Allogeneic Hematopoietic Cell Transplantation (HCT) for Neuroblastoma (NB): The CIBMTR Experience
Bibliographic record
Abstract
Abstract Abstract 3074 Children with high-risk NB often receive using multiple treatment modalities including autoHCT. Disease remains the most common cause of treatment failure and the most recent cooperative group studies report survival rates approaching 45%. Prior reports showed comparable outcomes of patients with NB receiving auto- and allo-transplants, despite differences in relapse risk and treatment-related mortality (TRM). To update these data the CIBMTR conducted a retrospective review of 143 transplants reported 1990–2007 at 61centers, the largest group reported to date. For this analysis, patients were categorized into 2 groups for comparison: those without (Group 1; n=97) and those with a prior auto HCT (Group 2; n=46). Of the patients in Group 1, 31% were in first remission, 25% in partial response (PR) or very good PR (VGPR), and 24% with no response or with persistent/progressive disease. Of the patients Group 2, 17% were in first remission, 26% in PR or VGPR, and 28% with no response or with persistent/progressive disease. Median ages at alloHCT were similar for Group 1 (5y, range <1 to 55) and Group 2 (7y, range 2–32), while the median time from diagnosis to alloHCT was shorter (9 mo) for Group 1 than Group 2 (27 mo). In Group 1, 57% received grafts from HLA-matched related donors, 27% from mismatched related donors and 16% from unrelated donors. In Group 2, 39% received grafts from matched related donors, 9% from mismatched related donors and 52% from unrelated donors. In Group 1, stem cell sources were marrow (71%), peripheral blood (10%) and cord blood (16%). In Group 2, stem cell sources were marrow (35%), peripheral blood (28%) and cord blood (37%). There was no difference in the prevalence of acute (p=.15) or chronic GVHD (p=.24) between the two groups. Median follow-up was 84 months (range, <1 to 191) and 45 months (range 1 to 58) for those without and with prior autologous HCT. 1 year and 5 year OS were 59% and 29% for Group 1 and 50% and 7% for Group 2. Table 1 outlines the univariate analysis of some outcomes for the groups:Group 1: No prior AutoGroup 2: prior Autop-ValueTRM 100 days 1-year3% (1–9)2% (0–11)0.905825% (16–35)24% (12–37)0.8916Relapse 1-year 5-year27% (17–38)57% (41–70)0.001246% (34–58)70% (53–82)0.0123EFS 1-year 5-year48% (36–59)19% (9–32)0.000627% (17–38)6%A (1–17)0.0018OS 1-year 5-year59% (48–68)50% (35–64)0.343929% (20–39)7% (1–18)0.0005 Univariate analysis by donor-type also indicated higher relapse rates after unrelated donor transplants and lower relapse rates after HLA-mismatched related transplants compared with HLA-identical related donor transplants (p<0.0001). EFS and survival were significantly lower for unrelated donor transplants 1 and 3 years but not 5 years post-HCT. Patients in 1st CR at transplant had lower relapse rates and better EFS and survival compared to those not in 1st CR. The presence of acute and/or chronic GVHD did not correlate with outcome in univariate analyses. The most common causes of death in Groups 1 vs. 2 were relapse (64%/75%), GVHD (5%/0%), infections (11%/5%), and organ toxicity (11%/13%). Our analysis indicates that alloHCT can cure some NB patients, with lower relapse rates and improved survival in patients without a history of autoHCT compared with those patients who had undergone auto HCT first. AlloHCT for patients after autoHCT does not seem to offer benefit. However, the reasons for Group 1 patients not receiving autoHCT as part of their upfront therapy are unclear, and this group could include patients who were curable without alloHCT. Disease recurrence remains the most common cause of treatment failure while TRM is low. Future studies comparing OS after autoHCT and alloHCT for patients in CR1 should be considered. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".