RESUMEN
Immune responses to COVID-19 vaccination are attenuated in adult solid organ transplant recipients (SOTRs) and additional vaccine doses are recommended for this population. However, whether COVID-19 mRNA vaccine responses are limited in pediatric SOTRs (pSOTRs) compared to immunocompetent children is unknown. Due to SARS-CoV-2 evolution and mutations that evade neutralizing antibodies, T cells may provide important defense in SOTRs who mount poor humoral responses. Therefore, we assessed anti-SARS-CoV-2 IgG titers, surrogate neutralization, and spike (S)-specific T-cell responses to COVID-19 mRNA vaccines in pSOTRs and their healthy siblings (pHCs) before and after the bivalent vaccine dose. Despite immunosuppression, pSOTRs demonstrated humoral responses to both ancestral strain and Omicron subvariants following the primary ancestral strain monovalent mRNA COVID-19 series and multiple booster doses. These responses were not significantly different from those observed in pHCs and significantly higher six months after vaccination than responses in adult SOTRs two weeks post-vaccination. However, pSOTRs mounted limited S-specific CD8+ T-cell responses and qualitatively distinct CD4+ T-cell responses, primarily producing IL-2 and TNF with less IFN-γ production compared to pHCs. Bivalent vaccination enhanced humoral responses in some pSOTRs but did not shift the CD4+ T-cell responses toward increased IFN-γ production. Our findings indicate that S-specific CD4+ T cells in pSOTRs have distinct qualities with unknown protective capacity, yet vaccination produces cross-reactive antibodies not significantly different from responses in pHCs. Given altered T-cell responses, additional vaccine doses in pSOTRs to maintain high titer cross-reactive antibodies may be important in ensuring protection against SARS-CoV-2.
RESUMEN
Background: Cancer is one of the major causes of death and the projection of cancer incidences is essential for future healthcare resources planning. Joinpoint regression and average annual percentage change (AAPC) are common approaches for cancer projection, while time series models, traditional ways of trend analysis in statistics, were considered less popular. This study aims to compare these projection methods on seven types of cancers in 31 geographical jurisdictions. Methods: Using data from 66 cancer registries in the World Health Organization, projection models by joinpoint regression, AAPC, and autoregressive integrated moving average with exogenous variables (ARIMAX) were constructed based on 20 years of cancer incidences. The rest of the data upon 20-years of record were used to validate the primary outcomes, namely, 3, 5, and 10-year projections. Weighted averages of mean-square-errors and of percentage errors on predictions were used to quantify the accuracy of the projection results. Results: Among 66 jurisdictions and seven selected cancers, ARIMAX gave the best 5 and 10-year projections for most of the scenarios. When the ten-year projection was concerned, ARIMAX resulted in a mean-square-error (or percentage error) of 2.7% (or 7.2%), compared with 3.3% (or 15.2%) by joinpoint regression and 7.8% (or 15.0%) by AAPC. All the three methods were unable to give reasonable projections for prostate cancer incidence in the US. Conclusion: ARIMAX outperformed the joinpoint regression and AAPC approaches by showing promising accuracy and robustness in projecting cancer incidence rates. In the future, developments in projection models and better applications could promise to improve our ability to understand the trend of disease development, design the intervention strategies, and build proactive public health system.