Thiopurine Methyltransferase Intermediate Metabolizer Status and Thiopurine‐Associated Toxicity During Maintenance Therapy in Childhood Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Mercaptopurine is a cornerstone of maintenance chemotherapy in childhood acute lymphoblastic leukemia (ALL). Its cytotoxic effects are mediated by 6-thioguanine nucleotides (TGNs) incorporation into lymphocyte DNA. Thiopurine methyltransferase (TPMT) inactivates mercaptopurine, and deficiency resulting from genetic variants increases TGN exposure and hematopoietic toxicity. Although mercaptopurine-dose reduction reduces toxicity risk without compromising relapse rate in patients with TPMT deficiency, dosing recommendations for those with moderately reduced activity (intermediate metabolizer (IM)) are less clear and their clinical impacts have yet to be established. This cohort study assessed the effect of TPMT IM status on mercaptopurine-associated toxicity and TGN blood exposure in pediatric patients with ALL initiated on standard dose mercaptopurine. Of 88 patients studied (mean age 4.8 years), 10 (11.4%) were TPMT IM, and all had undergone ≥ 3 cycles of maintenance therapy (80% completed). A larger proportion of TPMT IM than normal metabolizers (NM) had febrile neutropenia (FN) during the first two cycles of maintenance, reaching significance in the second cycle (57% vs. 15%, respectively; odds ratio = 7.33, P < 0.05). Compared to NM, FN events occurred more frequently and with prolonged duration in IM in cycles 1 and 2 (adjusted P < 0.05). IM had a 2.46-fold increased hazard ratio for FN, and about twofold higher TGN level than NM (P < 0.05). Myelotoxicity was more common in IM than NM (86% vs. 42%, respectively) during cycle 2 (odds ratio = 8.2, P < 0.05). TPMT IM initiated at a standard mercaptopurine dose are at greater risk for FN during early cycles of maintenance therapy, thus our findings support genotype-guided dose adjustment to reduce toxicity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".