Cost-Effectiveness of Tight Control for Crohn’s Disease With Adalimumab-Based Treatment: Economic Evaluation of the CALM Trial From a Canadian Perspective
Bibliographic record
Abstract
Crohn's disease (CD) is associated with reduced quality of life, increased absenteeism and high direct medical costs resulting from frequent hospitalizations and surgeries. Tumor necrosis factor-alpha inhibitors (TNFi's) have transformed the therapeutic landscape and enabled a shift from a symptom control to a treat-to-target strategy. The Effect of Tight Control Management on Crohn's Disease (CALM) trial demonstrated tight control (TC), with TNFi dose changes informed by biochemical markers of inflammation, achieved higher mucosal healing rates compared with conventional management (CM) based on symptoms. A Markov model compared TC and CM strategies from the perspective of the Canadian public payer using patient-observation data from the CALM trial. A regression model estimated weekly CD Activity Index-based transition matrices over a 5-year horizon and included covariates to improve extrapolation of outcomes beyond the 48-week trial assessment period. Costs of CD-related hospitalizations, biomarker tests and adalimumab injections were sourced from public data. Other direct medical costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs) were calculated. Absenteeism was monetized and included in a sensitivity analysis. Over the 5-year time horizon, TC reduced hospitalization costs by 64% compared with CM. Other direct medical costs were reduced by 22%; adalimumab costs increased by 38%, generating an ICER of $35,168 per QALY gained. Absenteeism costs were reduced by 54%, and, when that was included in the model, TC became dominant compared with CM. Management of CD with TC is cost-effective compared with CM in Canada and is dominant if indirect costs associated with absenteeism are included. Trial registration number: NCT01235689.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".