Fludarabine and 2-Gy TBI is Superior to 2 Gy TBI as Conditioning for HLA-Matched Related Hematopoietic Cell Transplantation: A Phase III Randomized Trial
Bibliographic record
Abstract
The risks and benefits of adding fludarabine to a 2-Gy total body irradiation (TBI) nonmyeloablative regimen are unknown. For this reason, we conducted a prospective randomized trial comparing 2-Gy TBI alone, or in combination with 90 mg/m(2) fludarabine (FLU/TBI), before transplantation of peripheral blood stem cells from HLA-matched related donors. Eighty-five patients with hematological malignancies were randomized to be conditioned with TBI alone (n = 44) or FLU/TBI (n = 41). All patients had initial engraftment. Two graft rejections were observed, both in the TBI group. Infection rates, nonrelapse mortality, and graft-versus-host disease (GVHD) were similar between groups. Three-year overall survival was lower in the TBI group (54% versus 65%; hazard ratio [HR], .57; P = .09), with higher incidences of relapse/progression (55% versus 40%; HR, .55; P = .06), relapse-related mortality (37% versus 28%; HR, .53; P = .09), and a lower progression-free survival (36% versus 53%; HR, .56; P = .05). Median donor T cell chimerism levels were significantly lower in the TBI group at days 28 (61% versus 90%; P < .0001) and 84 (68% versus 92%; P < .0001), as was NK cell chimerism on day 28 (75% versus 96%; P = .0005). In conclusion, this randomized trial demonstrates the importance of fludarabine in augmenting the graft-versus-tumor effect by ensuring prompt and durable high-level donor engraftment early after 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".