Pneumococcal vaccination during chemotherapy in children treated for acute lymphoblastic leukemia
Bibliographic record
Abstract
BACKGROUND: Children treated for acute lymphoblastic leukemia (ALL) are at high risk of invasive pneumococcal disease (IPD). We assessed immunity to S. pneumoniae among children after ALL treatment, and the impact of pneumococcal immunization during and after chemotherapy. METHODS: We performed an observational retrospective study of children treated for ALL at a single center. All children were fully immunized with three routine doses of pneumococcal conjugate vaccine (PCV) prior to ALL diagnosis. Children from Group 1 received a 13-valent PCV (PCV13) dose during the maintenance phase as well as a PCV13 booster after completing chemotherapy, while Group 2 only received the postchemotherapy dose. Serologic testing was performed after chemotherapy and again after the postchemotherapy dose. A serotype-specific antibody level ≥0.35 μg/ml was considered protective, and patients with protective levels for ≥70% of serotypes in the PCV7 vaccine were defined as seroprotected. RESULTS: A total of 71 children (median age 46 months, range 12-160) were included. At the end of chemotherapy, 53.1% of children in Group 1 (17/32) and 25.6% in Group 2 (10/39) were seroprotected (p = .018). After the postchemotherapy booster, seroprotection rates increased to 96.9% in Group 1 (31/32) and 100% in Group 2. CONCLUSIONS: Rates of pneumococcal seroprotection among children with ALL are low following chemotherapy, despite prior routine immunization. A PCV booster during chemotherapy may shorten the period of susceptibility to IPD in some children. However, irrespective of a booster during chemotherapy, a PCV dose postchemotherapy appears sufficient to confer high rates of seroprotection against IPD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".