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Determination of Vaccine Immunogenicity Using Bovine Monocyte-Derived Dendritic Cells

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Published on: May 19, 2023

A threshold method for immunological correlates of protection.

Xuan Chen¹, Fabrice Bailleux, Kamal Desai

¹Sanofi Pasteur, Beijing, China

BMC Medical Research Methodology

|March 2, 2013

Summary

A new statistical model, the a:b model, formally estimates immunological thresholds for vaccine protection. This method identifies protective levels, aiding vaccine research and policy by differentiating susceptible from protected individuals.

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Area of Science:

Biostatistics
Vaccinology
Immunology

Background:

Immunological correlates of protection, such as antibodies, are crucial for vaccine research and policy.
Established thresholds for these correlates differentiate protected from susceptible individuals.
Existing statistical methods lack formal incorporation of threshold estimation from data.

Purpose of the Study:

To introduce and evaluate a novel statistical model for estimating protective thresholds.
To provide a formal method for differentiating susceptible from protected individuals based on immunological markers.

Main Methods:

Proposed the 3-parameter a:b model incorporating threshold and differential infection probabilities.
Employed profile likelihood or least squares for parameter estimation.
Utilized a modified likelihood ratio test for threshold significance and bootstrapping for confidence intervals.

Main Results:

The a:b model identified highly significant thresholds (p<0.01) in 13 of 15 datasets.
Relative risk analysis indicated substantial protection (≥70%) in 11 datasets.
Goodness-of-fit assessments were generally acceptable.

Conclusions:

The a:b model provides a formal statistical approach for estimating protective thresholds.
This method moves beyond visual inspection, offering data-driven threshold determination.
The model aids in refining vaccine policy and research by quantifying protection levels.