Cost‐utility analysis of proton pump inhibitors and other gastro‐protective agents for prevention of gastrointestinal complications in elderly patients taking nonselective nonsteroidal anti‐inflammatory agents
Bibliographic record
Abstract
BACKGROUND: The use of proton pump inhibitors (PPIs) among elderly patients using nonselective nonsteroidal anti-inflammatory drugs (nsNSAIDs) has increased; the price of PPIs is higher than that of majority of alternative treatment strategies. AIM: To evaluate the cost-effectiveness of nsNSAIDS + PPIs relative to alternative gastroprotective regimens in the prevention of GI complications among elderly patients (aged > or = 65 years). METHODS: An incremental cost-utility analysis, comparing PPIs with alternative gastroprotective regimens was conducted using a decision analytical model. Clinical outcomes, costs and utilities were derived from recently published studies. Probabilistic and deterministic sensitivity analyses were performed to test the robustness of the results to variation in model inputs and assumptions. RESULTS: The incremental cost-utility ratio (ICUR) of PPIs, relative to nsNSAID alone, was $206,315 per QALY gained or were more costly and less effective. Other co-prescribed treatment options had higher costs per QALY gained. In patients with a history of a complicated or uncomplicated ulcer, PPIs had ICURs of $24,277 and $40,876, respectively. CONCLUSIONS: Use of PPIs in all elderly patients taking nsNSAIDs is unlikely to represent an efficient use of finite healthcare resources. Co-prescribing PPIs, however, to elderly patients taking nsNSAIDs who have a history of complicated or uncomplicated ulcers appears to be economically attractive.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".