Favourable prognostic factors of subsequent screen-detected breast cancers among women aged 50–69
Bibliographic record
Abstract
Most studies reporting more favourable biological features of screen-detected breast cancers compared with symptomatic or interval cancers include initial or prevalent screens and therefore may not indicate the real benefit of screening on breast cancer mortality. We conducted case-case comparisons within a cohort of eligible women (N=771 715) who were aged 50-69 between 1 January 1995 and 31 December 2003. A randomly selected sample of breast cancers (N=1848) diagnosed among these women were compared by detection method. Tumour characteristics of interval cancers (N=362) diagnosed after 6-24 months of a negative screen or symptomatic breast cancers (N=491) were compared with subsequent screen-detected breast cancers diagnosed within 6 months of a positive screen (N=995) using polytomous logistic regression. Tumours were evaluated for clinical presentation, histology and expression of hormone receptors. Women with symptomatic detected [odds ratio (OR)=7.48, 95% confidence interval (CI)=5.38-10.38] and interval cancers (OR=2.20, 95% CI=1.56-3.10) were more often diagnosed at stage III-IV versus I than women with rescreen-detected cancers. After adjusting for tumour size, women with symptomatic cancers had tumours of higher grade (OR=1.50, 95% CI=1.05-2.15) and mitotic score (OR=1.69, 95% CI=1.15-2.49) and women with interval cancers had tumours of higher mitotic score (OR=1.52, 95% CI=1.01-2.28) compared with women diagnosed at screening. Subsequent screen-detected cancers are not only detected at an earlier stage but are also less aggressive, leading to a better prognosis. As long-term mortality reduction for breast screening may depend on subsequent screens, our study indicates that mammography screening can be effective in women aged 50-69.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".