Time to Start Adjuvant Systemic Treatment in Breast Cancer; a Retrospective Cohort Study
Bibliographic record
Abstract
Background: According to the World Health Organization (WHO), early diagnosis of cancer was associated with increasing rates of survival for cancers as breast, cervix, mouth, larynx, colon, rectum and skin. Still the optimal time to start adjuvant treatment after definitive surgery is uncertainAim of study: to evaluate the impact of delay to start adjuvant treatment in different biologic subtypes of breast cancer on treatment outcomes as regard response, failure free survival (FFS).Patients and methods: It involved 107 patients with nonmetastatic breast cancer presented to clinical oncology department, Assiut university hospital from January 2011 to December 2012, and were eligible for adjuvant systemic treatment, The time from surgery to the start of 1st cycle of adjuvant systemic treatment was calculated, then this time was divided into three time intervals; ≤30 days, >30 - ≤60 days, and >60 days.Results: 41.1%, 45.8%, 13.1% of patients received adjuvant treatment within 30 days, <30-60 days, and more than 60 days respectively, the median failure free survival was 50±2.104 months (95% CI=45.877-54.125) and was significantly decreased with increasing the time but not significantly differed between different time intervals in the whole study patients, nor in different biologic subtypes except luminal B, patients started early adjuvant treatment, relapsed late with significant effect of different time intervals on the time to relapse, local and distant relapses (P<0.000, P<0.001, P<0.02).Conclusion: Adjuvant systemic treatment for breast cancer should be initiated as early as possible better within 30 days of surgery because of significant poor effect of delay to initiate adjuvant treatment on FFS and TTR.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 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".