Aller au contenu principal
Accès ouvert déclaré 2025 article

Evaluating the Test-Negative Design for COVID-19 Vaccine Effectiveness Using Randomized Trial Data

6Citations signalées, ce qui n’est pas une note de qualité
22Institutions déclarées
3Pays d’affiliation déclarés

Rattachement africain : us, gb, be. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

Importance: The test-negative design (TND) has been widely used to assess postmarketing COVID-19 vaccine effectiveness but requires further evaluation for this application. Objective: To determine whether the TND reliably evaluates vaccine effectiveness against symptomatic COVID-19 using placebo-controlled vaccine efficacy randomized clinical trials (RCTs). Design, Setting, and Participants: This secondary cross-protocol analysis constructed TND study datasets from study sites in 16 countries across 5 continents using the blinded phase cohorts of 5 harmonized phase 3 COVID-19 Prevention Network RCTs: COVE (Coronavirus Vaccine Efficacy and Safety), AZD1222, ENSEMBLE, PREVENT-19 (Prefusion Protein Subunit Vaccine Efficacy Novavax Trial COVID-19), and VAT00008. Participants included adults who received the intended number of doses, experienced COVID-19-like symptoms, and obtained SARS-CoV-2 testing. Start dates ranged from July 27, 2020, to October 19, 2021; data cutoff dates ranged from March 26, 2021, to March 15, 2022. Statistical analysis was performed from May 11, 2023, to February 25, 2025. Interventions: Participants received vaccines consisting of messenger RNA-1273 (COVE; 2 doses 28 days apart), ChAdOx1 nCoV-19 (AZD1222; 2 doses 28 days apart), Ad26.COV2.S (ENSEMBLE; 1 dose), NVX-CoV2373 (PREVENT-19; 2 doses 21 days apart), CoV2 preS dTM-AS03 (VAT00008; D614) (2 doses 21 days apart), or CoV2 preS dTM-AS03 (D614 plus B.1.351) (VAT00008; 2 doses 21 days apart) or placebo. Main Outcomes and Measures: Main outcomes were symptomatic COVID-19 according to each trial's primary efficacy definition and the Centers for Disease Control and Prevention definition. Vaccine effectiveness was estimated using targeted maximum likelihood estimation under a semiparametric logistic regression model and ordinary logistic regression. Noncase exchangeability, a core TND assumption for unbiased estimation, was also assessed by estimating vaccine efficacy against non-COVID-19 illness. Results: Among the 12 157 participants included in the analysis, mean (SD) age was 45 (15) years, 6414 were female (53%), 5858 were vaccinated (48%), 2835 experienced primary COVID-19 (23%), and 2992 experienced Centers for Disease Control and Prevention-defined COVID-19 (25%). TND vaccine effectiveness estimates were concordant with RCT vaccine efficacy estimates (concordance correlation coefficient, 0.86 [95% CI, 0.58-0.96] for both outcomes). The semiparametric method had 48% smaller variance estimates than ordinary logistic regression. Noncase exchangeability was generally supported with a median vaccine efficacy against non-COVID-19 illness of 7.7% (IQR, 2.7%-16.8%) across trial cohorts and most 95% CIs including 0. Conclusions and Relevance: In this cross-protocol analysis, the TND provided reliable inferences on COVID-19 vaccine effectiveness in health care-seeking populations for multiple vaccines and symptom definitions when confounding and selection bias were absent. A machine-learning approach for robust confounding control in postmarketing TND studies was also introduced.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Evaluating the Test-Negative Design for COVID-19 Vaccine Effectiveness Using Randomized Trial Data
Date Crossref
28/05/2025
Éditeur
American Medical Association (AMA)
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Où se fait cette recherche

  • University of Washington pays non établi dans la notice
    Université ou école supérieure
  • Fred Hutch Cancer Center pays non établi dans la notice
    Organisation à but non lucratif
  • National Institutes of Health Fogarty International Center pays non établi dans la notice
    Organisme public
  • Fogarty International Center pays non établi dans la notice
    Établissement de santé
  • Florida State University pays non établi dans la notice
    Université ou école supérieure
  • Grady Memorial Hospital pays non établi dans la notice
    Établissement de santé
  • Emory University Department of Medicine pays non établi dans la notice
    Université ou école supérieure
  • Grady Health System pays non établi dans la notice
    Établissement de santé
  • Brigham and Women's Hospital Division of Infectious Diseases pays non établi dans la notice
    Établissement de santé
  • Columbia University pays non établi dans la notice
    Université ou école supérieure
  • New York Blood Center pays non établi dans la notice
    Organisation à but non lucratif
  • Baylor College of Medicine Department of Molecular Virology and Microbiology pays non établi dans la notice
    Université ou école supérieure

University of Washington, Fred Hutch Cancer Center et Fogarty International Center — National Institutes of Health, avec 9 autres affiliations.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

SARS-CoV-2 and COVID-19 Researchvaccines and immunoinformatics approachesImmune responses and vaccinations

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.