The Use of AlloDerm in Postmastectomy Alloplastic Breast Reconstruction: Part II. A Cost Analysis
Bibliographic record
Abstract
BACKGROUND: Increasingly, AlloDerm is being used in alloplastic breast reconstruction, and has been the subject of a recent systematic review. The authors' objective was to perform a cost analysis comparing direct-to-implant with AlloDerm reconstruction to two-stage non-AlloDerm reconstruction. METHODS: Seven clinically important health outcomes and their probabilities for both types of reconstruction were derived from the recent review. A decision analytic model from the Canadian provincial payer's perspective was constructed based on these health states. Direct medical costs were estimated from a university-based hospital, yielding expected costs for direct-to-implant reconstruction with AlloDerm and two-stage non-AlloDerm reconstruction. Sensitivity analyses were conducted. RESULTS: Baseline and expected costs were calculated for direct-to-implant AlloDerm and two-stage non-AlloDerm reconstruction. Direct-to-implant reconstruction with AlloDerm was found to be less expensive in the baseline ($10,240 versus $10,584) and expected cost ($10,734 versus $11,251) using a 6 × 16-cm AlloDerm sheet. With a 6 × 12-cm sheet, expected cost falls to $9673. By increasing direct-to-implant operative time from 2 hours to 2.5 hours, expected cost rises to $11,784. If capsular contracture rate requiring revision is set at 15 percent for both procedures, expected costs are $10,926 and $11,251 for direct-to-implant and two-stage procedures, respectively. If the capsular contracture rate is lowered for either procedure, this has minimal impact on expected cost. CONCLUSIONS: Although AlloDerm is expensive, it appears to be cost-effective if used for direct-to-implant breast reconstruction. The methods used here may be extrapolated to different centers incorporating local costs and complication rates. A formal randomized controlled trial, including costs, is recommended.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.023 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| 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".