Personalised therapy during preconception and gestation in SLE: usefulness of 6-mercaptopurine metabolite levelswith azathioprine
Bibliographic record
Abstract
Although azathioprine (AZA) is the immunosuppressive of choice in SLE pregnancies, no one has evaluated 6-mercaptopurine (6-MP) metabolite levels in this population. Even outside pregnancy, the use of metabolite testing has not been widely applied in SLE.1 AZA is a prodrug that is cleaved to 6-MP, which is converted to the active nucleotides 6-thioguanine (6-TG) and via the enzyme thiopurine methyltransferase (TPMT) to 6-methylmercaptopurine (6-MMP) (figure 1).1 Studies in inflammatory bowel diseases (IBD) established the therapeutic range for 6-TG concentrations between 235 and 450 pmol/8×108 red blood cells (RBC), as higher concentrations are associated with higher risk of myelotoxicity without increased efficacy.1 6-MMP levels >5700 pmol/8×108 RBC are associated with a higher risk of hepatotoxicity.1 Additionally, a subgroup of patients resistant to AZA shunts 6-MP towards the overproduction of 6-MMP, which is reflected in an inability to achieve therapeutic 6-TG levels despite dose escalation.1 In one study, 31% of patients on AZA were identified as ‘shunters’.2 Figure 1 Azathioprine metabolism. AZA, azathioprine; 6-MP, 6-mercaptopurine; 6-TG, 6-thioguanine; 6-MMP, 6-methylmercaptopurine; TPMT, thiopurine methyltransferase. Identifying patients as non-adherent, treatment-refractory or undertreated, as well as identifying drug toxicity, could improve the efficacy and safety of clinical decision-making. As pregnancy is a particularly critical period to optimise disease control and minimise drug toxicity, we evaluated …
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".