Favorable Overall Survival with Fully Myeloablative Allogeneic Stem Cell Transplantation for Follicular Lymphoma
Bibliographic record
Abstract
Allogeneic stem cell transplantation (Allo-SCT) remains an option for patients with follicular lymphoma (FL). We performed a retrospective analysis to examine long-term disease control and treatment-related mortality (TRM) in a group of patients that underwent transplant for clinically high-risk disease. Thirty-seven patients with indolent FL (follicular small cleaved [FSC], follicular mixed [FM] or FL grades 1 or 2 by WHO criteria) underwent allo-SCT. Patients were in a chemosensitive remission at the time of SCT. The conditioning regimen was typically busulfan-cyclophosphamide (BuCy). Cyclophosphamide-total body irradiation (TBI) was used for unrelated donor SCT. The median age at the time of transplant was 45 years (range: 24-58). The median number of prior chemotherapy regimens was 3 (range: 1-6). Thirty-seven patients received BuCy conditioning and 2 patients underwent reduced intensity conditioning SCT. Seventy-two percent of patients had a matched sibling donor. With a median follow-up of 63.5 months in survivors, the 5-year overall survival is 79.1% (95% confidence interval 66.3%-94.4%). TRM was 15.4%, with an additional case of mortality from breast cancer. These results demonstrate that in selected younger patients, a fully myeloablative allo-SCT utilizing BuCy conditioning provides excellent OS and disease control with low TRM.
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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".