Angiosarcomas of the Breast
Bibliographic record
Abstract
OBJECTIVE: Angiosarcoma arising in the irradiated breast after breast-conserving therapy is being reported with increasing frequency. As more women undergo breast-conserving therapy, the incidence can be expected to increase. The objective of this study was to review breast angiosarcomas diagnosed from 1981 to 2000 from our state cancer registry. METHODS: A comprehensive review of a population-based registry, Florida Cancer Data System, identified 70 cases of breast angiosarcomas from 1981 to 2000. Descriptive statistical and chi analyses were performed. RESULTS: Of the 70 cases at presentation, 39 were primary breast angiosarcomas (PBAs) and 31 were secondary breast angiosarcomas (SBAs). The mean ages were 59 and 72.9 for the PBA and SBA groups, respectively. In the SBA group the mean age of breast cancer diagnosis was 67.6. The mean time to diagnosis of the angiosarcoma was 5.2 years after breast cancer irradiation. At presentation 82% (n = 32) and 48% (n = 15), in the PBA and SBA groups, respectively had local disease (P = 0.003). The primary treatment was mastectomy in each group. There was no difference in mortality between the 2 groups (PSA; n = 18, SBA; n = 17). CONCLUSION: Angiosarcoma of the breast is rare and this study reports a review of 70 cases from 1980 to 2000. Angiosarcoma after breast-conserving therapy is increasingly diagnosed in a small but significant portion of breast carcinoma survivors. SBA patients present with more advance disease. Surgical resection is the primary therapy. The aggressive nature of this disease demands further investigation of adjuvant therapy to prevent recurrence of disease after surgery.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".