The Role of Second-HSCT for Children with Relapsed Hematological Malignancies: A Single Center Experience
Bibliographic record
Abstract
Background Allogeneic hematopoietic stem cell transplantation (HSCT) has become the standard of care for children with relapsed/refractory hematologic malignancies. Despite favorable outcomes, some patients experience relapsed/refractory disease after first-HSCT. With advancements of immunotherapies, less toxic conditioning regimens and expanded donor choices, second HSCT is being increasingly offered. However, data guiding selection of patients is scarce. This study aims to describe predictors of outcomes in children with relapsed/refractory hematologic malignancies after first-HSCT. Methods A retrospective review was conducted at The Hospital for Sick Children, Toronto, Canada. Children <18 years of age with hematologic malignancies who were diagnosed with relapsed/refractory disease after the first-HSCT between January 2008 and December 2023 were included. Descriptive statistics and Kaplan-Meier survival analyses were performed. A p-value <0.05 was considered statistically significant. Results Eighty-one children with relapsed/refractory hematologic malignancies after first-HSCT were included. The median age was 5.5 years (range, 0.1–15.6 years), the most common diagnosis was acute myeloid leukemia (49.4%), followed by acute lymphoblastic leukemia (37.0%). The median time from first-HSCT to relapse was 9 months (range, 1–108 months). With a median follow-up time of one-year, 3-year EFS was 35.1% (95%CI,24.8-45.6), OS was 36.4% (95%CI,26.0.0-46.9). A second-HSCT was performed in 32 cases (39.5%). Patients who received a second HSCT had a significant improved 3-year-EFS of 65.2% (95%CI,46.0-79.0) vs 15.2% (95%CI,6.6-26.9,p<0.001) and OS 68.3% (95%CI,49.1–81.6) vs 15.2% (95%CI,6.6–26.9,p < 0.001). Transplant related mortality was 8.6%. Number of relapses, previous graft-versus-host disease, switch of HSCT donor and time to relapse after first HSCT did not significantly affect outcomes. Limitations of the study include small number of patients and single institution setting. Conclusion Outcomes of children undergoing second-HSCT are favorable and should be considered for children who experience relapsed/refractory hematologic malignancies after first-HSCT. Additional research is needed to further define factors predicting treatment success.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".