Cost-effectiveness analysis of arthroscopic surgery compared with non-operative management for osteoarthritis of the knee
Bibliographic record
Abstract
OBJECTIVE: To determine the cost-effectiveness of arthroscopic surgery in addition to non-operative treatments compared with non-operative treatments alone in patients with knee osteoarthritis (OA). DESIGN, SETTING AND PARTICIPANTS: We conducted an economic evaluation alongside a single-centre, randomised trial among patients with symptomatic, radiographic knee OA (KL grade ≥ 2). INTERVENTIONS: Patients received arthroscopic debridement and partial resection of degenerative knee tissues in addition to optimised non-operative therapy, or optimised non-operative therapy only. MAIN OUTCOME MEASURES: Direct and indirect costs were collected prospectively over the 2-year study period. The effectiveness outcomes were the Western Ontario McMaster Osteoarthritis Index (WOMAC) and quality-adjusted life years (QALYs). Cost-effectiveness was estimated using the net benefit regression framework considering a range of willingness-to-pay values from the Canadian public payer and societal perspectives. We calculated incremental cost-effectiveness ratios and conducted sensitivity analyses using the extremes of the 95% CIs surrounding mean differences in effect between groups. RESULTS: 168 patients were included. Patients allocated to arthroscopy received partial resection and debridement of degenerative meniscal tears (81%) and/or articular cartilage (97%). There were no significant differences between groups in use of non-operative treatments. The incremental net benefit was negative for all willingness-to-pay values. Uncertainty estimates suggest that even if willing to pay $400,000 to achieve a clinically important improvement in WOMAC score, or ≥$50,000 for an additional QALY, there is <20% probability that the addition of arthroscopy is cost-effective compared with non-operative therapies only. Our sensitivity analysis suggests that even when assuming the largest treatment effect, the addition of arthroscopic surgery is not economically attractive compared with non-operative treatments only. CONCLUSIONS: Arthroscopic debridement of degenerative articular cartilage and resection of degenerative meniscal tears in addition to non-operative treatments for knee OA is not an economically attractive treatment option compared with non-operative treatment only, regardless of willingness-to-pay value. TRIAL REGISTRATION NUMBER: NCT00158431.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".