The real-world observational prospective study of health outcomes with dulaglutide and liraglutide in type 2 diabetes patients (TROPHIES): resource use and costs of treatment in clinical practice in France, Germany, and Italy
Bibliographic record
Abstract
AIMS: To describe healthcare resource utilization (HCRU) and associated costs after initiation of injectable glucagon-like peptide-1 receptor agonist (GLP-1 RA) therapy by adult patients with type 2 diabetes (T2D) in the prospective, observational, 24-month TROPHIES study in France, Germany, and Italy. MATERIALS AND METHODS: HCRU data for cost calculations were collected by treating physicians during patient interviews at baseline and follow-up visits approximately 6, 12, 18, and 24 months after GLP-1 RA initiation with once-weekly dulaglutide or once-daily liraglutide. Costs were evaluated from the national healthcare system (third-party payer) perspective and updated to 2018 prices. RESULTS: In total, 2,005 patients were eligible for the HCRU analysis (1,014 dulaglutide; 991 liraglutide). Baseline patient characteristics were generally similar between treatment groups and countries. The largest proportions of patients using ≥2 oral glucose-lowering medications (GLMs) at baseline (42.9-43.4%) and month 24 (44.0-45.1%) and using another injectable GLM at month 24 (15.3-23.2%) were in France. Mean numbers of primary and secondary healthcare contacts during each assessment period were highest in France (range = 4.0-10.7) and Germany (range = 2.9-5.7), respectively. The greatest proportions (≥60%) of mean annualized costs per patient comprised medication costs. Mean annualized HCRU costs per patient varied by treatment cohort and country: the highest levels were in the liraglutide cohort in France (€909) and the dulaglutide cohort in Germany (€883). LIMITATIONS: patient-completed diaries. CONCLUSIONS: Real-world HCRU and costs associated with the treatment of adults with T2D with two GLP-1 RAs in TROPHIES emphasize the need to avoid generalization with respect to HCRU and costs associated with a particular therapy when estimating the impact of a new treatment in a country-specific setting.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".