1601. Effect of Preemptive Rituximab Therapy on Epstein–Barr Reactivation in Allogenic Hematopoietic Stem Cell Pediatric Transplants
Bibliographic record
Abstract
Children with Epstein–Barr virus (EBV) viremia after hematopoietic stem cell transplantation (HSCT) are at increased risk of post-transplant lymphoproliferative disease (PTLD). Our aim was to assess whether pre-emptive rituximab reduced EBV-viral load (EBV-VL) and the risk of developing PTLD. We retrospectively included all children who had a positive EBV-VL within 12 months after an allogenic HSCT (2007–2015) in a single tertiary pediatric hospital. Whole blood EBV-VL was monitored weekly using a real-time PCR, during the first 100 days after HSCT and then monthly until 6 months post-HSCT or until EBV-VL became undetectable. EBV-VL clearance was defined as two negative EBV-VL at least 1 week apart. Pre-emptive rituximab was defined as a treatment administered before the occurrence of PTLD. We determined the impact of pre-emptive rituximab on EBV-VL clearance, using a marginal structural cox model, adjusting for age at transplant, time between transplant and first positive EBV-VL, in-vivo T-cell depletion at induction, value of EBV-VL at the first dose of rituximab, and the EBV-VL value at the current and previous time point. Of 214 children who underwent allogenic HSCT, EBV DNA was detected in 87 (41%) children. Children who received rituximab after diagnosis of PTLD were excluded, leading to a cohort of 78 children. Twenty-two (28%) children received pre-emptive rituximab. Mean (SD) age was similar in both groups (10 [5] year). First post-transplant positive EBV-VL was earlier in the pre-emptive rituximab group (mean of 55 [54] vs. 113 [96] days; P < 0.05) and first positive EBV-VL was higher in the pre-emptive rituximab group (mean of 3.4 [0.6] vs. 3.0 [0.6] log10/mL; P < 0.05). In adjusted analyses, pre-emptive rituximab was associated with a higher likelihood of EBV-VL clearance (hazard ratio 1.86; 95% confidence interval 1.10–3.14; Figure 1). Of the 10 children who developed PTLD, none had received pre-emptive rituximab. EBV viremia is frequent in children with allogenic HSCT. Our results suggest that pre-emptive rituximab is associated with more rapid EBV-VL clearance. The effect of rituximab on the risk of PTLD needs to be better defined. Inverse probability of EBV viremia clearance in children. All authors: No reported disclosures.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".