Feasibility of Reduced Clinical Monitoring in Patients with Inflammatory Bowel Disease Treated with Thiopurine Therapy
Bibliographic record
Abstract
BACKGROUND: Outpatient visits and laboratory assessments are routinely scheduled every 3 to 4 months in thiopurine-treated patients with inflammatory bowel disease (IBD) to timely detect thiopurine-related adverse events (AEs). AEs that require therapy adjustment beyond 12 months of treatment are rare. AIM AND METHODS: This single-center prospective cohort study evaluated the safety of a reduced 6-monthly monitoring strategy in steroid-free patients with quiescent IBD on stable dose of azathioprine, mercaptopurine, or thioguanine monotherapy. The primary outcome was thiopurine-related AEs requiring therapy adjustments during a follow-up period of 24 months. Secondary outcomes included all AEs including laboratory toxicity, disease flares until 12 months, and the net monetary benefit from this strategy concerning IBD-related health care use. RESULTS: We enrolled 85 patients with IBD (median age 42 years, 61% Crohn's disease, 62% female), with a median disease duration of 12.5 years and median thiopurine treatment duration of 6.7 years. During follow-up, 3 patients (4%) ceased thiopurines due to AEs: recurrent infections, non-melanoma skin cancer, and gastrointestinal complaints (nausea, vomiting). At 12 months, 25 laboratory toxicities were observed (including 13% myelotoxicity, 17% hepatotoxicity); none required therapy adjustments and all were transient. A reduced monitoring strategy had a net benefit of €136 per patient. CONCLUSION: Three patients (4%) ceased thiopurine therapy due to thiopurine-related AEs, while no laboratory toxicity required therapy adjustments. Monitoring frequency of every 6 months seems feasible in patients with stable IBD on long-term (median duration > 6 years) maintenance thiopurine therapy and may contribute to reduced patient-burden and health care costs.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".