Outcome prediction of the measles vaccination in healthcare employees - A. A. Ereshchenko; O. A. Gusyakova; N. B. Migacheva; F. N. Gilmiyarova; A. V. Lyamin (Медицинская иммунология, 2023)
Vaccination is the only guarantee for elimination of measles infection. Healthcare workers have a 13- to 19-fold higher risk for contracting measles than the general population. The number of individuals in the population who did not respond to vaccination is up to 10%, and their accumulation may lead to an outbreak of the infection. The aim of our research was to find potential predictors of arising post-vaccination measles antibodies in the panel of biochemical and immunological serum markers in healthcare workers. The group of healthcare workers (n = 76) aged from 19 to 51 years, with proven absence of pre-existing anti-measles antibodies were twice vaccinated 3 months apart with live measles culture vaccine (SPA “Microgen”, Russia). Measles-specific IgG, total IgG, IgM, IgA, IFNγ, IL-6, CRP, total protein, ALT, AST, total bilirubin, urea, creatinine, protein fractions were determined before vaccination, 1 month after vaccination, 1 month following revaccination, 1 year after revaccination. ROC analysis was used to gain access to the diagnostic performance of quantitative variables in predicting a categorical outcome. Development of a predictive probability model for the binary outcome was carried out using logistic regression. IFNγ, total IgG, IgM, total bilirubin, ALT activity at various post-immunization stages may be considered potential laboratory predictors of measles vaccination failures in healthcare workers. Meanwhile, the contents of pre-vaccination IFNγ, and IgG to measles virus after first vaccination proved to be most informative indexes, which formed the basis for the development of regression models predicting the risk of both primary and secondary vaccination failures. These models allowed to develop algorithm for predicting failures of the measles vaccination in healthcare workers that can be used for detection of persons at risk for non-forming specific humoral immunity. This algorithm is primarily focused on search for the persons who have not responded to measles vaccination, including subjects with probable immunodeficiency conditions. We do not exclude that, on the basis of revealed predictors following measles vaccination, it would be possible to build prognostic models of vaccination efficiency for other vaccinemanaged infections.