Impact of a Reduced Dose Intensity of Adjuvant Anthracycline Based Chemotherapy in a Population-Based Cohort of Stage I-II Breast Cancers
Bibliographic record
Abstract
BACKGROUND: Reductions in the dose intensity (DI) of adjuvant anthracycline-based chemotherapy in early stage breast cancer are frequently required due to treatment toxicity or poor tolerance, but the implications of a minimal reduction in DI on clinical outcome remain uncertain. PATIENTS AND METHODS: Women with stage I-II breast cancer treated with adjuvant adriamycin and cyclophosphamide (AC) from 1990-95 were identified in a provincial breast cancer database. Cases were classified into four cohorts: (1) all cycles delivered at full dose and on time; (2) one single dose reduction or dose delay; (3) >1 dose reduction or dose delay; (4) <2 cycles of chemotherapy delivered. RESULTS: 484 eligible cases were identified (cohort (1): n = 268; (2): n= 88; (3): n= 89; (4) n= 39). Slight imbalances in lymph node status (p=0.05) and adjuvant hormonal therapy (p=0.05) were observed between the cohorts. Fifty-five per cent (267/484) of the patients had node-positive disease and 33% (158/484) were ER+. 45% of cases had a reduction in DI. With a median follow-up of 9.6 years, there were no significant differences in relapse-free survival (p=0.94), breast cancer-specific survival (p=0.87) or overall survival (p=0.86) between the four cohorts. Outcomes were independent of hormone receptor status. CONCLUSIONS: Although toxicity related reductions in the DI of adjuvant AC chemotherapy for early stage breast cancer are common, they did not appear to significantly impact on clinical outcomes in this population-based cohort of women with stage I-II breast cancers.
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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 | 0.004 |
| 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 | 0.001 | 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".