Outcome of Lower-Intensity Allogeneic Transplantation in Non-Hodgkin Lymphoma after Autologous Transplantation Failure
Bibliographic record
Abstract
We studied the outcome of allogeneic hematopoietic stem cell transplantation after lower-intensity conditioning regimens (reduced-intensity conditioning and nonmyeloablative) in patients with non-Hodgkin lymphoma who relapsed after autologous hematopoietic stem cell transplantation. Nonrelapse mortality, lymphoma progression/relapse, progression-free survival (PFS), and overall survival were analyzed in 263 patients with non-Hodgkin lymphoma. All 263 patients had relapsed after a previous autologous hematopoietic stem cell transplantation and then had undergone allogeneic hematopoietic stem cell transplantation from a related (n = 26) or unrelated (n = 237) donor after reduced-intensity conditioning (n = 128) or nonmyeloablative (n = 135) and were reported to the Center for International Blood and Marrow Transplant Research between 1996 and 2006. The median follow-up of survivors was 68 months (range, 3-111 months). Three-year nonrelapse mortality was 44% (95% confidence interval [CI], 37%-50%). Lymphoma progression/relapse at 3 years was 35% (95% CI, 29%-41%). Three-year probabilities of PFS and overall survival were 21% (95% CI, 16%-27%) and 32% (95% CI, 27%-38%), respectively. Superior Karnofsky Performance Score, longer interval between transplantations, total body irradiation-based conditioning regimen, and lymphoma remission at transplantation were correlated with improved PFS. Allogeneic hematopoietic stem cell transplantation after lower-intensity conditioning is associated with significant nonrelapse mortality but can result in long-term PFS. We describe a quantitative risk model based on pretransplantation risk factors to identify those patients likely to benefit from this approach.
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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 | 0.000 | 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) | 0.001 | 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".