Tree-temporal scan statistics for safety signal detection in vaccine clinical trials.

The evaluation of safety is critical in all clinical trials. However, the quantitative analysis of safety data in clinical trials poses statistical difficulties because of multiple potentially overlapping endpoints. Tree-temporal scan statistic approaches address this issue and have been widely employed in other data sources, but not to date in clinical trials. We evaluated the performance of three complementary scan statistical methods for routine quantitative safety signal detection: the self-controlled tree-temporal scan (SCTTS), a tree-temporal scan based on group comparison (BGTTS), and a log-rank based tree-temporal scan (LgRTTS). Each method was evaluated using data from two phase III clinical trials, and simulated data (simulation study). In the case study, the reference set was adverse events (AEs) in the Reference Safety Information of the evaluated vaccine. The SCTTS method had higher sensitivity than other methods, and after dose 1 detected 80 true positives (TP) with a positive predictive value (PPV) of 60%. The LgRTTS detected 49 TPs with 69% PPV. The BGTTS had 90% of PPV with 38 TPs. In the simulation study, with simulated reference sets of AEs, the SCTTS method had good sensitivity to detect transient effects. The LgRTTS method showed the best performance for the detection of persistent effects, with high sensitivity and expected probability of type I error. These three methods provide complementary approaches to safety signal detection in clinical trials or across clinical development programmes. All three methods formally adjust for multiple testing of large numbers of overlapping endpoints without being excessively conservative.

The Importance of Frailty in the Assessment of Influenza Vaccine Effectiveness Against Influenza-Related Hospitalization in Elderly People.

Background: Influenza is an important cause of morbidity and mortality among older adults. Even so, effectiveness of influenza vaccine for older adults has been reported to be lower than for younger adults, and the impact of frailty on vaccine effectiveness (VE) and outcomes is uncertain. We aimed to study VE against influenza hospitalization in older adults, focusing on the impact of frailty. Methods: We report VE of trivalent influenza vaccine (TIV) in people ≥65 years of age hospitalized during the 2011-2012 influenza season using a multicenter, prospective, test-negative case-control design. A validated frailty index (FI) was used to measure frailty. Results: Three hundred twenty cases and 564 controls (mean age, 80.6 and 78.7 years, respectively) were enrolled. Cases had higher baseline frailty than controls (P = .006). In the fully adjusted model, VE against influenza hospitalization was 58.0% (95% confidence interval [CI], 34.2%-73.2%). The contribution of frailty was important; adjusting for frailty alone yielded a VE estimate of 58.7% (95% CI, 36.2%-73.2%). VE was 77.6% among nonfrail older adults and declined as frailty increased. Conclusions: Despite commonly held views that VE is poor in older adults, we found that TIV provided good protection against influenza hospitalization in older adults who were not frail, though VE diminished as frailty increased. Clinical Trials Registration: NCT01517191.

Influenza vaccine effectiveness against influenza-related hospitalization during a season with mixed outbreaks of four influenza viruses: a test-negative case-control study in adults in Canada.

BACKGROUND: The Serious Outcomes Surveillance (SOS) Network was established to monitor seasonal influenza complications among hospitalized Canadian adults and to assess the effectiveness of influenza vaccination against severe outcomes. Here we report age- and strain-specific vaccine effectiveness (VE) in preventing severe outcomes during a season characterized by mixed outbreaks of four different influenza strains. METHODS: This prospective, multicentre, test-negative case-control study evaluated the VE of trivalent influenza vaccine (TIV) in the prevention of laboratory-confirmed influenza-hospitalization in adults aged ≥16 years (all adults) and adults aged 16-64 years (younger adults). The SOS Network identified hospitalized patients with diagnoses potentially attributable to influenza during the 2011/12 influenza season. Swabs collected at admission were tested by reverse transcriptase polymerase chain reaction (RT PCR) or viral culture to discriminate influenza cases (positive) from controls (negative). VE was calculated as 1-odds ratio (OR) of vaccination in cases versus controls × 100. RESULTS: Overall, in all adults, the unadjusted and adjusted VEs of TIV against influenza-hospitalization were 41.8% (95% Confidence Interval [CI]: 26.0, 54.3), and 42.8% (95% CI: 23.8, 57.0), respectively. In younger adults (16-64 years), the unadjusted and adjusted VEs of TIV against influenza-hospitalization were 35.8% (95% CI: 4.5, 56.8) and 33.2% (95% CI: -6.7, 58.2), respectively. In the all adults group, adjusted VE against influenza A/H1N1 was 72.5% (95% CI: 30.5, 89.1), against A/H3N2 was 86.1% (95% CI: 40.1, 96.8), against B/Victoria was 40.5% (95% CI: -28.9, 72.6), and against B/Yamagata was 32.3% (95% CI: -8.3, 57.7). The adjusted estimate of early season VE (from November 1 to March 11) was 54.4% (95% CI: 29.7-70.4), which was higher than late season (from March 11 to May 25) VE estimate (VE: 29.7%, 95% CI: -5.3, 53.1). CONCLUSIONS: These results suggest that TIV was highly effective against A viruses and moderately effective against B viruses during a mild season characterised by co-circulation of four influenza strains in Canada. Findings underscore the need to provide VE assessment by subtype/lineage as well as the timing of vaccination (early season vs late season) to accurately evaluate vaccine performance and thus guide public health decision-making. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01517191. Registration was retrospective and the date of registration was January 17, 2012.

Estimates of hospitalization attributable to influenza and RSV in the US during 1997-2009, by age and risk status.

BACKGROUND: Estimates of influenza and respiratory syncytial virus (RSV) burden must be periodically updated to inform public health strategies. We estimated seasonal influenza- and RSV-attributable hospitalizations in the US from 1997 to 2009 according to age and risk status (NCT01599390). METHODS: Multiple linear regression modelling was used to attribute hospitalizations to influenza or RSV using virological surveillance and hospitalization data. Hospitalization data were obtained from the US Nationwide Inpatient Sample and virology data were obtained from FluView (Centers for Disease Control and Prevention). Outcomes included any mention of ICD-coded respiratory disease and cardiorespiratory disease diagnoses. We also explored a broader definition of respiratory disease that included mention of relevant respiratory sign/symptoms and viral infection ("respiratory broad"). RESULTS: Applying the respiratory broad outcome, our model attributed ~300,000 and ~200,000 hospitalizations to influenza and RSV, respectively. Influenza A/H3N2 was the predominant cause of influenza-related hospitalizations in most seasons, except in three seasons when influenza B was dominant; likewise, A/H3N2 caused most influenza-related hospitalizations in all age segments, except in children <18 years where the relative contribution of A/H3N2 and B was similar. Most influenza A- and B-related hospitalizations occurred in seniors while approximately one half and one third of all RSV-related events occurred in children 0-4 years and seniors 65+ years, respectively. High-risk status was associated with higher risk of both influenza- and RSV-attributable hospitalizations in adults, but not in children. CONCLUSIONS: Our study assessed the burden of influenza and RSV, information that is important for both cost effectiveness studies and for prioritization of the development of antivirals and vaccines. For seniors, we found that the burdens of influenza and RSV were both substantial. Among children <18 years, about half of all influenza hospitalizations were due to influenza B, most occurring in children without noted risk conditions. RSV hospitalizations among children were confined to those 0-4 years. Our study also demonstrated the importance of the outcome used to estimate hospitalization burden. Our findings highlight the burden of influenza among children regardless of risk status and underscore the prevalence of RSV infections among both young children and older adults.

Clinical Features of Influenza and Acute Respiratory Illness in Older Adults at Least 50 Years of Age in an Outpatient Setting in the Republic of Korea: a Prospective, Observational, Cohort Study.

Two prospective, multi-centre, observational studies (GlaxoSmithKline [GSK] identifier No. 110938 and 112519) were performed over 2 influenza seasons (2007-2008 and 2008-2009) in the Republic of Korea (ROK) with the aim to evaluate the burden of laboratory-confirmed influenza (LCI) in patients ≥ 50 years of age seeking medical attention for acute respiratory illness (ARI). The median participant age was 58 years in the 2007-2008 season and 60 years in the 2008-2009 season. LCI was observed in 101/346 (29.2%) of ARI patients in the 2007-2008 season and in 166/443 (37.5%) of ARI patients in the 2008-2009 season. Compared to patients with non-influenza ARI, those with LCI had higher rates of decreased daily activities (60.4% vs. 32.9% in 2007-2008 and 46.4% vs. 25.8% in 2008-2009), work absenteeism (51.1% vs. 25.6% and 14.4% vs. 7.7%), and longer duration of illness. These results indicated that influenza is an important cause of ARI in adults aged 50 and older causing more severe illness than non-influenza related ARI.

Model estimates of the burden of outpatient visits attributable to influenza in the United States.

BACKGROUND: Although many studies have modelled the national burdens of hospitalizations and deaths due to influenza, few studies have considered the outpatient burden. To fill this gap for the United States (US), we applied traditional statistical modelling approaches to time series derived from large medical claims databases held in the private sector. METHODS: We accessed ICD-9-coded office visit data extracted from Truven Health Analytics' MarketScan Commercial database covering about one third of the US population <65 years during 2001-2009, and Medicare Supplemental data covering about one fifth of US seniors 65+ during 2006-2009. We extracted weekly time series of visits due to respiratory diagnoses, otitis media (OM), and urinary tract infections (UTI), a "negative control". We used multiple linear regression modelling to estimate age-specific influenza-related excess in office visits. RESULTS: In the <65 year age group, in the 8 pre-pandemic seasons studied and for the broadest defined respiratory outcome, the model attributed an average of ~14.5 M (Standard deviation [SD] across seasons 3.9 million) office visits to influenza (rate of 5,581/100,000 population). Of these, ~80 % of visits occurred in the 5-17 and 18-49 age group. In school children aged 5-17 year olds and adult 18-64 year age groups the majority of visits were due to influenza B, while A/H3N2 explained most visits in children <5 year olds. The model further attributed ~2.2 M OM visits (SD across seasons 790,000) annually to influenza, of which 86 % of these occurred in children <18 years; this indicates that 6.4 % of all infants <2 years and 4.9 % of all toddlers aged 2-4 years in the US have an influenza-attributable outpatient visit with an OM diagnosis. In seniors 65 years and older, our model attributed ~0.7 M (SD across seasons 351,000) respiratory visits to influenza (rate of 1,887/100,000 population). The model identified no significant excess UTI (negative control) visits in most seasons. CONCLUSIONS: This is to our knowledge a first study of the outpatient burden of influenza in the US in a large database. The model estimated that 10 % of all children <18 years and 4 % of the entire population <65 years seek outpatient care for respiratory illness attributable to influenza annually. TRIAL REGISTRATION: ClinicalTrial.gov, NCT02019732 .

Modelling estimates of age-specific influenza-related hospitalisation and mortality in the United Kingdom.

BACKGROUND: Influenza is rarely confirmed with laboratory testing and accurate assessment of the overall burden of influenza is difficult. We used statistical modelling methods to generate updated, granular estimates of the number/rate of influenza-attributable hospitalisations and deaths in the United Kingdom. Such data are needed on a continuing basis to inform on cost-benefit analyses of treatment interventions, including vaccination. METHODS: Weekly age specific data on hospital admissions (1997-2009) and on deaths (1997-2009) were obtained from national databases. Virology reports (1996-2009) of influenza and respiratory syncytial virus detections were provided by Public Health England. We used an expanded set of ICD-codes to estimate the burden of illness attributable to influenza which we refer to as 'respiratory disease broadly defined'. These codes were chosen to optimise the balance between sensitivity and specificity. A multiple linear regression model controlled for respiratory syncytial virus circulation, with stratification by age and the presence of comorbid risk status (conditions associated with severe influenza outcomes). RESULTS: In the United Kingdom there were 28,516 hospitalisations and 7163 deaths estimated to be attributable to influenza respiratory disease in a mean season, with marked variability between seasons. The highest incidence rates of influenza-attributable hospitalisations and deaths were observed in adults aged 75+ years (252/100,000 and 131/100,000 population, respectively). Influenza B hospitalisations were highest among 5-17 year olds (12/100,000 population). Of all estimated influenza respiratory deaths in 75+ year olds, 50 % occurred out of hospital, and 25 % in 50-64 year olds. Rates of hospitalisations and death due to influenza-attributable respiratory disease were increased in adults identified as at-risk. CONCLUSIONS: Our study points to a substantial but highly variable seasonal influenza burden in all age groups, particularly affecting 75+ year olds. Effective influenza prevention or early intervention with anti-viral treatment in this age group may substantially impact the disease burden and associated healthcare costs. The high burden of influenza B hospitalisation among 5-17 year olds supports current United Kingdom vaccine policy to extend quadrivalent seasonal influenza vaccination to this age group. TRIAL REGISTRATION: ClinicalTrial.gov, NCT01520935.

Modelling estimates of the burden of Respiratory Syncytial virus infection in adults and the elderly in the United Kingdom.

BACKGROUND: Growing evidence suggests respiratory syncytial virus (RSV) is an important cause of respiratory disease in adults. However, the adult burden remains largely uncharacterized as most RSV studies focus on children, and population-based studies with laboratory-confirmation of infection are difficult to implement. Indirect modelling methods, long used for influenza, can further our understanding of RSV burden by circumventing some limitations of traditional surveillance studies that rely on direct linkage of individual-level exposure and outcome data. METHODS: Multiple linear time-series regression was used to estimate RSV burden in the United Kingdom (UK) between 1995 and 2009 among the total population and adults in terms of general practice (GP) episodes (counted as first consultation ≥28 days following any previous consultation for same diagnosis/diagnostic group), hospitalisations, and deaths for respiratory disease, using data from Public Health England weekly influenza/RSV surveillance, Clinical Practice Research Datalink, Hospital Episode Statistics, and Office of National Statistics. The main outcome considered all ICD-listed respiratory diseases and, for GP episodes, related symptoms. Estimates were adjusted for non-specific seasonal drivers of disease using secular cyclical terms and stratified by age and risk group (according to chronic conditions indicating severe influenza risk as per UK recommendations for influenza vaccination). Trial registration NCT01706302 . Registered 11 October 2012. RESULTS: Among adults aged 18+ years an estimated 487,247 GP episodes, 17,799 hospitalisations, and 8,482 deaths were attributable to RSV per average season. Of these, 175,070 GP episodes (36 %), 14,039 hospitalisations (79 %) and 7,915 deaths (93 %) were in persons aged 65+ years. High- versus low-risk elderly were two-fold more likely to have a RSV-related GP episode or death and four-fold more likely be hospitalised for RSV. In most seasons since 2001, more GP episodes, hospitalisations and deaths were attributable to RSV in adults than to influenza. CONCLUSION: RSV is associated with a substantial disease burden in adults comparable to influenza, with most of the hospitalisation and mortality burden in the elderly. Treatment options and measures to prevent RSV could have a major impact on the burden of RSV respiratory disease in adults, especially the elderly.

The epidemiology of herpes zoster and its complications in Medicare cancer patients.

BACKGROUND: Literature on the epidemiology of herpes zoster (HZ) in cancer patients is sparse and does not include the elderly. The objectives of this study were to determine the incidence of HZ and related complications in elderly cancer patients and assess risk factors associated with HZ. METHODS: Patients ≥65 years diagnosed with cancer in 1991-2007 were identified from the Surveillance, Epidemiology, and End Results (SEER) cancer registry-Medicare linked database in this retrospective, longitudinal, open cohort study. The observation period spanned from first cancer diagnosis until the end of data availability. A random group of non-cancer Medicare patients served as the comparison group. Cases of HZ and related complications were ascertained from medical claims. Incidence rates (IR) and adjusted IR ratios were reported. RESULTS: The study population consisted of 82,832 hematologic (HEM) and 944,777 solid cancer patients (SOLID). During follow-up, 9.2% of HEM and 6.3% of SOLID were diagnosed with HZ. The IR of HZ was significantly higher in HEM than SOLID (31.0 vs. 14.9 per 1,000 patient-years, p <0.01). The adjusted IR ratio vs. non-cancer elderly patients was 2.4 in HEM and 1.2 in SOLID. The proportion of patients with complications was higher in HEM than SOLID (17.8% vs. 15.8%, p <0.01). Age, gender, race, certain cancer therapies, and immunosuppression were HZ risk factors. CONCLUSIONS: Elderly cancer patients run a 1.2-2.4 times higher risk of developing HZ than those without cancer. The rates of HZ and HZ-related complications are significantly higher for hematologic than solid cancer patients.

Optimizing Signal Management in a Vaccine Adverse Event Reporting System: A Proof-of-Concept with COVID-19 Vaccines Using Signs, Symptoms, and Natural Language Processing.

INTRODUCTION: The Vaccine Adverse Event Reporting System (VAERS) has already been challenged by an extreme increase in the number of individual case safety reports (ICSRs) after the market introduction of coronavirus disease 2019 (COVID-19) vaccines. Evidence from scientific literature suggests that when there is an extreme increase in the number of ICSRs recorded in spontaneous reporting databases (such as the VAERS), an accompanying increase in the number of disproportionality signals (sometimes referred to as 'statistical alerts') generated is expected. OBJECTIVES: The objective of this study was to develop a natural language processing (NLP)-based approach to optimize signal management by excluding disproportionality signals related to listed adverse events following immunization (AEFIs). COVID-19 vaccines were used as a proof-of-concept. METHODS: The VAERS was used as a data source, and the Finding Associated Concepts with Text Analysis (FACTA+) was used to extract signs and symptoms of listed AEFIs from MEDLINE for COVID-19 vaccines. Disproportionality analyses were conducted according to guidelines and recommendations provided by the US Centers for Disease Control and Prevention. By using signs and symptoms of listed AEFIs, we computed the proportion of disproportionality signals dismissed for COVID-19 vaccines using this approach. Nine NLP techniques, including Generative Pre-Trained Transformer 3.5 (GPT-3.5), were used to automatically retrieve Medical Dictionary for Regulatory Activities Preferred Terms (MedDRA PTs) from signs and symptoms extracted from FACTA+. RESULTS: Overall, 17% of disproportionality signals for COVID-19 vaccines were dismissed as they reported signs and symptoms of listed AEFIs. Eight of nine NLP techniques used to automatically retrieve MedDRA PTs from signs and symptoms extracted from FACTA+ showed suboptimal performance. GPT-3.5 achieved an accuracy of 78% in correctly assigning MedDRA PTs. CONCLUSION: Our approach reduced the need for manual exclusion of disproportionality signals related to listed AEFIs and may lead to better optimization of time and resources in signal management.

Developing an Artificial Intelligence-Guided Signal Detection in the Food and Drug Administration Adverse Event Reporting System (FAERS): A Proof-of-Concept Study Using Galcanezumab and Simulated Data.

INTRODUCTION: Time- and resource-demanding activities related to processing individual case safety reports (ICSRs) include manual procedures to evaluate individual causality with the final goal of dismissing false-positive safety signals. Eminent experts and a representative from pharmaceutical industries and regulatory agencies have highlighted the need to automatize time- and resource-demanding procedures in signal detection and validation. However, to date there is a sparse availability of automatized tools for such purposes. OBJECTIVES: ICSRs recorded in spontaneous reporting databases have been and continue to be the cornerstone and the most important data source in signal detection. Despite the richness of this data source, the incessantly increased amount of ICSRs recorded in spontaneous reporting databases has generated problems in signal detection and validation due to the increase in resources and time needed to process cases. This study aimed to develop a new artificial intelligence (AI)-based framework to automate resource- and time-consuming steps of signal detection and signal validation, such as (1) the selection of control groups in disproportionality analyses and (2) the identification of co-reported drugs serving as alternative causes, to look to dismiss false-positive disproportionality signals and therefore reduce the burden of case-by-case validation. METHODS: The Summary of Product Characteristics (SmPC) and the Anatomical Therapeutic Chemical (ATC) classification system were used to automatically identify control groups within and outside the chemical subgroup of the proof-of-concept drug under investigation, galcanezumab. Machine learning, specifically conditional inference trees, has been used to identify alternative causes in disproportionality signals. RESULTS: By using conditional inference trees, the framework was able to dismiss 20.00% of erenumab, 14.29% of topiramate, and 13.33% of amitriptyline disproportionality signals on the basis of purely alternative causes identified in cases. Furthermore, of the disproportionality signals that could not be dismissed purely on the basis of the alternative causes identified, we estimated a 15.32%, 25.39%, and 26.41% reduction in the number of galcanezumab cases to undergo manual validation in comparison with erenumab, topiramate, and amitriptyline, respectively. CONCLUSION: AI could significantly ease some of the most time-consuming and labor-intensive steps of signal detection and validation. The AI-based approach showed promising results, however, future work is needed to validate the framework.

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.

Review of Over 15 Years Postmarketing Safety Surveillance Spontaneous Data for the Human Rotavirus Vaccine (Rotarix) on Intussusception.

INTRODUCTION: Rotavirus (RV) is the most common cause of acute gastroenteritis in children <5 years of age worldwide, and vaccination reduces the disease burden. Evidence from postmarketing surveillance studies suggested an increased risk of intussusception (IS) in infants post-RV vaccination. An overall positive benefit-risk balance for the human RV vaccine (HRV) Rotarix (GlaxoSmithKline [GSK], Belgium) has been established and recent findings indicate an indirect effect of reduced IS over the long term. OBJECTIVE: The aim of this study was to discuss spontaneous data from the GSK worldwide safety database on IS post-Rotarix administration. METHODS: The database was reviewed for all spontaneous IS cases from 2004 to 2020. Additionally, an observed versus expected (O/E) analysis was done for adverse events attributed to IS. Data were reviewed as overall worldwide and stratified by region (Europe/USA/Japan) and dose. RESULTS: A male predominance of IS patients was observed, consistent with earlier reports. The most frequently reported events in confirmed IS cases (Brighton Collaboration Working Group [BCWG] level 1) with time to onset ≤ 30 days post-vaccination were vomiting (55.8%), haematochezia (47.2%), and crying (21.1%). The observations from the IS spontaneous cases review and results of the O/E analysis are consistent with the known IS safety profile of RV vaccines: a transient increased incidence of IS post-vaccination (primarily in Europe/Japan/worldwide), mostly within 7 days postdose 1. CONCLUSION: Since the outcomes of early IS management are favourable over delayed management, healthcare professionals should inform parents about the importance of seeking immediate medical advice in case of unusual behaviour of the vaccinated infant. GSK continues to monitor the IS risk post-Rotarix administration through routine pharmacovigilance activities.

Rotavirus (RV) is the most common cause of acute gastroenteritis and a major cause of death in young children worldwide. Vaccination has been instrumental in reducing the impact of RV disease. Real-world evidence suggests an increased risk of intussusception (an infrequent type of bowel obstruction) in infants following RV vaccination. We reviewed IS cases reported spontaneously worldwide in children following a two-dose vaccination with the human RV vaccine (Rotarix, GlaxoSmithKline [GSK]) since its launch in 2004. We observed that (1) IS occurred more frequently 7 days after the first dose and, to a lesser extent, after the second dose; (2) boys were more frequently affected than girls (56.3%); (3) of 862 confirmed reported cases, 557 required hospitalisation; and (4) surgical intervention was required for 294 of 557 hospitalised cases. We used statistical analysis to assess whether the number of cases observed would be higher or lower than the natural occurrence of IS (irrespective of vaccination). These results were in line with the known RV vaccine safety profile. It is important to constantly monitor the real-world safety profile of RV vaccines in the postmarketing setting. Since the outcomes of early management of IS are favourable compared with delayed management, healthcare professionals should inform parents to seek immediate medical advice if they observe unusual behaviour in their vaccinated child. In conclusion, our analyses on data of a large patient pool for this rare event reinforce the favourable safety profile of human RV vaccine and the benefits of vaccination in young children.

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.

Dengue Infection in Children in Fortaleza, Brazil: A 3-Year School-Based Prospective Cohort Study.

Dengue is endemic in Brazil. The dengue surveillance system's reliance on passive reporting may underestimate disease incidence and cannot detect asymptomatic/pauci-symptomatic cases. In this 3-year prospective cohort study (NCT01391819) in 5- to 13-year-old children from nine schools in Fortaleza (N = 2,117), we assessed dengue virus (DENV) infection seroprevalence by IgG indirect ELISA at yearly visits and disease incidence through active and enhanced passive surveillance. Real-time quantitative polymerase chain reaction (RT-qPCR) and DENV IgM/IgG capture ELISA were used for diagnosis. We further characterized confirmed and probable cases with a plaque reduction neutralization test. At enrollment, 54.1% (95% CI: 46.6, 61.4) of children were DENV IgG positive. The annual incidence of laboratory-confirmed symptomatic dengue cases was 11.0 (95% CI: 7.3, 14.7), 18.1 (10.4, 25.7), and 10.2 (0.7, 19.7), and of laboratory-confirmed or probable dengue cases with neutralizing antibody profile evocative of dengue exposure was 13.2 (6.6, 19.9), 18.7 (5.3, 32.2), and 8.4 (2.4, 19.2) per 1,000 child-years in 2012, 2013, and 2014, respectively. By RT-qPCR, we identified 14 DENV-4 cases in 2012-2013 and seven DENV-1 cases in 2014. During the course of the study, 32.8% of dengue-naive children experienced a primary infection. Primary inapparent dengue infection was detected in 20.3% (95% CI: 13.6, 29.1) of dengue-naive children in 2012, 8.7% (6.9, 10.9) in 2013, and 5.1% (4.4, 6.0) in 2014. Our results confirmed the high dengue endemicity in Fortaleza, with active and enhanced passive surveillance detecting three to five times more cases than the National System of Disease Notification.

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.

Prevalence and Persistence of Maternal Dengue Neutralizing Antibodies in Infants From Central and Southern Thailand: A Retrospective Cohort Study.

Understanding maternal dengue virus (DENV) neutralizing antibody kinetics in infants remains timely to develop a safe and effective childhood immunization. This retrospective study evaluated the prevalence and persistence of maternal antibody titers against DENV serotypes 1 to 4 in 139 Thai infants at 2, 6, and 7 months of age, using serum samples collected in a vaccination trial ( http://clinicaltrials.gov ; NCT00197275). Neutralizing antibodies against all 4 DENV serotypes were detected in 87.8% and 22.9% of infants at 2 and 7 months, respectively. At 2 months, DENV-4 neutralizing antibody geometric mean titers were notably lower (80) compared with DENV-1 to DENV-3 (277-471). Our results corroborate previous findings that DENV-1 to DENV-4 maternal antibodies persist at 7 months despite titers decrease from 2 months onwards. As persisting maternal antibodies may inhibit immune responses in DENV-vaccinated infants, a comprehensive understanding of DENV antibody kinetics is required in the perspective of vaccine development for infants.

Enhanced Safety Surveillance of Influenza Vaccines in General Practice, 2015-16: Feasibility Study.

BACKGROUND: The European Medicines Agency (EMA) requires vaccine manufacturers to conduct enhanced real-time surveillance of seasonal influenza vaccination. The EMA has specified a list of adverse events of interest to be monitored. The EMA sets out 3 different ways to conduct such surveillance: (1) active surveillance, (2) enhanced passive surveillance, or (3) electronic health record data mining (EHR-DM). English general practice (GP) is a suitable setting to implement enhanced passive surveillance and EHR-DM. OBJECTIVE: This study aimed to test the feasibility of conducting enhanced passive surveillance in GP using the yellow card scheme (adverse events of interest reporting cards) to determine if it has any advantages over EHR-DM alone. METHODS: A total of 9 GPs in England participated, of which 3 tested the feasibility of enhanced passive surveillance and the other 6 EHR-DM alone. The 3 that tested EPS provided patients with yellow (adverse events) cards for patients to report any adverse events. Data were extracted from all 9 GPs' EHRs between weeks 35 and 49 (08/24/2015 to 12/06/2015), the main period of influenza vaccination. We conducted weekly analysis and end-of-study analyses. RESULTS: Our GPs were largely distributed across England with a registered population of 81,040. In the week 49 report, 15,863/81,040 people (19.57% of the registered practice population) were vaccinated. In the EPS practices, staff managed to hand out the cards to 61.25% (4150/6776) of the vaccinees, and of these cards, 1.98% (82/4150) were returned to the GP offices. Adverse events of interests were reported by 113 /7223 people (1.56%) in the enhanced passive surveillance practices, compared with 322/8640 people (3.73%) in the EHR-DM practices. CONCLUSIONS: Overall, we demonstrated that GPs EHR-DM was an appropriate method of enhanced surveillance. However, the use of yellow cards, in enhanced passive surveillance practices, did not enhance the collection of adverse events of interests as demonstrated in this study. Their return rate was poor, data entry from them was not straightforward, and there were issues with data reconciliation. We concluded that customized cards prespecifying the EMA's adverse events of interests, combined with EHR-DM, were needed to maximize data collection. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2016-015469.