Association between lymphovascular invasion (LVI) and prognostic factors in breast cancer.
Bibliographic record
Abstract
Background: The presence of tumor cells within lymphatic or blood vessels in the surrounding tissue of a malignant tumor indicates the possibility of cancer spreading (metastasis) to other parts of the body. Lymphovascular invasion (LVI) is a significant pathogenic feature in invasive breast cancer that can provide valuable information about the tumor's aggressiveness and influence therapy options. Objective: To the association of LVI with prognostic factors in breast cancer. Methods: This cross-sectional study was conducted in the Department of Surgery, Sir Salimullah Medical College and Mitford Hospital, on 52 adult breast cancer patients who received Breast Conserving Surgery (BCS) or mastectomy. No patients with neoadjuvant therapy (recurring, breast cancer, metastases, or advanced breast cancer were excluded). Patients' demographic data, clinical data, and lab diagnoses were obtained. Histopathology and immunohistochemistry were performed on all samples. ER, PR, and Ki-67 were correlated with histological results. Pathologists diagnosed LVI in surgical resection tissue. All data were validated for consistency after collection. Data were analyzed using SPSS 12.0. A p value < 0.05 was considered statistically significant. Results: The presence of ER and PR was significantly higher in cases where LVI was negative. On the other hand, the presence of Ki-67 was significantly higher in cases where LVI was positive. It was observed that cases with LVI positive had higher stages of lymph nodes metastasis and tumor grading. It was also found that the Ductal type of breast cancer was significantly higher in cases where LVI was negative. Additionally, LVI positive case was found to be significantly higher among aged people. Conclusion: The presence of lymphovascular invasion has a negative association with ER, PR, and ductal type breast cancer and is positively associated with ki67, high grade, and greater lymph node metastasis. J Shaheed Suhrawardy Med Coll 2022; 14(2): 35-38
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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 | 0.000 | 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) | 0.002 | 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".