Bibliographic record
Abstract
OBJECTIVE: To review the epidemiology, presentation, diagnosis, molecular genetics, treatment and prognosis of male breast cancer. DATA SOURCES: Articles, written in English or French, selected from the Medline database (1966 to January 2001), corresponding to the key words "male breast cancer," according to the following criteria: covering institutional experience or comparing diagnostic and treatment modalities, and epidemiologic or general reviews. STUDY SELECTION: Of 198 articles found 50 fulfilled the review criteria. DATA SYNTHESIS: Risk factors included advanced age, a positive family history, Jewish origin, black race, excess exposure to female hormones (Klinefelter's syndrome), environmental exposure (irradiation), alcohol, obesity, higher socioeconomic or higher educational status and childlessness. Gynecomastia remains a controversial factor, this term being used for both a histologic reality and a physical finding. Advanced disease is characterized by pain, bloody discharge and skin ulceration. There is no definitive diagnostic algorithm. Experience with male breast mammography is limited, and imaging is less informative for patients under 50 years of age. Fine-needle aspiration tends to overestimate the rate of malignancy. The commonest histologic finding is infiltrating ductal adenocarcinoma. Treatment includes modified radical mastectomy, followed by cyclophosphamide-methotrexate-5-fluorouracil or 5-fluorouracil-Adriamycin-cyclophosphamide chemotherapy for disease of stage II or greater. Radiotherapy does not seem to add any benefit. The disease is highly receptor-positive; however, many patients discontinue tamoxifen due to side effects. The most important prognostic factors are tumour size, lymphatic invasion and axillary node status. CONCLUSIONS: Because of the low incidence of male breast cancer, advances will be obtained mainly with the rapid transfer of newly gained knowledge in female mammary neoplasia. The increased use of adjuvant chemotherapy combined with tamoxifen postoperatively may have a positive impact on survival. Public education should be oriented toward men at higher risk to reduce the interval between appearance of symptoms and consultation. Rigorous data collection will allow for thorough reporting of risk factors and thus the possibility of characterizing the etiology of this disease.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".