A retrospective single-center study investigating the clinical significance of grade in triple-negative breast cancer.
Bibliographic record
Abstract
e13108 Background: Triple negative breast cancer is defined as estrogen (ER), progesterone (PR), and human epidermal growth factor receptor (HER-2) proteins negative. The grade is the degree of similarity of tumor cells to normal cells under microscope and is an important biomarker of overall patient outcomes or prognosis with higher grades having a poor prognosis. As recent chemotherapy trials noted moderately undifferentiated grade 2 tumors showing higher rates of relapse, we hypothesize that grade can also be a predictive biomarker or determinant of response to specific treatment. Methods: We reviewed 305 patient charts of triple negative breast cancer patients from 2004-2017 at Windsor Regional Cancer Center analyzing the significance of grade with respect to oncological variables, survival-time, and time to relapse. Statistical analysis was performed using Fleming-Harrington, Pairwise Testing, and COX regression, where applicable. Results: Univariate analysis showed statistically significance difference in chemotherapy type (P = 0.008) and a marginal one in ER & hormone therapy status (P ~0.09) between the grades. The overall survival rates were 90.12%, 64.4%, and 77.2%, for grade 1, 2, 3 respectively. The overall difference in survival among the three groups was statistically significant, based on Fleming-Harrington test (P = 0.019). Comparing only between grade 2 and grade 3, we found that after five years, grade 2 patients had a 5.5-fold increased risk of death (HR = 5.5; 95% CI 1.2-25.6) and 2-folds higher risk of relapse (HR = 1.9; 95% CI 1.1-3.2). Grade 3 does significantly better than grade 2 in time to relapse with relapse rates of 70%, 55.6 %, and 75.6%, respectively for grades 1, 2, and 3 (P = 0.04). Conclusions: Tumor grade has a significant positive predictive value in determining relapse with grade 2 tumors demonstrating poorer disease-free survival as compared to grade 1 & 3, less time to relapse, and increased risk of death. This has implications in stratifying triple negative breast cancer patients by grade in future clinical trials while ongoing research yields new targets for chemotherapy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".