Update on anaplastic large cell lymphoma in women with breast implants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since 1997, reports from the scientific community have suggested a possible association, without causation, between breast implants and anaplastic large cell lymphoma (ALCL). Analysis of these patients has been challenging. Many studies have been under-reported while others have been duplicated. In 2011, a United States Food & Drug Administration (FDA) ‘white paper’ analyzed 34 of the 60 cases reported worldwide. All 34 patients had undergone secondary surgery for breast swelling, firmness or pain. ALCL was an incidental finding. Diagnosis of ALCL is made by hematoxylin and eosin histology and immunochemistry for the CD30 marker. ALCL occurred with all types of implants. Subsequent studies have suggested that textured implants may have a greater risk. In all cases, ALCL cells were found in the capsule, in the seroma or within a mass adjacent to the implant. There was no invasion of cells beyond the capsule into the breast parenchyma. From the FDA study, the risk of developing ALCL after receiving implants appears to be approximately one in one million per year. All cases appear to be negative for the anaplastic lymphoma kinase marker. ALCL in most of these patients may represent a new entity with less aggressive behaviour. In most patients with capsule-confined disease, proper management may prove to be implant removal and capsulectomy. Patients with a distinct mass adjacent to their implant may have a more aggressive clinical course that may become systemic. They may require chemotherapy in addition to implant removal and capsulectomy. All cases of ALCL should be referred to an appropriate specialist and reported to the FDA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it