Can locoregional treatment of the primary tumor improve outcomes for women with stage IV breast cancer at diagnosis?
Bibliographic record
Abstract
89 Background: To determine whether locoregional treatment (LRT) of the primary tumor improves outcomes in patients with stage IV breast cancer at diagnosis. Methods: The study cohort comprised 733 women referred from 1996 to 2005 to a population-based cancer institution with clinical or pathologic M1 breast cancer at diagnosis. Patient, tumor, and treatment characteristics were compared between women who were treated with (n=378) and without LRT (n=355) of the primary tumor. Five-year Kaplan-Meier overall survival (OS) and locoregional progression-free survival (LRPFS) were compared between groups. Multivariable analysis to control for potential confounding factors was performed using Cox regression modeling. Results: LRT consisted of surgery alone in 67%, radiotherapy alone in 22%, and both in 11% of patients. LRT use was significantly associated with age <50 years, ECOG performance status 0-1, T1-2 tumors, and N0-1 disease, (all p<0.05). Subjects with less metastatic disease burden and those asymptomatic from the M1 disease were more likely to undergo LRT (p<0.001). Systemic therapy was used in 92% and 85% of patients treated with vs. without LRT, respectively. Five-year OS rates in the LRT and no LRT cohorts were 21% vs 14% (p<0.001). The 5-year LRPFS rates were 72% vs 46% (p<0.001). Among 378 patients who underwent LRT, 5-year OS rates were higher in patients with age <50, ECOG 0-1, ER positive disease, clear surgical margins, single M1 subsite, bone only metastases, and 1-3 metastatic lesions (all p<0.003). Type of LRT (surgery vs radiotherapy vs both) and type of surgery (lumpectomy vs mastectomy) were not associated with 5-year OS (all p>0.05). On multivariable analysis, LRT was associated with improved OS (hazard ratio 0.78, 95% confidence interval 0.64-0.94, p=0.009). Conclusions: LRT of the primary disease was associated with improved survival in women with stage IV breast cancer at diagnosis. Among subjects treated with LRT, the most favorable survival rates were observed in patients with young age, good performance status, ER-positive disease, clear resection margins and in those with distant disease limited to one subsite, bone only, or fewer than 4 metastatic lesions.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".