Long Term Results of Myeloablative Allogeneic Stem Cell Transplantation Using Related and Unrelated Donors in Patients with Relapsed Composite Low and Intermediate Grade (Including Transformed) Lymphoma.
Bibliographic record
Abstract
Abstract Patients (pts) with relapsed (REL) transformed non-Hodgkin lymphoma (NHL) have poor outcome with conventional therapies. Although the role of autologous (auto) stem cell transplantation (SCT) has been previously described, there is scarce literature about allogeneic (allo) SCT in this setting. Forty pts with REL composite low/intermediate (L/I) NHL (25 transformed, 8 composite (same site) and 7 discordant (different sites)) underwent allo-SCT Jan ’89 to June ’05. Fifteen pts (38%) received stem cells from unrelated donors (UD) (12 matched and 3 with one antigen mis-match [1AgMM]). Six of 15 pts (40%) in the UD group are alive including one pt post 1AgMM SCT. 25 pts (62%) had matched sibling allo-SCT and 5 (20%) pts are still alive. Twenty-nine of 40 pts (73%) died, with REL NHL (n=15, 38%) or treatment related mortality (TRM) (n=14, 35%). The 2 and 5-year probability of OS were 39% [95% CI: 26–58%] and 23% [10–49%] respectively; of EFS 36% [24–55%] and 23% [11–46%]. Univariate analysis (UVA) showed presence of residual (res) NHL prior to allo-SCT as a poor prognostic factor for OS and EFS with p value of 0.029 (HR=2.2) and 0.011 (HR=2.5) respectively. No survival difference was seen between patients treated with related or UD stem cells. On multivariate analysis (MVA), development of aGVHD grades 2–4 had a significantly negative impact on both OS and EFS (for OS: p=0.006, HR=1.46, for EFS: p=0.01, HR=1.37) as did res disease prior to SCT (for OS: p=0.04, HR=2.2, for EFS: p=0.02, HR=2.4). Age >46 years was a significant risk factor for TRM on UVA (p=0.02, HR=3.3) and MVA (p=0.07, HR=2.9). MVA also showed development of cGVHD as a significant risk factor for TRM (p=0.001, HR=1.8). No difference in TRM was seen between related and UD SCT. Pts with res NHL at SCT had a higher risk of REL NHL (p=0.008, HR=5), as did pts who were chemotherapy resistant (no change in the tumor mass) pre-SCT (p=0.002, HR=3.9). Inclusion of TBI in the conditioning regimen significantly reduced the risk of REL NHL (p=0.01, RR=0.22). Prior rituximab therapy was associated with reduced REL risk, although this was not statistically significant (p=0.06, HR=0.82). CGVHD was significantly protective against REL in MVA (p=0.03, HR= 0.8), and res NHL at SCT was associated with increased REL (p=0.003, HR= 7). Stem cell dose (mononuclear cells) >3X108/kg was the only significant risk factor for development of cGVHD in UVA (p=0.04, HR=0.4) and MVA (p=0.05, HR=0.4). In conclusion, this is the largest report on the utility of allo-SCT (inculding UD-SCT) in patients with REL composite L/I-NHL. Survival was similar in pts receiving stem cells from related and unrelated donors. UVA and MVA analysis revealed multiple significant risk factors for survival, TRM, development of cGVHD and relapse which should be taken into consideration for future allo SCT pts. Development of chronic, but not acute GVHD was protective for NHL relapse, supporting the action of a graft vs lymphoma effect in this population.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".