Clofarabine in Pediatric Acute Relapsed or Refractory Leukemia: Where Do We Stand on the Bridge to Hematopoietic Stem Cell Transplantation?
Bibliographic record
Abstract
Background: Despite pronounced improvement in overall survival (OS) in pediatric leukemia, a proportion of patients continue to suffer from lack of response or relapse, and the management of such patients is exceedingly difficult. Immunotherapy and engineered chimeric antigen receptor (CAR) T-cell therapy have shown promising results in the course of relapsed or refractory acute lymphoblastic leukemia (ALL). However, conventional chemotherapy continues to be utilized for re-induction purposes whether independently or in combination with immunotherapy. Methods: Forty-three pediatric leukemia patients (age < 14 years at diagnosis) consecutively diagnosed at our institution and got treated with clofarabine based regimen at a single tertiary care hospital between January 2005 and December 2019 were enrolled in this study. ALL comprised of 30 (69.8%) patients of the cohort while the remaining 13 (30.2%) were with acute myeloid leukemia (AML). Results: Post-clofarabine bone marrow (BM) was negative in 18 (45.0%) cases. Overall clofarabine failure rate was 58.1% (n = 25) with 60.0% (n = 18) in ALL and 53.8% (n = 7) in AML (P = 0.747). Eighteen (41.9%) patients eventually underwent hematopoietic stem cell transplantation (HSCT); 11 (61.1%) were from ALL group and remaining seven (38.9%) were AML (P = 0.332). Three- and 5-year OS of our patients was 37.7±7.6% and 32.7±7.3%. There was a trend of better OS for ALL patients compared to AML (40.9±9.3% vs. 15.4±10.0%, P = 0.492). Cumulative probability of 5-year OS was significantly better in transplanted patients (48.1±12.1% vs. 21.4±8.4%, P = 0.024). Conclusions: Though almost 90% of our patients proceeded to HSCT with complete response post-clofarabine treatment, yet clofarabine-based regimens are associated with the significant burden of infectious complications and sepsis-related deaths.
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 | 0.000 |
| 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 | 0.000 |
| 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".