Determinants of durable humoral and T cell immunity in myeloma patients following <scp>COVID</scp>‐19 vaccination
Bibliographic record
Abstract
OBJECTIVE: To describe determinants of persisting humoral and cellular immune response to the second COVID-19 vaccination among patients with myeloma. METHODS: This is a prospective, observational study utilising the RUDYstudy.org platform. Participants reported their second and third COVID-19 vaccination dates. Myeloma patients had an Anti-S antibody level sample taken at least 21 days after their second vaccination and a repeat sample before their third vaccination. RESULTS: 60 patients provided samples at least 3 weeks (median 57.5 days) after their second vaccination and before their third vaccination (median 176.0 days after second vaccine dose). Low Anti-S antibody levels (<50 IU/mL) doubled during this interval (p = .023) and, in the 47 participants with T-spot data, there was a 25% increase negative T-spot tests (p = .008). Low anti-S antibody levels prior to the third vaccination were predicted by lower Anti-S antibody level and negative T-spot status after the second vaccine. Independent determinants of a negative T-spot included increasing age, previous COVID infection, high CD4 count and lower percentage change in Anti-S antibody levels. CONCLUSIONS: Negative T-spot results predict low Anti-S antibody levels (<50 IU/mL) following a second COVID-19 vaccination and a number of biomarkers predict T cell responses in myeloma patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".