Effectiveness of Recombinant Zoster Vaccine Against Herpes Zoster in a Real-World Setting.

BACKGROUND: A 2-dose series of recombinant zoster vaccine (RZV) was 97% effective against herpes zoster (HZ) in a pivotal clinical trial. OBJECTIVE: To evaluate real-world effectiveness of RZV against HZ. DESIGN: Prospective cohort study. SETTING: Four health care systems in the Vaccine Safety Datalink. PARTICIPANTS: Persons aged 50 years or older. MEASUREMENTS: The outcome was incident HZ defined by a diagnosis with an antiviral prescription. Cox regression was used to estimate the hazard of HZ in vaccinated persons compared with unvaccinated persons, with adjustment for covariates. Vaccine effectiveness (VE) was calculated as 1 minus the adjusted hazard ratio and was estimated by time since the last RZV dose and by corticosteroid use. RESULTS: The study included nearly 2.0 million persons who contributed 7.6 million person-years of follow-up. After adjustment, VE of 1 dose was 64% and VE of 2 doses was 76%. After 1 dose only, VE was 70% during the first year, 45% during the second year, 48% during the third year, and 52% after the third year. After 2 doses, VE was 79% during the first year, 75% during the second year, and 73% during the third and fourth years. Vaccine effectiveness was 65% in persons who received corticosteroids before vaccination and 77% in those who did not. LIMITATION: Herpes zoster could not be identified as accurately in these observational data as in the previous clinical trials. CONCLUSION: Two doses of RZV were highly effective, although less effective than in the previous clinical trials. Two-dose effectiveness waned very little during the 4 years of follow-up. However, 1-dose effectiveness waned substantially after 1 year, underscoring the importance of the second dose. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention.

Influenza Vaccine Effectiveness Against Influenza A-Associated Emergency Department, Urgent Care, and Hospitalization Encounters Among US Adults, 2022-2023.

BACKGROUND: The 2022-2023 United States influenza season had unusually early influenza activity with high hospitalization rates. Vaccine-matched A(H3N2) viruses predominated, with lower levels of A(H1N1)pdm09 activity also observed. METHODS: Using the test-negative design, we evaluated influenza vaccine effectiveness (VE) during the 2022-2023 season against influenza A-associated emergency department/urgent care (ED/UC) visits and hospitalizations from October 2022 to March 2023 among adults (aged ≥18 years) with acute respiratory illness (ARI). VE was estimated by comparing odds of seasonal influenza vaccination among case-patients (influenza A test positive by molecular assay) and controls (influenza test negative), applying inverse-propensity-to-be-vaccinated weights. RESULTS: The analysis included 85 389 ED/UC ARI encounters (17.0% influenza A positive; 37.8% vaccinated overall) and 19 751 hospitalizations (9.5% influenza A positive; 52.8% vaccinated overall). VE against influenza A-associated ED/UC encounters was 44% (95% confidence interval [CI], 40%-47%) overall and 45% and 41% among adults aged 18-64 and ≥65 years, respectively. VE against influenza A-associated hospitalizations was 35% (95% CI, 27%-43%) overall and 23% and 41% among adults aged 18-64 and ≥65 years, respectively. CONCLUSIONS: VE was moderate during the 2022-2023 influenza season, a season characterized with increased burden of influenza and co-circulation with other respiratory viruses. Vaccination is likely to substantially reduce morbidity, mortality, and strain on healthcare resources.

A simple Cox approach to estimating risk ratios without sharing individual-level data in multi-site studies.

Epidemiologic studies frequently use risk ratios to quantify associations between exposures and binary outcomes. When the data are physically stored at multiple data partners, it can be challenging to perform individual-level analysis if data cannot be pooled centrally due to privacy constraints. Existing methods either require multiple file transfers between each data partner and an analysis center (e.g., distributed regression) or only provide approximate estimation of the risk ratio (e.g., meta-analysis). Here we develop a practical method that requires a single transfer of eight summary-level quantities from each data partner. Our approach leverages an existing risk-set method and software originally developed for Cox regression. Sharing only summary-level information, the proposed method provides risk ratio estimates and confidence intervals identical to those that would be provided - if individual-level data were pooled - by the modified Poisson regression. We justify the method theoretically, confirm its performance using simulated data, and implement it in a distributed analysis of COVID-19 data from the U.S. Food and Drug Administration's Sentinel System.

Interim Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccines Against COVID-19-Associated Hospitalization Among Adults Aged ≥18 Years with Immunocompromising Conditions - VISION Network, September 2023-February 2024.

In September 2023, CDC's Advisory Committee on Immunization Practices recommended updated 2023-2024 (monovalent XBB.1.5) COVID-19 vaccination for all persons aged ≥6 months to prevent COVID-19, including severe disease. As with past COVID-19 vaccines, additional doses may be considered for persons with immunocompromising conditions, who are at higher risk for severe COVID-19 and might have decreased response to vaccination. In this analysis, vaccine effectiveness (VE) of an updated COVID-19 vaccine dose against COVID-19-associated hospitalization was evaluated during September 2023-February 2024 using data from the VISION VE network. Among adults aged ≥18 years with immunocompromising conditions, VE against COVID-19-associated hospitalization was 38% in the 7-59 days after receipt of an updated vaccine dose and 34% in the 60-119 days after receipt of an updated dose. Few persons (18%) in this high-risk study population had received updated COVID-19 vaccine. All persons aged ≥6 months should receive updated 2023-2024 COVID-19 vaccination; persons with immunocompromising conditions may get additional updated COVID-19 vaccine doses ≥2 months after the last recommended COVID-19 vaccine.

Interim Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccines Against COVID-19-Associated Emergency Department and Urgent Care Encounters and Hospitalization Among Immunocompetent Adults Aged ≥18 Years - VISION and IVY Networks, September 2023-January 2024.

In September 2023, CDC's Advisory Committee on Immunization Practices recommended updated 2023-2024 (monovalent XBB.1.5) COVID-19 vaccination for all persons aged ≥6 months to prevent COVID-19, including severe disease. However, few estimates of updated vaccine effectiveness (VE) against medically attended illness are available. This analysis evaluated VE of an updated COVID-19 vaccine dose against COVID-19-associated emergency department (ED) or urgent care (UC) encounters and hospitalization among immunocompetent adults aged ≥18 years during September 2023-January 2024 using a test-negative, case-control design with data from two CDC VE networks. VE against COVID-19-associated ED/UC encounters was 51% (95% CI = 47%-54%) during the first 7-59 days after an updated dose and 39% (95% CI = 33%-45%) during the 60-119 days after an updated dose. VE estimates against COVID-19-associated hospitalization from two CDC VE networks were 52% (95% CI = 47%-57%) and 43% (95% CI = 27%-56%), with a median interval from updated dose of 42 and 47 days, respectively. Updated COVID-19 vaccine provided increased protection against COVID-19-associated ED/UC encounters and hospitalization among immunocompetent adults. These results support CDC recommendations for updated 2023-2024 COVID-19 vaccination. All persons aged ≥6 months should receive updated 2023-2024 COVID-19 vaccine.

Tinnitus after COVID-19 vaccination: Findings from the vaccine adverse event reporting system and the vaccine safety datalink.

PURPOSE: To assess the occurrence of tinnitus following COVID-19 vaccination using data mining and descriptive analyses in two U.S. vaccine safety surveillance systems. METHODS: Reports of tinnitus after COVID-19 vaccination to the Vaccine Adverse Event Reporting System (VAERS) from 2020 through 2024 were examined using empirical Bayesian data mining and by calculating reporting rates. In the Vaccine Safety Datalink (VSD) population, ICD-10 coded post-vaccination medical visits were examined using tree-based data mining, and tinnitus visit incidence rates during post-vaccination days 1-140 were calculated by age group for COVID-19 vaccines and for comparison, influenza vaccine. RESULTS: VAERS data mining did not find disproportionate reporting of tinnitus for any COVID-19 vaccine. VAERS received up to 84.82 tinnitus reports per million COVID-19 vaccine doses administered. VSD tree-based data mining found no signals for tinnitus. VSD tinnitus visit incidence rates after COVID-19 vaccines were similar to those after influenza vaccine except for the group aged ≥65 years (Moderna COVID-19 vaccine, 165 per 10,000 person-years; Pfizer-BioNTech COVID-19 vaccine, 154; influenza vaccine, 135). CONCLUSIONS: Overall, these findings do not support an increased risk of tinnitus following COVID-19 vaccination but cannot definitively exclude the possibility. Descriptive comparisons between COVID-19 and influenza vaccines were limited by lack of adjustment for potential confounding factors.

Trends in Gonorrhea and Chlamydia Testing and Infections Across the COVID-19 Pandemic in Adolescents and Young Adults in an Integrated Health System.

PURPOSE: The COVID-19 pandemic impacted testing and incidence of sexually transmitted infections (STIs), with some studies showing uneven effects across sociodemographic groups. We aim to determine whether rates of gonorrhea and chlamydia testing and infections were affected by the pandemic, overall and by subgroups, defined by sociodemographic factors and comorbidities. METHODS: We conducted a retrospective cohort study from January 1, 2016, through December 31, 2022, among adolescents and young adults ages 15-29 years within Kaiser Permanente Northern California (KPNC). We determined the rate of testing for gonorrhea/chlamydia, and the incident rates of infections before and during the COVID-19 pandemic by sociodemographic factors. We compared incidence rates of gonorrhea/chlamydia testing and infection before and during the pandemic using Poisson regression. RESULTS: Gonorrhea/chlamydia testing during the pandemic was 19% lower than prepandemic baseline. Testing among Black patients was 1.8-fold higher than White patients. Black patients had 5.5 and 3.6-fold higher rate of gonorrhea and chlamydia infections, respectively, compared with White patients. Patients living in more deprived neighborhoods also had higher rates of infection compared to those in the least deprived neighborhoods. In multivariable analyses stratified by the period before and during the COVID-19 pandemic, there were no significant differences in the incidence rate ratios of testing or infections for any specific sociodemographic factor. DISCUSSION: STI testing in adolescents and young adults dropped dramatically after the start of the pandemic and has not recovered to its prior levels. Preexisting disparities in STI testing and infections were not exacerbated by the pandemic.

Impact of the PATH Statement on Analysis and Reporting of Heterogeneity of Treatment Effect in Clinical Trials: A Scoping Review.

Background: The Predictive Approaches to Treatment Effect Heterogeneity (PATH) Statement provides guidance for using predictive modeling to identify differences (i.e., heterogeneity) in treatment effects (benefits and harms) among participants in randomized clinical trials (RCTs). It distinguished risk modeling, which uses a multivariable model to predict risk of trial outcome(s) and then examines treatment effects within strata of predicted risk, from effect modeling, which predicts trial outcomes using models that include treatment, individual participant characteristics and interactions of treatment with selected characteristics. Purpose: To describe studies of heterogeneous treatment effects (HTE) that use predictive modeling in RCT data and cite the PATH Statement. Data Sources: The Cited By functions in PubMed, Google Scholar, Web of Science and SCOPUS databases (Jan 7, 2020 - June 5, 2023). Study Selection: 42 reports presenting 45 predictive models. Data Extraction: Double review with adjudication to identify risk and effect modeling and examine consistency with Statement consensus statements. Credibility of HTE findings was assessed using criteria adapted from the Instrument to assess Credibility of Effect Modification Analyses (ICEMAN). Clinical importance of credible HTE findings was also assessed. Data Synthesis: The numbers of reports, especially risk modeling reports, increased year-on-year. Consistency with consensus statements was high, except for two: only 15 of 32 studies with positive overall findings included a risk model; and most effect models explored many candidate covariates with little prior evidence for effect modification. Risk modeling was more likely than effect modeling to identify both credible HTE (14/19 vs 5/26) and clinically important HTE (10/19 vs 4/26). Limitations: Risk of reviewer bias: reviewers assessing credibility and clinical importance were not blinded to adherence to PATH recommendations. Conclusions: The PATH Statement appears to be influencing research practice. Risk modeling often uncovered clinically important HTE; effect modeling was more often exploratory.

Ischemic Stroke After Bivalent COVID-19 Vaccination: Self-Controlled Case Series Study.

BACKGROUND: The potential association between bivalent COVID-19 vaccination and ischemic stroke remains uncertain, despite several studies conducted thus far. OBJECTIVE: This study aimed to evaluate the risk of ischemic stroke following bivalent COVID-19 vaccination during the 2022-2023 season. METHODS: A self-controlled case series study was conducted among members aged 12 years and older who experienced ischemic stroke between September 1, 2022, and March 31, 2023, in a large health care system. Ischemic strokes were identified using International Classification of Diseases, Tenth Revision codes in emergency departments and inpatient settings. Exposures were Pfizer-BioNTech or Moderna bivalent COVID-19 vaccination. Risk intervals were prespecified as 1-21 days and 1-42 days after bivalent vaccination; all non-risk-interval person-time served as the control interval. The incidence of ischemic stroke was compared in the risk interval and control interval using conditional Poisson regression. We conducted overall and subgroup analyses by age, history of SARS-CoV-2 infection, and coadministration of influenza vaccine. When an elevated risk was detected, we performed a chart review of ischemic strokes and analyzed the risk of chart-confirmed ischemic stroke. RESULTS: With 4933 ischemic stroke events, we found no increased risk within the 21-day risk interval for the 2 vaccines and by subgroups. However, risk of ischemic stroke was elevated within the 42-day risk interval among individuals aged younger than 65 years with coadministration of Pfizer-BioNTech bivalent and influenza vaccines on the same day; the relative incidence (RI) was 2.13 (95% CI 1.01-4.46). Among those who also had a history of SARS-CoV-2 infection, the RI was 3.94 (95% CI 1.10-14.16). After chart review, the RIs were 2.34 (95% CI 0.97-5.65) and 4.27 (95% CI 0.97-18.85), respectively. Among individuals aged younger than 65 years who received Moderna bivalent vaccine and had a history of SARS-CoV-2 infection, the RI was 2.62 (95% CI 1.13-6.03) before chart review and 2.24 (95% CI 0.78-6.47) after chart review. Stratified analyses by sex did not show a significantly increased risk of ischemic stroke after bivalent vaccination. CONCLUSIONS: While the point estimate for the risk of chart-confirmed ischemic stroke was elevated in a risk interval of 1-42 days among individuals younger than 65 years with coadministration of Pfizer-BioNTech bivalent and influenza vaccines on the same day and among individuals younger than 65 years who received Moderna bivalent vaccine and had a history of SARS-CoV-2 infection, the risk was not statistically significant. The potential association between bivalent vaccination and ischemic stroke in the 1-42-day analysis warrants further investigation among individuals younger than 65 years with influenza vaccine coadministration and prior SARS-CoV-2 infection. Furthermore, the findings on ischemic stroke risk after bivalent COVID-19 vaccination underscore the need to evaluate monovalent COVID-19 vaccine safety during the 2023-2024 season.

Mortality risk after COVID-19 vaccination: A self-controlled case series study.

BACKGROUND: Although previous studies found no-increased mortality risk after COVID-19 vaccination, residual confounding bias might have impacted the findings. Using a modified self-controlled case series (SCCS) design, we assessed the risk of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes after primary series COVID-19 vaccination. METHODS: We analyzed all deaths between December 14, 2020, and August 11, 2021, among individuals from eight Vaccine Safety Datalink sites. Demographic characteristics of deaths in recipients of COVID-19 vaccines and unvaccinated individuals were reported. We conducted SCCS analyses by vaccine type and death outcomes and reported relative incidences (RI). The observation period for death spanned from the dates of emergency use authorization to the end of the study period (August 11, 2021) without censoring the observation period upon death. We pre-specified a primary risk interval of 28-day and a secondary risk interval of 14-day after each vaccination dose. Adjusting for seasonality in mortality analyses is crucial because death rates vary over time. Deaths among unvaccinated individuals were included in SCCS analyses to account for seasonality by incorporating calendar month in the models. RESULTS: For Pfizer-BioNTech (BNT162b2), RIs of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes were below 1 and 95 % confidence intervals (CIs) excluded 1 across both doses and both risk intervals. For Moderna (mRNA-1273), RI point estimates of all outcomes were below 1, although the 95 % CIs of two RI estimates included 1: cardiac-related (RI = 0.78, 95 % CI, 0.58-1.04) and non-COVID-19 cardiac-related mortality (RI = 0.80, 95 % CI, 0.60-1.08) 14 days after the second dose in individuals without pre-existing cancer and heart disease. For Janssen (Ad26.COV2.S), RIs of four cardiac-related death outcomes ranged from 0.94 to 0.98 for the 14-day risk interval, and 0.68 to 0.72 for the 28-day risk interval and 95 % CIs included 1. CONCLUSION: Using a modified SCCS design and adjusting for temporal trends, no-increased risk was found for non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes among recipients of the three COVID-19 vaccines used in the US.