Epidemiological data and utilization patterns of anti-TNF alpha therapy in the Hungarian ulcerative colitis population between 2012-2016
Bibliographic record
Abstract
Background: Anti-TNF therapy is efficacious in the maintenance of remission in ulcerative colitis (UC); however, long-term data on real-life use of these agents are lacking.Methods: This observational, retrospective, epidemiological study using the National Health Insurance Fund social security database aimed to understand patient characteristics and therapeutic patterns of anti-TNF therapy. Data of adult Hungarian, UC patients treated with anti-TNF agents (IFX-infliximab, ADA-adalimumab) between 2012 and 2016 were analyzed.Results: Five hundred and sixty-eight UC patients were identified. Approximately 70-80% of the patients reached maintenance therapy. A large proportion of patients stopped therapy after 10 to 12 months due to the reimbursement policy. Corticosteroid use decreased significantly after the initiation of biological therapy. The dose-escalation rate was 19.8% for ADA and 10.9% for IFX, respectively, and was performed earlier along the treatment timeline for patients on ADA. In the present study, the rate of primary non-response (PNR) was 11.6% and the rate of secondary loss of response (LOR) was 36.5%.Summary: Treatment length is in correspondence with the Hungarian reimbursement policies. The mandatory stop of treatment in the reimbursement policy is suboptimal in UC patients requiring biological therapy. The corticosteroid-sparing effect of biological therapy was demonstrated.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".