Combined Impact of Prior Polatuzumab Vedotin Plus Bendamustine and Rituximab Therapy and Myeloablative Conditioning on Early Post-Transplant BK Virus-Associated Hemorrhagic Cystitis
Bibliographic record
Abstract
Relapsed/refractory diffuse large B-cell lymphomas (R/R DLBCLs) have an extremely poor prognosis, with no established salvage chemotherapy currently available. Polatuzumab, rituximab, and bendamustine combination therapy (Pola-BR) has been approved as a new therapeutic option for R/R DLBCL. Recently, chimeric antigen receptor T-cell therapy and bispecific antibodies have induced long-term remission in many patients with R/R DLBCL. However, allogeneic transplantation remains potentially curative for patients unresponsive to the abovementioned treatments. While allogeneic transplantation can also cause various adverse events, hemorrhagic cystitis is a particularly severe complication that requires effective prevention strategies. Here, we report two cases of severe BK virus-associated hemorrhagic cystitis (BKV-HC) that developed after successive cord blood transplantation with myeloablative conditioning and Pola-BR treatment for early-relapsed DLBCL. Both patients received Pola-BR after undergoing multiple salvage therapies and developed early-onset BKV-HC post-transplant, demonstrating the effects of Pola-BR and myeloablative conditioning. We analyzed the shared characteristics between these two cases to distinguish between the factors that trigger the onset of BKV-HC and those that contribute to its severity. Based on the differences in the clinical course between the two cases, we propose prevention strategies for BKV-HC and identify treatment strategies for Pola-BR in patients with R/R DLBCL undergoing allogeneic transplantation.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".