Immune response after SARS-CoV-2 vaccination in patients with inflammatory immune-mediated diseases receiving immunosuppressive treatment
Bibliographic record
Abstract
BACKGROUND: Real world data on the response to the SARS-CoV-2 vaccine in patients with immunomediated diseases (IMIDs) treated with immunesuppressants is of great interest because vaccine response may be impaired. The main aim was to study the humoral and cellular immune response after SARS-CoV-2 vaccination in patients with IMIDs treated with immunosuppressants. The secondary aim was to describe the frequency of SARS-CoV-2 infections after vaccination in these patients. MATERIAL AND METHODS: This is an observational study including 86 patients with IMIDs. All patients were treated with biologic or targeted synthetic disease-modifying antirheumatic drugs [b/tsDMARDs: TNF inhibitors (TNFi), rituximab, anti-interleukin 6 receptor (anti-IL6R) or JAK inhibitors (JAKi)]. Demographic and clinical information were collected. After 4-6 weeks of 2nd and 3rd vaccine doses, humoral response was assessed using the Thermo Scientific ELiA SARS-CoV-2-Sp1 IgG Test. Also, in patients with serum SARS-CoV-2 antibody levels under 100UI/ml, cellular response was analyzed using the QuantiFERON SARS-CoV-2 Starter Pack. RESULTS: A total of 86 patients under b/tsDMARDs and 38 healthy controls were included. Most patients received TNFi (45 with TNFi, 31 with rituximab, 5 with anti-IL6R and 5 with JAKi). SARS-CoV-2 antibodies (Ab) were present in an 86% of patients with IMIDs and in 100% healthy controls (p = 0.017). However, 12 (14%) patients had undetectable SARS-CoV-2 Ab levels, all treated with rituximab. In addition, SARS-CoV-2 Ab (IU/ml) were statistically lower in patients (Mdn (IQR): 59.5 (17-163) in patients vs 625 (405-932) in controls, p < 0.001). Patients treated with rituximab had lower Ab levels than those treated with TNFi and controls (p < 0.001). The cellular response to SARS-CoV-2 vaccine was evaluated in 30 patients. Eleven patients had a positive cellular response, being more frequent in patients treated with rituximab (p = 0.03). SARS-CoV-2 infection was reported in 43% of patients and 34% of controls after vaccination. Only 6 (7%) patients required hospitalization, most of whom treated with rituximab (67%). CONCLUSION: SARS-CoV-2 antibody levels were lower in patients than in controls, especially in patients treated with rituximab. A cellular response can be detected despite having a poor humoral response. Severe infections in vaccinated patients with IMIDs are rare, and are observed mainly in patients treated with rituximab.
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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) | 0.001 | 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) | 0.001 | 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".