Clinical-Pathologic Factors Associated with Hormone Receptor Expression Predict Prognosis in Breast Cancer
Bibliographic record
Abstract
ER positive, PR negative tumors are an especial subtype of breast cancers with the character that having unfavorable outcome and tamoxifen resistance in spite of being ER positive. While there is little attention to the subgroup that within the majority of ER positive tumors there is a subtype with the ER positive, PR negative, whose outcome is as bad as the triple negative breast cancer (TNBC)or even worse. This review is mainly about the investigation of the clinicopathological features of the ER-positive and PR-negative subtype of the Luminal B-like breast cancer. The total amount of the patients is 320, they are hormone receptor positive breast cancer patients who were operated in 2006~2012 were included in the study. The percentage (79.1%) of expression of P53 protein among Luminal B subtype is higher than it was among Luminal A (20.9%).The index of Ki-67 was distinctly interrelated with the status of PR (P＜0.05), and it was more probably to have a higher Ki 67 index in Luminal B like breast cancers with PR positivity (53.4% VS 46.6%), PR negativity is associated with a dreadful outcome of Luminal B patients containing high risk of recurrence and short overall survival. P53 protein accumulation was correlated with prognosis of Luminal B breast cancers. In this article, we emphasize the role of PR HER-2 Ki67 and P53 in Luminal B breast cancer which have positive ER expression and negative PR expression. Our findings have revealed the expression of different biomarker have unique value to its sprognostic, and indicated that due to the high risk of relapse, the ER+/PR- Luminal-B tumors warrant further attention.
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 | 0.000 | 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".