AEOI) was applied, and 31% when a 2-fold increase was applied. The relatively low detection performance may be attributed to the higher granularity associated with the lower levels of the hierarchy, leading to a lack of power and the stringent definition criteria that were applied for a true positive result. CONCLUSION: As a data-mining method for manufacturing-related safety signal detection, the TBSS may provide advantages over other disproportionality analyses (using batch information) but may benefit from complementary methods (not relaying on batch information). While the method warrants further refinement, it may improve safety signal detection and contribute to improvements in the quality of manufacturing processes.

Investigating Reports of Complex Regional Pain Syndrome: An Analysis of HPV-16/18-Adjuvanted Vaccine Post-Licensure Data.

Complex regional pain syndrome (CRPS) is a chronic pain disorder that typically follows trauma or surgery. Suspected CRPS reported after vaccination with human papillomavirus (HPV) vaccines led to temporary suspension of proactive recommendation of HPV vaccination in Japan. We investigated the potential CRPS signal in relation to HPV-16/18-adjuvanted vaccine (Cervarix®) by database review of CRPS cases with independent expert confirmation; a disproportionality analysis and analyses of temporality; an observed versus expected analysis using published background incidence rates; systematic reviews of aggregate safety data, and a literature review. The analysis included 17 case reports of CRPS: 10 from Japan (0.14/100,000 doses distributed) and seven from the United Kingdom (0.08/100,000). Five cases were considered by independent experts to be confirmed CRPS. Quantitative analyses did not suggest an association between CRPS and HPV-16/18-adjuvanted vaccine. Observed CRPS incidence after HPV-16/18 vaccination was statistically significantly below expected rates. Systematic database reviews using search terms varying in specificity and sensitivity did not identify new cases. No CRPS was reported during clinical development and no unexpected results found in the literature. There is not sufficient evidence to suggest an increased risk of developing CRPS following vaccination with HPV-16/18-adjuvanted vaccine. Post-licensure safety surveillance confirms the acceptable benefit-risk of HPV-16/18 vaccination.

Post-marketing monitoring of intussusception after rotavirus vaccination in Japan.

PURPOSE: Rotarix(TM) was launched in November 2011 in Japan to prevent rotavirus gastroenteritis. Some studies suggest that Rotarix(TM) may have a temporal association with a risk of intussusception (IS). We assessed a possible association between IS and Rotarix(TM) vaccination in Japan. METHODS: All IS cases spontaneously reported post-vaccination (Brighton collaboration levels 1, 2, and 3) were extracted from the GlaxoSmithKline spontaneous report database on the 11th of January 2013. Expected numbers of IS cases were estimated using the number of vaccine doses distributed and the Japanese incidence rate of IS stratified by month of age. The observed versus expected analysis considered the IS cases for each risk period (7 and 30 days post-vaccination) and for each vaccine dose (two doses). RESULTS: Before January 2013, approximately 601 000 Rotarix(TM) doses were distributed in Japan. For a risk period of 7 days post-dose 1 and post-dose 2, 10 and five IS cases were observed, whereas 3.4 and 7.6 were expected, providing an observed-to-expected ratio of 2.96 (95% confidence interval [CI]: 1.42; 5.45) and 0.66 (95% CI: 0.21; 1.53), respectively. For a risk period of 30 days post-dose 1 and post-dose 2, 14 and eight cases were observed, whereas 14.5 and 32.7 were expected, providing an observed-to-expected ratio of 0.97 (95% CI: 0.53; 1.62) and 0.24 (95% CI: 0.11; 0.48), respectively. CONCLUSION: A statistically significant excess of IS cases was observed within 7 days post-dose 1, but not post-dose 2. These results are consistent with previous observations in large post-marketing safety studies in other world regions.