Prognostic Role of Tumor Budding in Breast Cancer Patients Receiving Neo-Adjuvant Therapy
Bibliographic record
Abstract
BACKGROUND: Isolated tumor cells or small clusters of tumor cells observed in the vicinity of the main tumor mass in pathology sections, termed tumor budding, are common in cancers and have been associated with prognosis in some settings. This study examined the clinical associations and treatment efficacy implications of tumor budding in breast cancer patients receiving neo-adjuvant therapy. METHODS: Breast cancer patients that received neo-adjuvant therapy before definitive surgical treatment in a single cancer center over a 7-year period were included, and their records were reviewed. Data extracted included patient demographics, tumor characteristics and pathologic response to treatment at surgery. The initial breast cancer biopsy before any therapy was reviewed by two pathologists, and a hot spot area was evaluated for tumor budding (defined as 1 to 5 cancer cells observed detached from the main tumor mass). RESULTS: Seventy-five patients who received neo-adjuvant therapy (73 received chemotherapy and 2 received hormonal therapy) were included. Tumor budding was observed in two-thirds of the patients. There were no significant differences in patient (age and menopause status) and tumor (stage, histology and molecular sub-type equivalent) characteristics between the group that had tumor budding and the group that did not have tumor budding in the pre-treatment biopsy. Likewise, no statistically significant differences were observed in the frequency of complete or partial responses between the two groups. CONCLUSION: In this cohort of breast cancer patients receiving neo-adjuvant therapy, tumor budding was frequent, but it was not associated with tumor characteristics or pathologic responses to treatment. The value of tumor budding as a prognostic factor in the neo-adjuvant setting within the general breast cancer population could not be confirmed, but such a value in specific sub-groups deserves further investigation, given the pathophysiologic rationale and data from other settings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".