Impact on Survival of Time From Definitive Surgery to Initiation of Adjuvant Chemotherapy for Early-Stage Breast Cancer
Bibliographic record
Abstract
PURPOSE: To determine if time to start of adjuvant chemotherapy after curative surgery influences survival in early-stage breast cancer. PATIENTS AND METHODS: A retrospective review was conducted of 2,594 patients receiving adjuvant chemotherapy for stage I and II breast cancer between 1989 and 1998 at the British Columbia Cancer Agency. Relapse-free survival (RFS) and overall survival (OS) were compared among patients grouped by time from definitive curative surgery to start of adjuvant chemotherapy (< or = 4 weeks, > 4 to 8 weeks, > 8 to 12 weeks, and >12 to 24 weeks). RESULTS: RFS and OS were similar for women starting chemotherapy up to 12 weeks after surgery. OS hazard ratio (univariate) for initiation of chemotherapy more than 12 weeks compared with 12 weeks or less after surgery was 1.5 (95% CI, 1.07 to 2.10; P = .017). Five-year OS rates were 84%, 85%, 89%, and 78%, (log-rank P = .013); RFS rates were 74%, 79%, 82%, and 69% (log-rank P = .004) for patients starting chemotherapy 4 weeks or fewer, more than 4 to 8 weeks, more than 8 to 12 weeks, and more than 12 to 24 weeks after surgery, respectively. In multivariate analysis, independent prognostic factors were grade, size, nodal status, estrogen receptor, age, and lymphatic and/or vascular invasion. Initiation of adjuvant chemotherapy more than 12 weeks from surgery remained significantly associated with inferior survival, with a hazard ratio of 1.6 (95% CI, 1.2 to 2.3; P = .005). CONCLUSION: This retrospective analysis suggests that adjuvant chemotherapy is equally effective up to 12 weeks after definitive surgery but that RFS and OS appear to be compromised by delays of more than 12 weeks after definitive surgery.
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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 | 0.009 |
| 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".