Systematic Review Comparing Cost Analyses of Fasciectomy, Needle Aponeurotomy, and Collagenase Injection for Treatment of Dupuytren’s Contracture
Bibliographic record
Abstract
PURPOSE: (CCH) injection. An important factor in clinical decision making is the cost-effectiveness of the various modalities, as will be discussed in this article. METHODS: A literature search was performed by 2 independent reviewers. A total of 14 articles and 3 abstracts met inclusion criteria. Papers were excluded for non-English language, insufficient breakdown of costs by treatment type, promotional materials, or works-in-progress. Cost data were extracted and subsequently converted to US dollars. Weighted means were used to objectively pool data that were sufficiently similar in methodology and population. RESULTS: Seven observational cohort studies were pooled and found to have a weighted mean cost in favour of PNA at US$3335 per patient as compared to CCH at US$3673.14 and PF at US$4734.14. Two expected-value decision analysis models were in agreement that PF is not cost-effective, but they differed on whether PNA or CCH was the most cost-effective strategy. Two cost minimization studies agreed that CCH was less costly than PF by US$486. One cost-benefit analysis found no significant cost benefit to CCH or PF, but found significant indirect benefit to CCH. Overall 10 of 17 studies found CCH to be superior with respect to direct cost, indirect cost, or both. Only 2 of the 17 studies found PF to be the most cost-effective method. Of the 7 studies that considered PNA, 4 found it to be lowest cost. CONCLUSION: The vast majority of studies found PF to be the most costly treatment modality; however, it is still the treatment of choice in certain clinical scenarios. It is difficult to compare CCH to PNA, as many studies did not consider PNA. More studies, especially considering indirect costs, are required to be able to accurately determine which method is most cost-effective.
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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 | 0.013 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".