Trends in Public Drug Plan Expenditures for Patients With Crohn Disease and Ulcerative Colitis Initiating Targeted Immune Modulator Therapy
Bibliographic record
Abstract
The objective of this analysis was to examine the changes in drug expenditures with the initiation of targeted immune modulator (TIM) treatment in patients diagnosed with Crohn disease (CD) and ulcerative colitis (UC). Patient cohorts for CD and UC were identified from hospitalizations in Canada. Expenditure data for TIMs with a Health Canada–approved indication for the treatment of CD or UC were extracted from all provincial drug plans (except Quebec) and Yukon from 2016 to 2021, and a descriptive analysis was performed to assess the expenditure patterns. Annual expenditures on TIMs for patients with CD increased each year from 2016 to 2019 before decreasing in 2020 and 2021, whereas expenditures on TIMs in UC increased each year, generally by a greater percentage than was observed in CD (peak percentage growth of 92.5% for UC versus 15.9% for CD in 2018). Expenditures associated with TIM initiation among patients with CD and UC were driven by infliximab and adalimumab, with the 2 drugs accounting for nearly all expenditures in both indications in 2016 and most expenditures in 2021. In both CD and UC, vedolizumab expenditures increased over time, as did the proportions of TIM expenditures on ustekinumab in CD and tofacitinib in UC, albeit to a lesser extent than vedolizumab.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".