Treatment of adults with BCR‐ABL negative acute lymphoblastic leukaemia with a modified paediatric regimen
Bibliographic record
Abstract
Between 2000 and 2006, 85 adult BCR-ABL negative acute lymphoblastic leukaemia (ALL) patients between 18 and 60 years of age were treated using a modified paediatric regimen, which included high doses of asparaginase delivered weekly for 30 weeks during intensification. The complete response rate with induction therapy was 89%, and decreased with increasing age, mainly due to higher induction mortality. All post-induction treatments were delivered on an outpatient basis. The most common complications during intensification were infections (47%), osteonecrosis (32%), venous thromboembolism (23%) and neuropathy (22%). At a median follow-up of 4 years, the 5-year overall survival (OS) and relapse-free survival (RFS) were 63% and 71%, respectively. Significant adverse predictors for OS were age >35 years, high white blood cell count, MLL rearrangement, allogeneic stem cell transplantation in first complete remission and <80% of the planned asparaginase dose delivered during intensification. Patients aged < or = 35 years had a 3 year OS of 83%, as compared to 52% for patients aged >35 years. We conclude that the administration of this paediatric regimen is feasible and has considerable activity in adult ALL, particularly in younger patients. Effective delivery of asparaginase dosing appears to be important in achieving an optimal antileukaemic effect.
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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 | 0.000 | 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".