Outcomes for patients with EBV-positive PTLD post-allogeneic HCT after failure of rituximab-containing therapy
Bibliographic record
Abstract
Abstract Epstein–Barr virus-positive (EBV+) post-transplant lymphoproliferative disease (PTLD) is an ultra-rare and aggressive condition that may occur following allogeneic hematopoietic cell transplant (HCT) due to immunosuppression. Approximately half of EBV+ PTLD cases are relapsed or refractory (R/R) to initial rituximab-containing therapy. There are limited treatment options and no standard of care for patients with R/R EBV+ PTLD, and little is known about their treatment history and outcomes. We performed a multinational, multicenter, retrospective chart review of patients with R/R EBV+ PTLD following HCT to describe patients’ demographic and disease characteristics, treatment history, and overall survival (OS) from rituximab failure. Among 81 patients who received initial treatment with rituximab as monotherapy (84.0%) or in combination with chemotherapy (16.0%), median time from HCT to PTLD diagnosis was 3.0 months and median OS was 0.7 months. Thirty-six patients received a subsequent line of treatment. The most frequent causes of death were PTLD (56.8%), graft-versus-host disease (13.5%) and treatment-related mortality (10.8%). In multivariate analysis, early PTLD onset and lack of response to initial treatment were associated with mortality. This real-world study demonstrates that the prognosis of patients with R/R EBV+ PTLD following HCT remains poor, highlighting the urgent unmet medical need in this population.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".