Febuxostat as a Novel Option to Optimize Thiopurines’ Metabolism in Patients With Inadequate Metabolite Levels
Bibliographic record
Abstract
OBJECTIVE: To report the use of febuxostat in order to potentiate thiopurines' metabolism in a patient on azathioprine (AZA) therapy with low metabolite 6-thioguanine nucleotides (6-TGN) levels and elevated metabolite 6-methylmercaptopurine (6-MMP) levels. CASE SUMMARY: A 44-year-old woman with a history of anti-signal recognition particle necrotizing myopathy was treated with AZA-allopurinol combination therapy. When she developed an atypical drug-induced hypersensitivity syndrome, allopurinol was replaced by the new xanthine oxidase (XO) inhibitor febuxostat, at a daily dose of 40 mg. Febuxostat-AZA combination was successful with 6-TGN reaching therapeutic levels while 6-MMP levels remained low. After 5 months, she developed similar manifestations that she had presented on AZA-allopurinol combination. Febuxostat and AZA were then stopped. DISCUSSION: AZA and 6-MP are both inactive pro-drugs that undergo a complex metabolic transformation leading to active 6-TGN and potentially hepatotoxic 6-MMP. Some patients with unfavorable thiopurine metabolism might benefit from addition of XO inhibitor allopurinol in order to potentiate 6-TGN and reduce 6-MMP levels. It is likely that febuxostat, via its XO inhibition, would exhibit the same effect on thiopurines' metabolism. CONCLUSION: It has been shown that low dose of febuxostat was able to prevent hypermethylation and to potentiate 6-TGN levels in an AZA-treated patient. Thus, febuxostat could be useful in optimizing thiopurines' metabolism, but more data are needed before this practice can be recommended. The mechanisms by which febuxostat optimizes thiopurines' metabolism remain to be confirmed. Also, the optimal dose of febuxostat for this use remains to be determined.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".