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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 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".