Literature DB >> 16158409

A model for immunological correlates of protection.

Andrew J Dunning1.   

Abstract

Immunological assays measure characteristics of the immune system, such as antibody levels, specific to certain diseases. High assay values are often associated with protection from disease. A question of interest is how the relationship between assay values and subsequent development of disease should be quantitatively modelled. Existing approaches successfully model the relationship for high assay values, where the probability of developing disease is low. However at low assay values, the probability of developing disease is more closely associated with factors such as disease prevalence rates and an individual's chance of exposure to infection; these are less well captured by existing models. This paper presents a model that accommodates both assay values and factors independent of assay values, enabling protection from disease to be modelled over the whole range of assay values and proposing a method for predicting the efficacy of a vaccine from the assays of vaccinees and non-vaccinees.

Mesh:

Substances:

Year:  2006        PMID: 16158409     DOI: 10.1002/sim.2282

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  26 in total

1.  A new approach to estimate vaccine efficacy based on immunogenicity data applied to influenza vaccines administered by the intradermal or intramuscular routes.

Authors:  Laurent Coudeville; Philippe Andre; Fabrice Bailleux; Françoise Weber; Stanley Plotkin
Journal:  Hum Vaccin       Date:  2010-10-01

2.  Validation and evaluation of serological correlates of protection for inactivated enterovirus 71 vaccine in children aged 6-35 months.

Authors:  Pengfei Jin; Jingxin Li; Xuefeng Zhang; Fangyue Meng; Yang Zhou; Xuejun Yao; Zhengkai Gan; Fengcai Zhu
Journal:  Hum Vaccin Immunother       Date:  2016-01-11       Impact factor: 3.452

3.  Identification of immune correlates of protection in Shigella infection by application of machine learning.

Authors:  Jorge M Arevalillo; Marcelo B Sztein; Karen L Kotloff; Myron M Levine; Jakub K Simon
Journal:  J Biomed Inform       Date:  2017-08-09       Impact factor: 6.317

4.  NONPARAMETRIC INFERENCE FOR IMMUNE RESPONSE THRESHOLDS OF RISK IN VACCINE STUDIES.

Authors:  Kevin M Donovan; Michael G Hudgens; Peter B Gilbert
Journal:  Ann Appl Stat       Date:  2019-06-17       Impact factor: 2.083

5.  Association between antibody titers and protection against influenza virus infection within households.

Authors:  Tim K Tsang; Simon Cauchemez; Ranawaka A P M Perera; Guy Freeman; Vicky J Fang; Dennis K M Ip; Gabriel M Leung; Joseph Sriyal Malik Peiris; Benjamin J Cowling
Journal:  J Infect Dis       Date:  2014-03-26       Impact factor: 5.226

6.  Relationship between haemagglutination-inhibiting antibody titres and clinical protection against influenza: development and application of a bayesian random-effects model.

Authors:  Laurent Coudeville; Fabrice Bailleux; Benjamin Riche; Françoise Megas; Philippe Andre; René Ecochard
Journal:  BMC Med Res Methodol       Date:  2010-03-08       Impact factor: 4.615

7.  Correlation of cellular immune responses with protection against culture-confirmed influenza virus in young children.

Authors:  Bruce D Forrest; Michael W Pride; Andrew J Dunning; Maria Rosario Z Capeding; Tawee Chotpitayasunondh; John S Tam; Ruth Rappaport; John H Eldridge; William C Gruber
Journal:  Clin Vaccine Immunol       Date:  2008-04-30

8.  Evaluating a surrogate endpoint at three levels, with application to vaccine development.

Authors:  Peter B Gilbert; Li Qin; Steven G Self
Journal:  Stat Med       Date:  2008-10-15       Impact factor: 2.373

9.  The cost-effectiveness and value of information of three influenza vaccination dosing strategies for individuals with human immunodeficiency virus.

Authors:  Bohdan Nosyk; Behnam Sharif; Huiying Sun; Curtis Cooper; Aslam H Anis
Journal:  PLoS One       Date:  2011-12-06       Impact factor: 3.240

10.  A threshold method for immunological correlates of protection.

Authors:  Xuan Chen; Fabrice Bailleux; Kamal Desai; Li Qin; Andrew J Dunning
Journal:  BMC Med Res Methodol       Date:  2013-03-01       Impact factor: 4.615

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.