An exploration of mercaptopurine/methotrexate tolerance during maintenance therapy in children with acute lymphoblastic leukemia
Bibliographic record
Abstract
PURPOSE: Mercaptopurine (6MP) and methotrexate (MTX) cause myelosuppression and interruptions in therapy in children with lymphoblastic leukemia (ALL). Length of time off of therapy is related to poorer outcomes. To date the dose at which most children tolerate these agents without drops in blood counts has not been identified. This study attempts to determine the maximum tolerated dose of both 6MP/MTX. METHODS: A retrospective chart review of 77 ALL children, median age 4.5 years. Time to first interruption and dose, along with total number of interruptions were collected. Absolute neutrophil and platelet counts recorded at time of interruption. Subgroup analysis of age, sex, diagnosis and risk stratification were also completed. REB approval was gained. RESULTS: Of the 77 patients that were studied, 9 of them had no treatment interruptions. Descriptive statistics are reported using Strata software. The mean number of interruptions during maintenance was 3.2, the mean time to first interruption was 149.8 days. The mean dose percent of MTX and 6MP at first interruption was 94.4% and 106% respectively. Maintenance therapy was interrupted independent of age, sex, diagnosis or disease risk stratification. CONCLUSION: Few patients complete maintenance therapy without interruptions at the current dose escalation schedules outlined by the Children's Oncology Group protocols. The interruptions are due in part to intolerance of dose escalations of MTX and 6 MP above 100%. Future research should investigate doses of 6MP and MTX in maintenance therapy in relation to leukemia outcomes.
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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 | 0.005 |
| 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 | 0.000 | 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".