A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal Immunization

Background/Objectives: Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants worldwide. Maternal immunization to protect younger infants is supported by evidence that virus-neutralizing antibodies, which are efficiently transferred across the placenta from m...

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Published in:Vaccines
Main Authors: Bing Cai, Yili Chen, Yasmeen Agosti, Beate Schmoele-Thoma, Kenneth Koury, Kathrin U. Jansen, William C. Gruber, Philip R. Dormitzer, Kena A. Swanson
Format: Article
Language:English
Published: MDPI AG 2024-11-01
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Online Access:https://www.mdpi.com/2076-393X/12/12/1351
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author Bing Cai
Yili Chen
Yasmeen Agosti
Beate Schmoele-Thoma
Kenneth Koury
Kathrin U. Jansen
William C. Gruber
Philip R. Dormitzer
Kena A. Swanson
author_facet Bing Cai
Yili Chen
Yasmeen Agosti
Beate Schmoele-Thoma
Kenneth Koury
Kathrin U. Jansen
William C. Gruber
Philip R. Dormitzer
Kena A. Swanson
author_sort Bing Cai
collection DOAJ
container_title Vaccines
description Background/Objectives: Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants worldwide. Maternal immunization to protect younger infants is supported by evidence that virus-neutralizing antibodies, which are efficiently transferred across the placenta from mother to fetus, are a primary immune mediator of protection. In maternal RSV vaccine studies, estimates of correlates of protection are elusive because many factors of maternal–fetal immunobiology and disease characteristics must be considered for the estimates. Methods: We developed statistical models that aims to predict vaccine efficacy (VE) in infants following maternal immunization by including quantifiable covariates of the antibody titer distribution of the mother (pre- and post-immunization), the transplacental transfer ratio of IgG antibodies, the rate of antibody decay, and RSV disease incidence rate, all of which are season- and time-dependent and vary by infant age. Result: Our model shows that integrating the lower respiratory tract disease risk based on infant airway diameter and associated airway resistance is critical to appropriately model predicted infant VE. The VE predictions by our models, which preceded maternal RSV prefusion F vaccine efficacy trial primary readouts, closely align with the VE outcomes of these field studies. Conclusion: Our models successfully predicted VE of the RSV maternal vaccines and have potential use in modeling the clinical trial out-comes of other respiratory disease vaccines where maternal antibodies play a role in the protection of newborns.
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spelling doaj-art-888cc52b525f4068bf239df014f9fa212025-08-20T00:36:29ZengMDPI AGVaccines2076-393X2024-11-011212135110.3390/vaccines12121351A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal ImmunizationBing Cai0Yili Chen1Yasmeen Agosti2Beate Schmoele-Thoma3Kenneth Koury4Kathrin U. Jansen5William C. Gruber6Philip R. Dormitzer7Kena A. Swanson8Vaccine Research and Development, Pfizer Inc., Collegeville, PA 19426, USAClinical Development and Operations, Pfizer Inc., Collegeville, PA 19426, USAChief Medical Affairs Office, Pfizer Inc., Collegeville, PA 19426, USAVaccine Research and Development, Pfizer Inc., Pearl River, NY 10965, USAVaccine Research and Development, Pfizer Inc., Pearl River, NY 10965, USAVaccine Research and Development, Pfizer Inc., Pearl River, NY 10965, USAVaccine Research and Development, Pfizer Inc., Pearl River, NY 10965, USAVaccine Research and Development, Pfizer Inc., Pearl River, NY 10965, USAVaccine Research and Development, Pfizer Inc., Pearl River, NY 10965, USABackground/Objectives: Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants worldwide. Maternal immunization to protect younger infants is supported by evidence that virus-neutralizing antibodies, which are efficiently transferred across the placenta from mother to fetus, are a primary immune mediator of protection. In maternal RSV vaccine studies, estimates of correlates of protection are elusive because many factors of maternal–fetal immunobiology and disease characteristics must be considered for the estimates. Methods: We developed statistical models that aims to predict vaccine efficacy (VE) in infants following maternal immunization by including quantifiable covariates of the antibody titer distribution of the mother (pre- and post-immunization), the transplacental transfer ratio of IgG antibodies, the rate of antibody decay, and RSV disease incidence rate, all of which are season- and time-dependent and vary by infant age. Result: Our model shows that integrating the lower respiratory tract disease risk based on infant airway diameter and associated airway resistance is critical to appropriately model predicted infant VE. The VE predictions by our models, which preceded maternal RSV prefusion F vaccine efficacy trial primary readouts, closely align with the VE outcomes of these field studies. Conclusion: Our models successfully predicted VE of the RSV maternal vaccines and have potential use in modeling the clinical trial out-comes of other respiratory disease vaccines where maternal antibodies play a role in the protection of newborns.https://www.mdpi.com/2076-393X/12/12/1351RSVviral infectioninfantsairway resistancemodelingvaccine efficacy
spellingShingle Bing Cai
Yili Chen
Yasmeen Agosti
Beate Schmoele-Thoma
Kenneth Koury
Kathrin U. Jansen
William C. Gruber
Philip R. Dormitzer
Kena A. Swanson
A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal Immunization
RSV
viral infection
infants
airway resistance
modeling
vaccine efficacy
title A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal Immunization
title_full A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal Immunization
title_fullStr A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal Immunization
title_full_unstemmed A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal Immunization
title_short A Statistical Model to Predict Protection Against Infant Respiratory Syncytial Virus Disease Through Maternal Immunization
title_sort statistical model to predict protection against infant respiratory syncytial virus disease through maternal immunization
topic RSV
viral infection
infants
airway resistance
modeling
vaccine efficacy
url https://www.mdpi.com/2076-393X/12/12/1351
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