Clinical, Pathological, and Prognostic Features of Male Breast Cancer: A Multicenter Study
Bibliographic record
Abstract
Male breast cancer (BC) represents less than 1% of male tumors. Little is known about male BC characteristics, management, and survival, with many studies based on a small number of cases. Consequently, the treatment of male BC lacks specific guidelines. The aims of the study are to compare male and female breast cancer (FBC) in terms of cancer clinical and anatomopathological features and treatment approach, and to identify differences between male BC and FBC in terms of survival. Patients and methods: Data from 2006 to 2018 were retrospectively acquired. Amounts of 49 males and 680 postmenopausal females with primary non-metastatic BC who underwent breast surgery at Mauriziano Hospital or IRCCS Candiolo (TO—Italy) were included. The mean age at diagnosis for male BC was 68.6 years, and males presented a smaller tumor size than women (p < 0.05) at diagnosis. Most male BC patients received adjuvant endocrine therapy (AET) with tamoxifen (73.5%). AET drop-out rate due to side effects was 16.3% for males compared to 7.6% for women (p = 0.04). Comparing FBC and male BC, no differences have been identified in terms of DFS and OS, with a similar 10-year-relapse rate (12% male BC vs. 12.4% FBC). Propensity Score Matching by age, nodal status, pT, and molecular subtype had been performed and no differences in OS and DFS were seen between male BC and FBC. In conclusion, male BC and FBC have similar prognostic factors and survival outcomes. The drop-out rate of AET was higher in males, and side effects were the main reason for drug discontinuation.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".