Severe Acute Respiratory Syndrome Coronavirus 2 Vaccine Immunogenicity among Chimeric Antigen Receptor T Cell Therapy Recipients
Bibliographic record
Abstract
Patients receiving chimeric antigen receptor T cell (CAR-T) therapy may have impaired humoral responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccinations owing to their underlying hematologic malignancy, prior lines of therapy, and CAR-T-associated hypogammaglobulinemia. Comprehensive data on vaccine immunogenicity in this patient population are limited. A single-center retrospective study of adults receiving CD19 or BCMA-directed CAR-T therapy for B cell non-Hodgkin lymphoma or multiple myeloma was conducted. Patients received at least 2 doses of SARS-CoV-2 vaccination with BNT162b2 or mRNA-1273 or 1 dose of Ad26.COV2.S and had SARS-CoV-2 anti-spike antibody (anti-S IgG) levels measured at least 1 month after the last vaccine dose. Patients were excluded if they received SARS-CoV-2 monoclonal antibody therapy or immunoglobulin within 3 months of the index anti-S titer. The seropositivity rate (assessed by an anti-S assay cutoff of ≥.8 U/mL in the Roche assay) and median anti-S IgG titers were analyzed. Fifty patients were included in the study. The median age was 65 years (interquartile range [IQR], 58 to 70 years), and the majority were male (68%). Thirty-two participants (64%) had a positive antibody response, with a median titer of 138.5 U/mL (IQR, 11.61 to 2541 U/mL). Receipt of ≥3 vaccines was associated with a significantly higher anti-S IgG level. Our study supports current guidelines for SARS-CoV-2 vaccination among recipients of CAR-T therapy and demonstrates that a 3-dose primary series followed by a fourth booster increases antibody levels. However, the relatively low magnitude of titers and low percentage of nonresponders demonstrates that further studies are needed to optimize vaccination timing and determine predictors of vaccine response in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".