Bortezomib reinduction chemotherapy in high‐risk <scp>ALL</scp> in first relapse: a report from the Children's Oncology Group
Bibliographic record
Abstract
While survival in paediatric acute lymphoblastic leukaemia (ALL) is excellent, survival following relapse is poor. Previous studies suggest proteasome inhibition with chemotherapy improves relapse ALL response rates. This phase 2 Children's Oncology Group study tested the hypothesis that adding the proteasome inhibitor bortezomib to chemotherapy increases complete response rates (CR2). Evaluable patients (n = 135, 103 B-ALL, 22 T-ALL, 10 T-lymphoblastic lymphoma) were treated with reinduction chemotherapy plus bortezomib. Overall CR2 rates were 68 ± 5% for precursor B-ALL patients (<21 years of age), 63 ± 7% for very early relapse (<18 months from diagnosis) and 72 ± 6% for early relapse (18-36 months from diagnosis). Relapsed T-ALL patients had an encouraging CR2 rate of 68 ± 10%. End of induction minimal residual disease (MRD) significantly predicted survival. MRD negative (MRDneg; MRD <0·01%) rates increased from 29% (post-cycle 1) to 64% following cycle 3. Very early relapse, end-of-induction MRDneg precursor B-ALL patients had 70 ± 14% 3-year event-free (EFS) and overall survival (OS) rates, vs. 3-year EFS/OS of 0-3% (P = 0·0001) for MRDpos (MRD ≥0·01) patients. Early relapse patients had similar outcomes (MRDneg 3-year EFS/OS 58-65% vs. MRDpos 10-19%, EFS P = 0·0014). These data suggest that adding bortezomib to chemotherapy in certain ALL subgroups, such as T-cell ALL, is worthy of further investigation. This study is registered at http://www.clinical.trials.gov as NCT00873093.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".