Evaluating cost per remission and cost of serious adverse events of advanced therapies for ulcerative colitis
Bibliographic record
Abstract
BACKGROUND: Determining the relative cost-effectiveness between advanced therapeutic options for ulcerative colitis (UC) may optimize resource utilization. We evaluated total cost per response, cost per remission, and cost of safety events for patients with moderately-to-severely active UC after 52 weeks of treatment with advanced therapies at standard dosing. METHODS: An analytic model was developed to estimate costs from the US healthcare system perspective associated with achieving efficacy outcomes and managing safety outcomes for advanced therapies approved for the treatment of UC. Numbers needed to treat (NNT) for response and remission, and numbers needed to harm (NNH) for serious adverse events (SAEs) and serious infections (SIs) were derived from a network meta-analysis of pivotal trials. NNT for induction and maintenance were combined with drug regimen costs to calculate cost per clinical remission. Cost of managing AEs was calculated using NNH for safety outcomes and published costs of treating respective AEs. RESULTS: Costs per remission were $205,240, $249,417, $267,463, $365,050, $579,622, $750,200, and $787,998 for tofacitinib 10 mg, tofacitinib 5 mg, infliximab, vedolizumab, golimumab, adalimumab, and ustekinumab, respectively. Incremental costs of SAEs and SIs collectively were $136,390, $90,333, $31,888, $31,061, $20,049, $12,059, and $0 for tofacitinib 5 mg, golimumab, adalimumab, tofacitinib 10 mg, infliximab, ustekinumab, and vedolizumab (reference), respectively. CONCLUSIONS: Tofacitinib was associated with the lowest cost per response and cost per remission, while vedolizumab had the lowest costs related to SAEs and SIs. Balancing efficacy versus safety is important when evaluating the costs associated with treatment of moderate-to-severe UC.
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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 | 0.000 | 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".