Conditioning regimens for allotransplants for diffuse large B-cell lymphoma: myeloablative or reduced intensity?
Bibliographic record
Abstract
The best conditioning regimen before allogeneic transplantation for high-risk diffuse large B-cell lymphoma (DLBCL) remains to be clarified. We analyzed data from 396 recipients of allotransplants for DLBCL receiving myeloablative (MAC; n = 165), reduced intensity (RIC; n = 143), or nonmyeloablative conditioning (NMAC; n = 88) regimens. Acute and chronic GVHD rates were similar across the groups. Five-year nonrelapse mortality (NRM) was higher in MAC than RIC and NMAC (56% vs 47% vs 36%; P = .007). Five-year relapse/progression was lower in MAC than in RIC/NMAC (26% vs 38% vs 40%; P = .031). Five-year progression-free survival (15%-25%) and overall survival (18%-26%) did not differ significantly between the cohorts. In multivariate analysis, NMAC and more recent transplant year were associated with lower NRM, whereas a lower Karnofsky performance score (< 90), prior relapse resistant to therapy, and use of unrelated donors were associated with higher NRM. NMAC transplants, no prior use of rituximab, and prior relapse resistant to therapy were associated with a greater risk of relapse/progression. In conclusion, allotransplantation with RIC or NMAC induces long-term progression-free survival in selected DLBCL patients with a lower risk of NRM but with higher risk of lymphoma progression or relapse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| 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 teacher head, 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".