Breast Reconstruction Following Breast Implant–Associated Anaplastic Large Cell Lymphoma
Bibliographic record
Abstract
BACKGROUND: Standard of care treatment of breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) involves surgical resection with implant removal and complete capsulectomy. We report a case series of BIA-ALCL reconstruction with proposals for timing and technique selection. METHODS: We retrospectively reviewed and prospectively enrolled all BIA-ALCL patients at 2 tertiary care centers and 1 private plastic surgery practice from 1998 to 2017. Demographics, treatment, reconstruction, pathology staging, patient satisfaction, and oncologic outcomes were reviewed. RESULTS: We treated 66 consecutive BIA-ALCL patients and 18 (27%) received reconstruction. Seven patients (39%) received immediate reconstruction, and 11 (61%) received delayed reconstruction. Disease stage at presentation was IA (T1N0M0 disease confined to effusion or a layer on luminal side of capsule with no lymph node involvement and no distant spread) in 56%, IB in 17%, IC (T3N0M0 cell aggregates or sheets infiltrating the capsule, no lymph node involvement and no distant spread) in 6%, IIA (T4N0M0 lymphoma infiltrating beyond the capsule, no lymph node involvement and no distant spread) in 11%, and III in 11%. Types of reconstruction included smooth implants (72%), immediate mastopexy (11%), autologous flaps (11%), and fat grafting (6%). Outcomes included no surgical complications, but 1 patient progressed to widespread bone metastasis (6%); ultimately, all patients achieved complete remission. Ninety-four percent were satisfied/highly satisfied with reconstructions, whereas 6% were highly unsatisfied with immediate smooth implants. CONCLUSIONS: Breast reconstruction following BIA-ALCL management can be performed with acceptable complications if complete surgical ablation is possible. Immediate reconstruction is reserved for disease confined to capsule on preoperative positive emission tomography/computed tomography scan. Genetic predisposition and bilateral cases suggest that BIA-ALCL patients should not receive textured implants. Autologous options are preferable for implant adverse BIA-ALCL patients. Patients with extensive disease at presentation should be considered for 6- to 12-month delayed reconstruction with interval positive emission tomography/computed tomography evaluation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".