Tumor budding in breast carcinoma: A systematic review and meta-analysis
Bibliographic record
Abstract
ABSTRACT: Tumor budding is gaining importance as a prognostic factor in various carcinomas due to its association with epithelial-mesenchymal transition (EMT) and hence clinical outcome. Reporting tumor budding in breast cancer lacks homogeneity. We aim to systematically review the existing literature and conduct a meta-analysis to assess the prognostic implication of tumor budding in breast carcinoma. A systematic search was performed to identify studies that compared different prognostic variables between high- and low-grade tumor budding. Quality assessment was performed using a modified Newcastle Ottawa Scale. Dichotomous variables were pooled using the odds ratio using the Der-Simonian-Laird method. Meta-analysis was conducted to study the association between low/high-grade tumor budding and tumor grade, lymph node metastasis, lymphovascular invasion, ER, PR, HER2neu, KI67, and the molecular subtype triple-negative breast carcinoma. Thirteen studies with a total of 1763 patients were included. A moderate risk of bias was noted. The median bias scoring was 7 (6-9). High-grade tumor budding was significantly associated with lymph node metastasis (OR: 2.25, 95% CI: 1.52-3.34, P < 0.01) and lymphovascular invasion (OR: 3.14, 95% CI: 2.10-4.71, P < 0.01), and low-grade budding was significantly associated with triple-negative breast carcinoma (OR: 0.61, 95% CI: 0.39-0.95, P = 0.03)There was significant heterogeneity in the assessment and grading of tumor budding; thus, a checklist of items was identified that lacked standardization. Our meta-analysis concluded that tumor budding can act as an independent prognostic marker for breast cancer.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".