O0072 6-MMP/6-TG METABOLITE LEVELS & THEIR RATIO GUIDE THIOPURINE TREATMENT IN ULCERATIVE COLITIS
Bibliographic record
Abstract
Introduction: The efficient conversion of the thiopurine drugs azathioprine (AZA) and 6-mercaptopurine (6-MP) to the immunosuppressive metabolites, the 6-thioguanine nucleotides (6-TG), is determinant to its clinical efficacy. The major catabolic metabolite, 6-methylmercaptopurine (6-MMP), is formed via the competing pathway by thiopurine methyltransferase. Measurement of these metabolites in Crohn’s disease patients has been shown to be helpful in titrating dose to enhance efficacy, to explain therapeutic failures and to identify non-adherence. However, little information has been reported in patients with ulcerative colitis (UC). Aim: To assess the clinical utility of repeated 6-MP drug metabolite measurements in a cohort of pediatric patients with ulcerative colitis. Methods: 6-MP metabolite levels were measured prospectively at 6 monthly intervals, or at the time of a clinical relapse, in 25 pediatric patients with UC receiving 6-MP or AZA. Therapeutic response was determined by UC activity index and physical exam was ascertained at each clinic visit corresponding to a 6-MP metabolite measurement (clinical evaluation point). Erythrocyte 6-TG and 6-MMP concentrations (pmol/8x108 RBC) were measured by HPLC assay at Ste Justine Hospital. Logistic regression analysis using generalized estimation equations (GEE) was carried out accounting for correlation between repeated measures. Results: Mean age (SD) was 10.2 (3.6) years. 13/25 patients (52%) had one or more relapses, and 30% of all the 103 clinical evaluation points corresponded to disease relapses. Mean 6-TG level in remission was higher (244, SD 205) compared to patients with active disease (183, SD 113) (p<0.05). After controlling for time since diagnosis and age at diagnosis, clinical remission was strongly correlated with higher erythrocyte 6-TG levels (OR=0.21; 95% CI= [0.06–0.8], p= 0.02), but neither with 6-MMP levels nor dose of 6-MP/AZA. An increased risk for relapse was associated with above average (35.7 mean, SD 80.7) ratios of 6-MMP/6-TG: odds ratio (OR) = 1.65; 95% CI= [0.99 - 2.7], p<0.001. With a 5 log unit increase in the ratio, the risk for relapse among the UC patients increased 12 fold. Baseline (close to diagnosis of disease) ratios of 6-MMP/6-TG were good predictors of future relapse (Area under the curve, AUC=0.70, 95% CI= [0.45–0.95]). Conclusion: 6-MP metabolite levels and 6-MMP/6-TG ratio determination provide clinicians with useful tools for optimizing therapeutic response to thiopurine drugs in UC. An excessive 6-MMP/6-TG ratio supports the use of other, non-thiopurine drugs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".