Retrospective study of neuroendocrine breast cancer cases from a single institution in Québec.
Bibliographic record
Abstract
e12588 Background: Within numerous breast cancer types, the neuroendocrine subtype distinguishes itself from the others by its rarity. Most of the actual data comes from European and Asian retrospective studies, whom were mostly published before the 2012 WHO classification. Methods: The aim of our study was to describe a North American cohort of neuroendocrine breast cancer tumors homogenized for the latest WHO classification of 2012. We describe the clinical presentation, diagnostic, therapeutic management and prognosis of our population recensed between 2006 and 2016 at the CHUS in Sherbrooke, Québec. A pathological review of the cases was done to unify the cohort by the latest WHO classification. Results: 59 cases were identified from the 5238 cases of breast cancer evaluated between 2006 and 2016. After review from the pathologist, 9 cases were discarded since they did not meet the diagnostic criterias. 47 patients had invasive breast carcinoma with neuroendocrine differentiation, 4 patients had poorly differentiated/small cell carcinoma and none had well differentiated neuroendocrine tumor. 44 patients were not metastatic whereas 7 patients were metastatic at disease onset with a mean age at diagnosis of 70 and 67 years respectively. 10% (4/44) developed a metastatic disease with a median time of 30 months. The mean size of the tumor was 26,1 mm and had a mean Ki67% of 28,3%. All of our patients were ER+, 98% PR+ and 4% Her2+. None had a triple negative disease. 6 patients were SBR grade 1, 31 were grade 2 and 12 were grade 3. The median follow-up for the non-metastatic patients was 42 months and 23 months for the metastatic patients. The median overall survival of our metastatic cohort was 30 months. The histologic subtype did not statistically influence the overall survival and the progression-free survival. Conclusions: Our study is the largest North American cohort of neuroendocrine breast cancer tumors classified with the latest WHO classification of 2012. More details about each subgroup analysis will be presented at the meeting. Even with this classification, the histologic diagnosis remains challenging. Further studies are needed to better characterize these patients and define their optimal management.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".