Factors Affecting COVID-19 Vaccine Seroconversion

Descriptive statistics are reported as count (percent) for categorical variables and as median (interquartile range [IQR]) for continuous variables. Demographics and baseline variables are also reported by IgG antibody status before/after receiving 3V dose.
To assess the association between each individual characteristics and seroconversion status, patients were placed into two groups based on IgG antibody status pre and post the 3V dose, (−/+) and (−/−). Categorical variables were compared using a Chi-squared test or a Fisher’s exact test, as appropriate, and continuous variables using a Mann–Whitney U-test. P-value less than 0.05 were used as an indicator of statistical significance. For categorical variables with more than two levels, P-values were calculated for both the global and the pairwise comparisons. Odds ratios (OR) are displayed as measures of association for all categorical variables. Logistic regressions were used to measure the association between HM condition and seroconversion. A multivariable logistic regression model was run to assess significant associations fitting seroconversion on cancer diagnosis adjusting for age, sex, and days between dose 2 and dose 3. Myeloid leukemia and Hodgkin lymphoma were eliminated from the model due to small cell size (Table 4). Achieving seroconversion (−/+) was used as the reference outcome. Male, White, non-Hispanic/Latino, receiving Pfizer-BioNTech as the 3V dose, having previous COVID-19 infection, and NHL were used as reference groups for the respective variables for the OR calculation [3 (link)]. NHL was chosen as the reference group because it is the most common condition in our dataset. Data management and analysis were performed by the study team using R 4.1.1 (R Core Team, 2021).