Predictors of Hepatitis B Surface Antigen Titers two decades after vaccination in a cohort of students and post-graduates of the Medical School at the University of Palermo, Italy

Introduction and objective The introduction of a vaccine against hepatitis B virus (HBV) for newborn babies in Italy in 1991, extended to 12-year-old children for the first 12 years of application, has been a major achievement in terms of the prevention of HBV infection. The objective of this study was to analyse the long-term immunogenicity and effectiveness of HBV vaccination among healthcare students with different working seniorities. Material and Methods A cross-sectional observational study of undergraduate and postgraduate students attending the Medical School of the University of Palermo was conducted from January 2014 – July 2016. HBV serum markers were performed with commercial chemiluminescence assays. Categorical variables were analyzed using the chi-square test (Mantel–Haenszel), whereas means were compared by using the Student’s t test. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were also calculated by a multivariable logistic regression, using a model constructed to examine predictors of anti-HBs titer above 10 mIU/mL, assumed as protective. Results Of the 2,114 subjects evaluated – all vaccinated at infancy or at the age of 12 years and were HBsAg/anti-HBc negative – 806 (38.1%) had an anti-HBs titre <10 IU/L. The latter were younger, more likely to be attending a healthcare profession school (i.e., nursing and midwifery), than a medical postgraduate level school, and more likely to have been vaccinated in infancy (p <0.001, 95% CI 2.63–5.26, adjusted OR 3.70). Conclusions The results of the study suggest that assessment of HBV serum markers in workers potentially exposed to hospital infections is useful for identifying small numbers of unvaccinated subjects, or vaccinated subjects with low antibody titre, all of whom should be referred to a booster series of vaccinations.

Abstract licence: CC BY-NC

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.