Azathioprine Metabolite Measurements Are not Useful for Following Treatment of Autoimmune Hepatitis in Alaska Native and other Non-Caucasian People
Bibliographic record
Abstract
BACKGROUND: In autoimmune hepatitis (AIH) patients treated with azathioprine, the utility of measuring thiopurine methyltransferase (TPMT) and azathioprine metabolites has been limited. OBJECTIVE: To evaluate the association between TPMT genotype and enzyme activity, and the impact of TPMT enzyme activity on levels of azathioprine metabolites and leukopenia to assess the clinical utility of monitoring azathioprine metabolites in Alaska Native and other non-Caucasian AIH patients. METHODS: Individuals with AIH were recruited at the Alaska Native Medical Center (Alaska, USA) and the University of Texas Southwestern Medical Center (Texas, USA). Identification of TPMT genotype and measurement of enzyme activity were performed. The metabolites 6-thioguanine nucleotides (6-TGN) and 6-methylmercaptopurine (6-MMP) were measured in participants who were on azathioprine, and the associations with disease remission and leukopenia were assessed. RESULTS: Seventy-one patients with AIH were included. The distribution of TPMT genotypes was similar to that reported in other populationbased studies. TPMT genotype and phenotype were strongly associated (P<0.0001). Levels of 6-TGN and 6-MMP correlated with azathioprine dose only in individuals with normal TPMT enzyme activity. Patients with leukopenia due to azathioprine were no more likely to have abnormal TPMT enzyme levels than those without leukopenia (P=1.0). No specific level of 6-TGN metabolites was associated with remission or leukopenia. DISCUSSION: Results of the present study were consistent with previous studies in Caucasian populations. TPMT genotype and phenotype correlated well, and levels of 6-TGN and 6-MMP metabolites were not associated with remission of AIH or toxicity of azathioprine. CONCLUSIONS: The present study confirmed the limited utility of monitoring levels of azathioprine metabolites in AIH patients.
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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 | 0.001 | 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".