Single-center retrospective study assessing the efficacy and safety of BeEAM (bendamustine, etoposide, cytarabine, melphalan) as conditioning regimen for autologous hematopoietic stem cell transplantation
Bibliographic record
Abstract
One of the most widely accepted conditioning regimens for hematopoietic stem cell transplantation (HSCT) is BEAM (carmustine, etoposide, cytarabine, melphalan). However, a recent increase in the cost of carmustine has limited its use bringing our institution to replace carmustine with bendamustine. This observational retrospective single-center study aims to report the efficacy and safety of the BeEAM regimen. 55 patients with diffuse large B-cell lymphoma (47%), Hodgkin lymphoma (25%), mantle cell lymphoma (25%), or follicular lymphoma (2%) were included. Progression-free survival (PFS) at 24 months was 75% and overall survival (OS) was 83%. Treatment-related mortality was 4%. The most common adverse effects were febrile neutropenia (98%), mucositis (72%) and colitis (60%). Our study demonstrated excellent efficacy of the BeEAM regimen. However, the toxicity profile of BeEAM significantly varies from one study to another, and guidelines suggesting optimal dose of bendamustine and supportive care are currently lacking.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".