Vaccine response following anti-CD20 therapy: a systematic review and meta-analysis of 905 patients
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Bibliographic record
Abstract
The objective of this study was to perform a systematic review of the literature on vaccine responsiveness in patients who have received anti-CD20 therapy. PubMed and EMBASE were searched up to 4 January 2021 to identify studies of vaccine immunogenicity in patients treated with anti-CD20 therapy, including patients with hematologic malignancy or autoimmune disease. The primary outcomes were seroprotection (SP), seroconversion (SC), and/or seroresponse rates for each type of vaccine reported. As the pandemic influenza vaccine (2009 H1N1) has standardized definitions for SP and SC, and represented a novel primary antigen similar to the COVID-19 vaccine, meta-analysis was conducted for SC of studies of this vaccine. Pooled estimates, relative benefit ratios (RBs), and 95% confidence intervals (CIs) were calculated using a random-effects model. Thirty-eight studies (905 patients treated with anti-CD20 therapy) were included (19 studies of patients with hematologic malignancies). Patients on active (<3 months since last dose) anti-CD20 therapy had poor responses to all types of vaccines. The pooled estimate for SC after 1 pandemic influenza vaccine dose in these patients was 3% (95% CI, 0% to 9%), with an RB of 0.05 (95% CI, 0-0.73) compared with healthy controls and 0.22 (95% CI, 0.09-0.56) compared with disease controls. SC compared with controls seems abrogated for at least 6 months following treatment (3-6 months post anti-CD20 therapy with an RB of 0.50 [95% CI, 0.24-1.06] compared with healthy and of 0.44 [95% CI, 0.23-0.84] compared with disease controls). For all vaccine types, response to vaccination improves incrementally over time, but may not reach the level of healthy controls even 12 months after therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it