Annual Surveillance Mammography After Early-Stage Breast Cancer and Breast Cancer Mortality
Bibliographic record
Abstract
BACKGROUND: After treatment for early-stage breast cancer (bca), annual surveillance mammography (asm) is recommended based on the assumption that early detection of an invasive ipsilateral breast tumour recurrence or subsequent invasive contralateral primary bca reduces bca mortality. METHODS: We studied women with unilateral early-stage bca treated by breast-conserving surgery from 1994 to 1997 who subsequently developed an ipsilateral recurrence or contralateral primary more than 24 months after initial diagnosis, without prior regional or distant metastases. Annual surveillance mammography was defined as 2 episodes of bilateral mammography 11-18 months apart during the 2 years preceding the ipsilateral recurrence or contralateral primary. The association between asm and bca death was evaluated using a Cox proportional hazards model. RESULTS: = 214) at a median interval of 53 months [interquartile range (iqr): 37-72 months] after initial diagnosis, 64.7% of whom had received asm during the preceding 2 years. The median interval between the 2 bilateral mammograms was 12.3 months (iqr: 11.9-13.0 months), and the median interval between the 2nd mammogram and histopathologic confirmation of ipsilateral recurrence or contralateral primary was 1.5 months (iqr: 0.8-3.9 months). Median followup after ipsilateral recurrence or contralateral primary was 7.76 years (iqr: 3.68-9.81 years). The adjusted hazard ratio for bca death associated with asm was 0.86 (95% confidence limits: 0.63, 1.16). CONCLUSIONS: Annual surveillance mammography was associated with a modestly lowered hazard ratio for bca death.
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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 | 0.001 | 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) | 0.001 | 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".