Journal Article

A statistical method for evaluating vaccine-induced immune correlates of protection against infection and disease progression: application to the ChAdOx1-S nCoV-19 phase 3 trial

Grassly, Nicholas C., Voysey, Merryn, Pollard, Andrew J., Williams, Lucy R.

2025

Overview

Correlates of protection (CoPs), defined as immune markers statistically correlated with vaccine efficacy (VE), can be used to accelerate vaccine development. Different components of the immune response may be important for protection against infection and against progression from asymptomatic infection to symptomatic or severe disease. However, CoPs are typically evaluated for these outcomes separately, which can lead to some CoPs not being identified. We propose a novel statistical framework for the integrated evaluation of CoPs for infections with multiple potential outcomes. We developed a model of the natural history of an infection that can identify CoPs at each stage of infection and disease progression and implemented this model in a Bayesian estimation framework. We validated the model on simulated data then applied it to individual-level clinical and serum neutralising and binding antibody data from COV002 (NCT04400838), a phase II/III trial of the ChAdOx1 nCoV-19 (AZD1222) vaccine. We explored logistic and non-parametric (cubic spline) relationships between VE and the candidate CoPs. Both parametric and non-parametric forms of the model accurately estimated the relationships between the immune CoP and VE against infection (VEin) and against progression to symptoms given infection (VEpr) in 1000 simulated trial datasets. In the COV002 correlates subset (2227 participants, 5315 samples), SARS-CoV-2 spike-specific IgG was positively associated with both VEin and VEpr (average proportion of VE mediated by spike-specific IgG, 27 % (95 % CI 2–88 %) for VEin and 41 % (95 % CI 0–96 %) for VEpr). Pseudoneutralisation antibody titres and receptor binding domain (RBD) specific serum IgG showed similar correlations. Integrated analysis of multiple disease outcomes and candidate CoPs enables the identification of CoPs that operate at different stages of disease progression, which are missed when evaluating outcomes separately. •Effectors of immune protection after vaccination may vary by the outcome under consideration.•We present a method to estimate immune correlates of protection against infection and disease progression from trial data.•We use causal inference to estimate the proportion of protection mediated by the immune correlate at different values.•We validate this method using simulated datasets and apply it to phase 2/3 trial data for the ChAdOx1 nCoV-19 vaccine.•The method identifies immune correlates of protection against infection missed when analysing asymptomatic infection alone.•It highlights the importance of spike-specific serum IgG in protecting against SARS-CoV-2 infection and disease.

• Publisher: Elsevier Ltd,Elsevier Limited
• Subject: Allergy and Immunology / Antibodies / Antibodies, Neutralizing - blood / Antibodies, Neutralizing - immunology / Antibodies, Viral - blood / Antibodies, Viral - immunology / Asymptomatic / Asymptomatic infection / Bayes Theorem / Bayesian analysis / Bayesian statistics / Binding / ChAdOx1 nCoV-19 - administration & dosage / ChAdOx1 nCoV-19 - immunology / Clinical outcomes / Clinical trial / Correlation / COVID-19 / COVID-19 - immunology / COVID-19 - prevention & control / COVID-19 vaccines / Disease Progression / Female / Humans / Immune correlate of protection / Immune response / Immune system / Immunoglobulin G / Infections / Male / Mediation / Models, Statistical / Natural history / SARS-CoV-2 - immunology / Severe acute respiratory syndrome coronavirus 2 / Statistical analysis / Statistical method / Statistical methods / Statistics / Vaccine / Vaccine development / Vaccine Efficacy / Vaccines / Viral diseases