Cost-Effectiveness of Different Forms of Intra-Articular Injections for the Treatment of Osteoarthritis of the Knee
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Osteoarthritis (OA), as one of the leading causes of disability, decreases the quality of life for those suffering from the disease and creates a substantial financial burden. Intra-articular hyaluronic acid (HA) can provide relief from the symptoms of OA and multiple HA products are prescribed. The purpose of this study is to examine the single payer cost-effectiveness of various HA products in the treatment of knee OA. METHODS: A single payer economic evaluation was conducted comparing Synvisc(®) (Sanofi, USA), Durolane(®) (Bioventus, USA), Hyalgan(®) (Fidia Pharma Inc., USA), Supartz™ (Bioventus, USA), and Euflexxa(®) (Ferring Pharmaceuticals Inc., USA). Utility scores for HA products were obtained by extracting Western Ontario and McMaster Universities Arthritis Index pain, stiffness and function from randomized controlled trials and converting them to health utilities index mark 3 scores. The cost of a treatment included the cost of the HA injection, cost of a knee injection procedure and cost of a doctor's visit for each required injection. Cost-utility in 2015 USD per quality-adjusted life years (QALY) saved was calculated for each HA product, and incremental cost-effectiveness ratios were calculated to compare the effectiveness of HA products to one another and to conventional care. RESULTS: When compared to conventional care, all investigated HA products were cost-effective, assuming a willingness-to-pay threshold of $50,000/QALY gained. The HA product Euflexxa had the most favorable cost-utility ratio ($5785.52/QALY) when compared to all other HA brands. CONCLUSION: The present study showed several HA products to be cost-effective in comparison to conventional care, with Euflexxa having the most favorable cost/QALY gained ratio compared to the other HA products. FUNDING: Ferring Pharmaceutics Inc.
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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 it