Prognostic significance of HER‐2 status in women with inflammatory breast cancer
Bibliographic record
Abstract
BACKGROUND: Inflammatory breast cancer (IBC) is a rare, aggressive form of breast cancer with poorly understood prognostic variables. The purpose of this study was to define the prognostic impact of HER-2 status on survival outcomes of patients with IBC. METHODS: In all, 179 patients with IBC, diagnosed between 1989 and 2005, with known HER-2 status, and treated with an anthracycline-based chemotherapy regimen without trastuzumab, were included in the analysis. Patients with HER-2-positive disease who received trastuzumab at the time of disease recurrence were included. Survival outcomes were estimated by the Kaplan-Meier product limit method and compared across groups using the log-rank statistic. A Cox proportional hazards model was fitted to determine the association of survival outcomes with HER-2 status after adjusting for patient and tumor characteristics. RESULTS: A total of 111 patients (62%) had HER-2-negative disease and 68 (38%) had HER-2-positive disease. The median follow-up among all patients was 35 months. At the time of the analysis, 62 patients (55.9%) with HER-2-negative disease and 42 patients (61.8%) with HER-2-positive disease had a recurrence. Thirty-one patients (73.8%) with HER-2-positive disease who had a disease recurrence went on to receive trastuzumab. On univariate analysis, no statistically significant difference was observed for either recurrence-free survival (P = .75) or overall survival (P = .24) between patients who had HER-2-positive disease and those who had HER-2-negative disease. In a multivariate model, HER-2 status did not appear to significantly affect recurrence-free survival (hazards ratio [HR] of 0.75; 95% confidence interval [95% CI], 0.46-1.22 [P = .241]). In the multivariate model, patients with HER-2-positive disease had a decreased hazard of death (HR of 0.56; 95% CI, 0.34-0.93 [P = .024]) compared with patients with HER-2-negative disease. CONCLUSIONS: HER-2 status, in the absence of trastuzumab, did not appear to significantly affect recurrence-free survival. After adjusting for other characteristics, the addition of trastuzumab in the metastatic setting significantly improved survival in the HER-2-positive group above and beyond that of the HER-2-negative group. This gives us further insight into the biology of this aggressive disease and underlines the major effect of targeted intervention.
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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 | 0.000 | 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) | 0.001 | 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".