When Should I Get My Next COVID-19 Vaccine? Data From the Surveillance of Responses to COVID-19 Vaccines in Systemic Immune-Mediated Inflammatory Diseases (SUCCEED) Study
Bibliographic record
Abstract
OBJECTIVE: To determine how serologic responses to coronavirus disease 2019 (COVID-19) vaccination and infection in immune-mediated inflammatory disease (IMID) are affected by time since last vaccination and other factors. METHODS: Post-COVID-19 vaccination, data, and dried blood spots or sera were collected from adults with rheumatoid arthritis, inflammatory bowel disease, systemic lupus erythematosus, ankylosing spondylitis and spondylarthritis, and psoriasis and psoriatic arthritis. The first sample was collected at enrollment, then at 2 to 4 weeks and 3, 6, and 12 months after the latest vaccine dose. Multivariate generalized estimating equation regressions (including medications, demographics, and vaccination history) evaluated serologic response, based on log-transformed anti-receptor-binding domain (RBD) IgG titers; we also measured antinucleocapsid (anti-N) IgG. RESULTS: Positive associations for log-transformed anti-RBD titers were seen with female sex, number of doses, and self-reported COVID-19 infections in 2021 to 2023. Negative associations were seen with prednisone, anti-tumor necrosis factor agents, and rituximab. Over the 2021-2023 period, most (94%) of anti-N positivity was associated with a self-reported infection in the 3 months prior to testing. From March 2021 to February 2022, anti-N positivity was present in 5% to 15% of samples and was highest in the post-Omicron era, with antinucleocapsid positivity trending to 30% to 35% or higher as of March 2023. Anti-N positivity in IMID remained lower than Canada's general population seroprevalence (> 50% in 2022 and > 75% in 2023). Time since last vaccination was negatively associated with log-transformed anti-RBD titers, particularly after 210 days. CONCLUSION: Ours is the first pan-Canadian IMID assessment of how vaccine history and other factors affect serologic COVID-19 vaccine responses. These findings may help individuals personalize vaccination decisions, including consideration of additional vaccination when > 6 months has elapsed since last COVID-19 vaccination/infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".