Skin Recurrence of a Phyllodes Tumor and Impact of Radiotherapy: A Case Report and Review of the Literature
Bibliographic record
Abstract
Abstract: Introduction : Phyllodes tumors (PTs) are rare and are usually associated with local recurrences. Determining appropriate clear margins at surgery, adjuvant chemotherapy, and adjuvant radiotherapy is an ongoing dilemma for oncology professionals. The skin recurrence of a PT is not a commonly described situation in the published literature. Herein, we presented a patient with a skin recurrence of a PT. Case : A 48 year old Turkish woman presented with a lump on her left nipple-areolar complex. She had an anamnesis of a lumpectomy for PT 6 years ago and a nipple-areolar complex sparing mastectomy with immediate silicon reconstruction due to the recurrence of PT 3 years ago. No adjuvant treatment was administered after either of these surgical procedures. A magnetic resonance examination of her breast and a histopathological evaluation revealed the skin recurrence of PT. A nipple-areolar complex excision with 2 cm clear margins and adjuvant radiotherapy was then administered to her as the treatment regimen. Discussion : Surgery is defined as the effective treatment for PT but patients with high risk factors as large tumor size, positive margins and recurrent disease adjuvant treatments must be added.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".