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Embacher S, Maertens K, Herzog SA. Half-life Estimation of Pertussis-Specific Maternal Antibodies in (Pre)Term Infants After In-Pregnancy Tetanus, Diphtheria, Acellular Pertussis Vaccination. J Infect Dis 2023; 228:1640-1648. [PMID: 37285482 PMCID: PMC10681861 DOI: 10.1093/infdis/jiad212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/09/2023] [Accepted: 06/06/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND To reduce the risk of pertussis-related morbidity and mortality in early life, an increasing number of countries recommend maternal pertussis vaccination. However, there is limited knowledge about half-lives of vaccine-induced pertussis-specific maternal antibodies, especially in preterm infants, and factors potentially influencing them. METHODS We compared 2 different approaches to provide estimates of the half-lives of pertussis-specific maternal antibodies in infants and explored potential effects on the half-life in 2 studies. In the first approach, we estimated the half-lives per child and used these estimates as responses in linear models. In the second approach, we used linear mixed effect models on a log2 transformed scale of the longitudinal data to use the inverse of the time parameter as an estimate for the half-lives. RESULTS Both approaches provided similar results. The identified covariates partly explain differences in half-life estimates. The strongest evidence we observed was a difference between term and preterm infants, with the preterm infants showing a longer half-life. Among others, a longer interval between vaccination and delivery increases the half-life. CONCLUSIONS Several variables influence the decay speed of maternal antibodies. Both approaches have advantages and disadvantages, while the choice is secondary when assessing the half-life of pertussis-specific antibodies. CLINICAL TRIALS REGISTRATION NCT02408926 and NCT02511327.
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Affiliation(s)
- Stefan Embacher
- Institute for Medical Informatics, Statistics, and Documentation, Medical University of Graz, Graz, Austria
| | - Kirsten Maertens
- Centre for the Evaluation of Vaccination, Vaccine and Infectious Diseases Institute, University of Antwerp, Antwerp, Belgium
| | - Sereina A Herzog
- Institute for Medical Informatics, Statistics, and Documentation, Medical University of Graz, Graz, Austria
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Gomme J, Wanlapakorn N, Ha HTT, Leuridan E, Herzog SA, Maertens K. The Impact of Timing of Pertussis Vaccination During Pregnancy on Infant Antibody Levels at Birth: A Multi-Country Analysis. Front Immunol 2022; 13:913922. [PMID: 35837400 PMCID: PMC9273881 DOI: 10.3389/fimmu.2022.913922] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 06/02/2022] [Indexed: 11/24/2022] Open
Abstract
Background Pertussis vaccination during pregnancy is an effective strategy at reducing pertussis-related morbidity and mortality in infancy and is recommended across several countries. However, the optimal timepoint for vaccination in pregnancy to afford maximal protection to newborns is yet to be elucidated. This multi-country analysis aimed to model the impact of timing of vaccination during pregnancy on infant antibody titers at birth. Methods A multi-country analysis on a cohort of mother-infant pairs (n=698) vaccinated between 19.6-37.1 weeks gestation was conducted. Data taken from four parent studies on pertussis vaccination during pregnancy were modelled using natural cubic splines and linear mixed models to study the association of both gestational age at vaccination and the interval between vaccination and delivery with pertussis-specific cord blood antibody levels after pertussis vaccination during pregnancy. Results Term born infants on average achieve the highest antibody levels at birth if women are vaccinated before 31 weeks’ gestation. When considering both term and preterm deliveries, an interval of at least 7.5 weeks between vaccination and delivery is required to achieve the highest cord blood antibody levels. The models show that vaccinating earlier than these timeframes will also provide the infant with equally high antibody levels at birth. Conclusions Vaccinating in the second and early third trimester results in the highest antibody levels at birth. Vaccinating earlier within this window is needed to provide equal benefits to both term and preterm born infants.
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Affiliation(s)
- Justin Gomme
- Centre for the Evaluation of Vaccination, Vaccine and Infectious Diseases Institute, University of Antwerp, Antwerp, Belgium
| | - Nasamon Wanlapakorn
- Department of Pediatrics, Center of Excellence in Clinical Virology, Bangkok, Thailand
- Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | | | - Elke Leuridan
- Centre for the Evaluation of Vaccination, Vaccine and Infectious Diseases Institute, University of Antwerp, Antwerp, Belgium
| | - Sereina Annik Herzog
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Diseases Institute, University of Antwerp, Antwerp, Belgium
- *Correspondence: Kirsten Maertens, ; Sereina Annik Herzog,
| | - Kirsten Maertens
- Centre for the Evaluation of Vaccination, Vaccine and Infectious Diseases Institute, University of Antwerp, Antwerp, Belgium
- *Correspondence: Kirsten Maertens, ; Sereina Annik Herzog,
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The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection. STATS 2022. [DOI: 10.3390/stats5020029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
The limit of detection (LOD) is commonly encountered in observational studies when one or more covariate values fall outside the measuring ranges. Although the complete-case (CC) approach is widely employed in the presence of missing values, it could result in biased estimations or even become inapplicable in small sample studies. On the other hand, approaches such as the missing indicator (MDI) approach are attractive alternatives as they preserve sample sizes. This paper compares the effectiveness of different alternatives to the CC approach under different LOD settings with a survival outcome. These alternatives include substitution methods, multiple imputation (MI) methods, MDI approaches, and MDI-embedded MI approaches. We found that the MDI approach outperformed its competitors regarding bias and mean squared error in small sample sizes through extensive simulation.
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Orije MRP, García-Fogeda I, Van Dyck W, Corbière V, Mascart F, Mahieu L, Hens N, Van Damme P, Cools N, Ogunjimi B, Maertens K, Leuridan E. Impact of maternal pertussis antibodies on the infants' cellular immune responses. Clin Infect Dis 2021; 75:442-452. [PMID: 34849638 DOI: 10.1093/cid/ciab972] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Indexed: 11/14/2022] Open
Abstract
INTRODUCTION Maternal antibody interference of the infant's humoral immune responses raises some concern to the strategy of maternal Tdap (tetanus, diphtheria, acellular pertussis [aP]) vaccination. This study assessed the impact of maternal Tdap antibodies on the infant's pertussis-specific T lymphocyte responses following infant vaccination with an aP containing vaccine, in a term and preterm born cohort. METHODS Heparin samples (±0.5mL) were conveniently drawn from infants of a Belgian prospective cohort study (N=79, NCT02511327), including Tdap vaccinated (Boostrix®) and non-vaccinated women (no Tdap vaccine in the last 5 years) that delivered at term or prematurely. Sampling was performed before and one month after primary (8-12-16 weeks) and booster vaccination (13 or 15 months) with DTaP-IPV-HB-PRP~T vaccine (Hexyon®). Pertussis toxin (PT)-specific CD3 +, CD3 +CD4 + and CD3 +CD8 + lymphoblasts and their cytokine secretions were measured using a flow cytometric assay on whole blood (FASCIA) and multiplex technology (Meso Scale Discovery), respectively. RESULTS 57% of all infants were considered PT-specific CD3 +CD4 + lymphoblasts responders after primary and booster vaccination, whereas 17% were CD3 +CD8 + lymphoblast responders. IFN-γ, IL-13, IL-17A and IL-5 cytokine secretions after primary and booster vaccination were indicative of a mixed T helper (Th) 1/Th2/Th17 cell profile. Lymphoblast and cytokine levels were comparable between term and preterm infants. Non-responders for IL-13 after booster vaccination had higher maternal PT IgG levels at birth when compared to responders. CONCLUSIONS Term and preterm born infants are capable of inducing Th1, Th2 and Th17 responses after aP vaccination, yet maternal vaccination modulate these responses. Evaluation of this effect in larger trials is needed.
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Affiliation(s)
- Marjolein R P Orije
- Centre for the Evaluation of Vaccination (CEV); Vaccine & Infectious Diseases Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Irene García-Fogeda
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID); Vaccine & Infectious Diseases Institute (VAXINFECTIO); University of Antwerp, Antwerp, Belgium
| | - Wouter Van Dyck
- Centre for the Evaluation of Vaccination (CEV); Vaccine & Infectious Diseases Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Véronique Corbière
- Laboratory of Vaccinology and Mucosal Immunity, Université Libre de Bruxelles (U.L.B.), Faculty of Medicine, Belgium
| | - Françoise Mascart
- Laboratory of Vaccinology and Mucosal Immunity, Université Libre de Bruxelles (U.L.B.), Faculty of Medicine, Belgium
| | - Ludo Mahieu
- Department of Paediatrics, Division of Neonatology; University Hospital Antwerp, Antwerp, Belgium
| | - Niel Hens
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID); Vaccine & Infectious Diseases Institute (VAXINFECTIO); University of Antwerp, Antwerp, Belgium.,Interuniversity Institute of Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Pierre Van Damme
- Centre for the Evaluation of Vaccination (CEV); Vaccine & Infectious Diseases Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Nathalie Cools
- Immune Regulation and tolerance-inducing Strategies (IRiS); Vaccine & Infectious Diseases Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID); Vaccine & Infectious Diseases Institute (VAXINFECTIO); University of Antwerp, Antwerp, Belgium.,Antwerp Center for Translational Immunology and Virology (ACTIV); Vaccine & Infectious Diseases Institute (VAXINFECTIO); University of Antwerp, Antwerp, Belgium.,Department of Paediatrics; University Hospital Antwerp, Antwerp, Belgium
| | - Kirsten Maertens
- Centre for the Evaluation of Vaccination (CEV); Vaccine & Infectious Diseases Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Elke Leuridan
- Centre for the Evaluation of Vaccination (CEV); Vaccine & Infectious Diseases Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
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Tran TMP, Abrams S, Aerts M, Maertens K, Hens N. Measuring association among censored antibody titer data. Stat Med 2021; 40:3740-3761. [PMID: 33942345 PMCID: PMC8251995 DOI: 10.1002/sim.8995] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 12/26/2020] [Accepted: 04/03/2021] [Indexed: 12/21/2022]
Abstract
Censoring due to a limit of detection or limit of quantification happens quite often in many medical studies. Conventional approaches to deal with censoring when analyzing these data include, for example, the substitution method and the complete case (CC) analysis. More recently, maximum likelihood estimation (MLE) has been increasingly used. While the CC analysis and the substitution method usually lead to biased estimates, the MLE approach appears to perform well in many situations. This article proposes an MLE approach to estimate the association between two measurements in the presence of censoring in one or both quantities. The central idea is to use a copula function to join the marginal distributions of the two measurements. In various simulation studies, we show that our approach outperforms existing conventional methods (CC and substitution analyses). In addition, rank‐based measures of global association such as Kendall's tau or Spearman's rho can be studied, hence, attention is not only confined to Pearson's product‐moment correlation coefficient capturing solely linear association. We have shown in our simulations that our approach is robust to misspecification of the copula function or marginal distributions given a small association. Furthermore, we propose a straightforward MLE method to fit a (multiple) linear regression model in the presence of censoring in a covariate or both the covariate and the response. Given the marginal distribution of the censored covariate, our method outperforms conventional approaches. We also compare and discuss the performance of our method with multiple imputation and missing indicator model approaches.
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Affiliation(s)
- Thao M P Tran
- I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Steven Abrams
- I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium.,Global Health Institute, Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium
| | - Marc Aerts
- I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Kirsten Maertens
- Centre for Evaluation of Vaccination, Vaccine and Infectious Disease Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Niel Hens
- I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium.,Global Health Institute, Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
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