Protocol for Autologous Fat Grafting for Immediate Reconstruction of Lumpectomy Defects Following Surgery for Breast Cancer
Bibliographic record
Abstract
BACKGROUND: For women undergoing breast conservative surgery or lumpectomy for early stage breast carcinoma, there are limited options for reconstruction. Options include the use of flap surgery and/or implants, and have a significant associated morbidity and cost. Autologous fat grafting is a new alternative that can achieve a good cosmetic result, while reducing patient morbidity and cost by avoiding more extensive surgery. OBJECTIVE: The primary objectives are to assess patient satisfaction using the Breast-Q questionnaire and to evaluate fat graft volume. The secondary objectives are fat survival and assessment for complication (eg, fat necrosis, cysts), local recurrence, and the number of sessions needed for a satisfactory outcome. METHODS: This study is a case series of 100 patients, at a single-center institute spanning one year. The inclusion criteria include: female sex, age 18 to 75, early state breast cancer (confirmed on ultrasound/ positron emission tomography-computed tomography and cytology), amenable to breast conservative surgery, and at least 6 months post-completion of radiotherapy/ hormone/chemotherapy. Exclusion criteria include patients with more advanced stages of breast cancer necessitating total mastectomy, those unsuitable for surgical excision, and those in whom lumpectomy is not feasible. The patients will have follow-up data collected at 6 months, 12 months and 5 years post-operatively. RESULTS: This study will begin enrolment in January 2017. We anticipate that there will be good patient satisfaction with fat grafting. The risk for long-term breast cancer recurrence hasn't been evaluated extensively in literature, however some clinical studies have shown no increased risk of breast cancer in appropriately selected patients at one year. Although some patients may develop complications from fat grafting (eg, necrosis/cysts) this should not confuse the radiological detection of breast cancer recurrence. CONCLUSIONS: Fat grafting is proving to be a viable option for reconstruction of lumpectomy defects with good patient satisfaction. The heterogeneous methods of reporting the harvesting of fat in literature may account for the variable outcomes described, and makes it difficult to compare results with similar studies. The long-term risk of breast cancer recurrence with fat grafting for lumpectomy defects is unknown.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.068 | 0.020 |
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".