Second Autologous Stem Cell Transplantation for Relapsed Lymphoma after a Prior Autologous Transplant
Bibliographic record
Abstract
We determined treatment-related mortality, progression-free survival (PFS), and overall survival (OS) after a second autologous HCT (HCT2) for patients with lymphoma relapse after a prior HCT (HCT1). Outcomes for patients with either Hodgkin lymphoma (HL, n = 21) or non-Hodgkin lymphoma (NHL, n = 19) receiving HCT2 reported to the Center for International Blood and Marrow Transplant Research (CIBMTR) were analyzed. The median age at HCT2 was 38 years (range: 16-61) and 22 (58%) patients had a Karnofsky performance score <90. HCT2 was performed >1 year after HCT1 in 82%. The probability of treatment-related mortality at day 100 was 11% (95% confidence interval [CI], 3%-22%). The 1-, 3-, and 5-year probabilities of PFS were 50% (95% CI, 34%-66%), 36% (95% CI, 21%-52%), and 30% (95% CI, 16%-46%), respectively. Corresponding probabilities of survival were 65% (95% CI, 50%-79%), 36% (95% CI, 22%-52%), and 30% (95% CI, 17%-46%), respectively. At a median follow-up of 72 months (range: 12-124 months) after HCT2, 29 patients (73%) have died, 18 (62%) secondary to relapsed lymphoma. The outcomes of patients with HL and NHL were similar. In summary, this series represents the largest reported group of patients with relapsed lymphomas undergoing SCT2 following failed SCT1, and with long-term follow-up. Our series suggests that SCT2 is feasible in patients relapsing after prior HCT1, with a lower treatment-related mortality than that reported for allogeneic transplant in this setting. HCT2 should be considered for patients with relapsed HL or NHL after HCT1 without alternative allogeneic stem cell transplant options.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".