Coudeville Laurent, Konate Eleine, Simon Tabassome, de Lamballerie Xavier, Patterson Scott, El Guerche-Séblain Clotilde, Launay Odile
Global Medical, Vaccines, 69007 Sanofi Lyon, France.
Assistance Publique Hôpitaux de Paris (APHP), Hôpital Cochin, CIC Cochin Pasteur, Inserm, 75014 Paris, France.
Vaccines (Basel). 2024 Sep 21;12(9):1079. doi: 10.3390/vaccines12091079.
In this post hoc exploratory study of the APHP-COVIBOOST trial (NCT05124171), we used statistical modeling to describe the evolution of neutralizing antibody (nAb) titers over time, asses its impact on SARS-CoV-2 infection, and explore potential differences between three booster vaccine formulations (D614, B.1.351, and BNT162b2).
Antibody titers were measured for 208 adult participants at day 28, 3 months, and 6 months using a microneutralization assay against different Omicron subvariants. We developed four specific Bayesian statistical models based on a core model, accounting for vaccine-specific antibody decline, boosting of nAb for breakthrough infection, and risk of infection according to nAb levels. The model findings were cross-verified using another validated microneutralization assay.
The decrease in nAb titers was significantly lower for the B.1.351 vaccine than for the other booster formulations. An inverse relationship was found between risk of infection upon exposure and nAb levels. With Omicron BA.1 data, these results translated into a positive relative vaccine efficacy against any infection over 6 months for the B.1.351 vaccine compared to the BNT162b2 (31%) and D614 (21%) vaccines.
Risk of infection decreased with increasing nAb titers for all vaccines. Statistical models predicted significantly better antibody persistence for the B.1.351 booster formulation compared to the other evaluated vaccines.
在这项针对APHP-COVIBOOST试验（NCT05124171）的事后探索性研究中，我们使用统计模型来描述中和抗体（nAb）滴度随时间的变化，评估其对SARS-CoV-2感染的影响，并探索三种加强疫苗配方（D614、B.1.351和BNT162b2）之间的潜在差异。
使用针对不同奥密克戎亚变体的微量中和试验，在第28天、3个月和6个月时测量了208名成年参与者的抗体滴度。我们基于一个核心模型开发了四个特定的贝叶斯统计模型，该模型考虑了疫苗特异性抗体的下降、突破性感染中nAb的增强以及根据nAb水平的感染风险。模型结果使用另一种经过验证的微量中和试验进行交叉验证。
B.1.351疫苗的nAb滴度下降明显低于其他加强疫苗配方。暴露后感染风险与nAb水平之间存在反比关系。根据奥密克戎BA.1数据，与BNT162b2疫苗（31%）和D614疫苗（21%）相比，这些结果转化为B.1.351疫苗在6个月内对任何感染的相对疫苗效力为阳性。
所有疫苗的感染风险均随着nAb滴度的增加而降低。统计模型预测，与其他评估疫苗相比，B.1.351加强疫苗配方的抗体持久性明显更好。
