P0701 Trans-continental analysis of determinants of response to COVID-19 vaccination in 2268 patients with Inflammatory Bowel Disease
Bibliographic record
Abstract
Abstract Background Little is known about the relative efficacy of available COVID-19 vaccine types around the world in immune-compromised patients with inflammatory bowel disease (IBD).1,2 We aimed to compare antibody responses to SARS-CoV-2 in patients with IBD who had received mRNA, vector, and inactivated virus vaccines and the impact of medications thereof among multinational sites. Methods Serum samples taken after 1st, 2nd, and 3rd doses of COVID-19 vaccines from patients with IBD seen at 13 sites across Europe, Asia, and North America were prospectively collected between January 2021 and November 2022. We measured anti-Spike (S) and anti-nucleocapsid (N) antibody levels. To identify determinants of serological responses to vaccination, both univariate and multivariate analyses were conducted. Results There were a total of 2,268 patients, including 1,279 Crohn’s disease (CD) and 868 ulcerative colitis (UC) (Table 1). 1552 patients had an mRNA vaccine, 590 an adenovirus vaccine, and 98 an inactivated virus vaccine. At 14-84 days, 85-168 days, and 169+ days after completing a full vaccination series, the proportion of patients who were positive for anti-S antibodies were 98% (n=922/939), 96% (n=700/731), and 98% (n=677/692) for mRNA, 95% (n=378/396), 89% (n=55/62), and 97% (n=33/34) for adenovirus, and 72% (n=21/29), 84% (n=31/37), and 95% (n=55/58) for inactivated virus vaccine, respectively. On univariate analysis, rates of serological response were highest in those who received mRNA vaccines at all six time periods (Figure 1a). Adenovirus vaccine response rates closely resembled the rate of seropositivity in mRNA vaccinated patients. In contrast, inactivated vaccines had a significantly lower percent of patients reaching seropositivity until 169 days or more after the second vaccine dose (p<0.001). Anti-TNF monotherapy and immunomodulator monotherapy were associated with the ability to obtain maximum antibody titres. However, this difference is ablated after the 3rd dose (Figure 1c). Univariate analysis also implicated geographical site, male sex, and a diagnosis of ulcerative colitis as determinants of serological responses. On multi-variable analysis, vaccine type (p < 0.001 at every time point analysed) and the use of immunomodulators (p <0.001 at time points 1 and 3) were confirmed as independent determinants of vaccine responsiveness across the study populations. Conclusion Our data suggests that while there is variability between geographical centers, the response rates are high worldwide, and the key determinants of serological response to vaccines are the use of immunosuppressive agents and vaccine class.3 These data are important considerations for better pandemic preparedness in the IBD community worldwide. References (1)Wong SY, Wellens J, Helmus D, et al. Geography Influences Susceptibility to SARS-CoV-2 Serological Response in Patients With Inflammatory Bowel Disease: Multinational Analysis From the ICARUS-IBD Consortium. Inflamm Bowel Dis. 2023;29(11):1693-1705. doi:10.1093/ibd/izad097 (2)Goodyear CS, Patel A, Barnes E, et al. Immunogenicity of third dose COVID-19 vaccine strategies in patients who are immunocompromised with suboptimal immunity following two doses (OCTAVE-DUO): an open-label, multicentre, randomised, controlled, phase 3 trial. Lancet Rheumatol. 2024;6(6):e339-e351. doi:10.1016/S2665-9913(24)00065-1 (3)Barnes E, Goodyear CS, Willicombe M, et al. SARS-CoV-2-specific immune responses and clinical outcomes after COVID-19 vaccination in patients with immune-suppressive disease. Nat Med. 2023;29(7):1760-1774. doi:10.1038/s41591-023-02414-4
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
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".