Precision therapy of 6‐mercaptopurine in Chinese children with acute lymphoblastic leukaemia
Bibliographic record
Abstract
Aims Chinese children are more susceptible to the development of thiopurine‐induced leukopenia compared with Caucasian populations. The aim of our study was to establish a 6‐mercaptopurine (6‐MP) dose–concentration–response relationship through exploration of pharmacogenetic factors involved in the thiopurine‐induced toxicities in Chinese paediatric patients afflicted by acute lymphoblastic leukaemia (ALL). Methods Blood samples were obtained from ALL children treated with 6‐MP. We determined the metabolite steady‐state concentrations of 6‐MP in red blood cells (RBCs) by using high‐performance liquid chromatography. Pharmacogenetic analysis was carried out on patients' genomic DNA using the MassArray genotyping platform. Results Sixty children afflicted by ALL who received 6‐MP treatment were enrolled in this study. The median concentration of 6‐thioguanine in patients afflicted by leukopenia was 235.83 pmol/8 × 10 8 RBCs, which was significantly higher than for patients unafflicted by leukopenia (178.90 pmol/8 × 10 8 RBCs; P = 0.029). We determined the population special target 6‐thioguanine threshold to have equalled 197.50 pmol/8 × 10 8 RBCs to predict leukopenia risk in Chinese paediatric patients afflicted by ALL. Among 36 candidate single nucleotide polymorphisms, our results indicated that NUDT15 (rs116855232) and IMPDH1 (rs2278293) were correlated with a 5.50‐fold and 5.80‐fold higher risk of leukopenia, respectively. MTHFR rs1801133 variants were found to have had a 4.46‐fold significantly higher risk of hepatotoxicity vs wild‐type genotype. Conclusion Our findings support the idea that predetermination of genotypes and monitoring of thiopurine metabolism for Chinese paediatric patients afflicted by ALL is necessary to effectively predict the efficacy of treatments and to minimize the adverse effects of 6‐MP maintenance therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".