Residual Cancer Burden in Locally Advanced Breast Cancer: A Superior Tool
Bibliographic record
Abstract
OBJECTIVES: Locally advanced breast cancer (LABC) poses a difficult clinical challenge with an overall poor long-term prognosis. The strength of the association between tumour characteristics, treatment response, and outcome is not well defined. In the present study, we attempted to gain further insight into LABC by reviewing tumour characteristics of patients treated with neoadjuvant chemotherapy and by studying the association of those characteristics with outcome. We calculated the residual cancer burden (RCB) score obtained at surgery and attempted to study its correlation with event-free survival (EFS) and overall survival (OS). METHODS: We studied patients diagnosed primarily with LABC (n = 45). Pathologic and clinical responses were determined. Pathology slides were reviewed. RESULTS: Of the 45 study patients, 9% had stage IIB disease; 29%, stage IIIA; 51%, stage IIIB; and 11%, stage IIIC. Inflammatory breast cancer (IBC) was found in 16%. Pathologic complete response (pCR) was achieved in 22% of all patients. None of the patients with ibc achieved pcr. Patients with estrogen receptor-negative (ER-)/progesterone receptor-negative (PR-) tumours were more likely to achieve pcr than were those with ER+/PR+ tumours. Among patients with tumours that overexpressed human epidermal growth factor receptor 2 (HER2/neu), 17% achieved pCR as compared with 25% of patients with non-overexpressing tumours; only 1 patient had received trastuzumab. The RCB scores were calculated in 32 patients and ranged between 0 and 4.6. CONCLUSIONS: The present study examined practical issues related to the classification and management of LABC and IBC. The RCB, defined from routine pathology materials, was easily quantifiable. It appears to be a better predictor than pCR of outcome following neoadjuvant chemotherapy in LABC. Higher RCB scores were associated with lower efs and a lower rate of os. A continual quest for reliable predictive and correlative prognostic markers, and for better surrogate endpoints for outcome, is essential to advance our understanding of LABC and to improve treatment outcomes.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".