ArticleBiostatistics (Oxford, England)2022
Immune correlates analysis using vaccinees from test negative designs.
Article in Biostatistics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- A comparison of the test-negative and the matched case-control study designs for estimation of EV71 vaccine immunological surrogate endpoints from a randomized controlled trial.Human vaccines & immunotherapeutics · 2022Trial
- Use of the test-negative design to estimate the protective effect of a scalar immune measure: a simulation analysis.American journal of epidemiology · 2026Article
- Influenza Antibody Levels Associated with Laboratory-Confirmed Influenza in a Test-Negative Study Design, US Flu VE Network, November 2018-May 2019.medRxiv : the preprint server for health sciences · 2026Article
- A Test-Negative Design for Immune Correlates Approximates a Traditional Exposure-Proximal Design but Requires Far Fewer Blood Samples.The Journal of infectious diseases · 2026Article
- Access to licenced vaccines for high-threat infectious diseases: a scoping review and interpretive analysis of Ebola virus disease.BMC infectious diseases · 2026Article
- Anti-SARS-CoV-2 Antibody Levels Associated With COVID-19 Protection in Outpatients Tested for SARS-CoV-2, US Flu Vaccine Effectiveness Network, October 2021-June 2022.The Journal of infectious diseases · 2024Article
- Antibody response to symptomatic infection with SARS-CoV-2 Omicron variant viruses, December 2021-June 2022.medRxiv : the preprint server for health sciences · 2023Article
- Kinetics of the Antibody Response to Symptomatic SARS-CoV-2 Infection in Vaccinated and Unvaccinated Individuals in the Blinded Phase of the mRNA-1273 COVID-19 Vaccine Efficacy Trial.Open forum infectious diseases · 2023Article
- SARS-CoV-2 breakthrough infections in vaccinated individuals: measurement, causes and impact.Nature reviews. Immunology · 2022Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Determining the effect of vaccine-induced immune response on disease risk is an important goal of vaccinology. Typically, immune correlates analyses are conducted prospectively with immune response measured shortly after vaccination and subsequent disease status regressed on immune response. In outbreaks and rare disease settings, collecting samples from all vaccinees is not feasible. The test negative design is a retrospective design used to measure vaccine efficacy where symptomatic individuals who present at a clinic are assessed for relevant disease (cases) or some other disease (controls) and vaccination status ascertained. This article proposes that test negative vaccinees have immune response to vaccine assessed both for relevant (e.g., Ebola) and irrelevant (e.g., vector) proteins. If the latter immune response is unaffected by active (Ebola) infection, and is correlated with the relevant immune response, it can serve as a proxy for the immune response of interest proximal to infection. We show that logistic regression using imputed immune response as the covariate and case disease as outcome can estimate the prospective immune response slope and detail the assumptions needed for unbiased inference. The method is evaluated by simulation under various scenarios including constant and decaying immune response. A simulated dataset motivated by ring vaccination for an ongoing Ebola outbreak is analyzed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.