Impact of Screening Mammography on Mortality from Breast Cancer before Age 60 in Women 40 to 49 Years of Age
Bibliographic record
Abstract
BACKGROUND: Whether screening mammography programs should include women in their 40s is controversial. In Canada, screening of women aged 40-49 years has not been shown to reduce mortality from breast cancer. Given that screening mammography reduces mean tumour size and that tumour size is inversely associated with survival, the lack of benefit seen with screening is puzzling and suggests a possible adverse effect on mortality of mammography or subsequent treatment (or both) that counterbalances the expected benefit derived from downstaging. METHODS: We followed 50,436 women 40-49 years of age until age 60 for mortality from breast cancer. Of those women, one half had been randomly assigned to annual mammography and one half to no mammography. The impact of mammography on breast cancer mortality was estimated using a left-censored Cox proportional hazards model. RESULTS: Of 256 deaths from breast cancer recorded in the study cohort, 134 occurred in women allocated to mammography, and 122 occurred in those receiving usual care and not allocated to mammography. The cumulative risk of death from breast cancer to age 60 was 0.53% for women assigned to mammography and 0.48% for women not so assigned. The hazard ratio for breast cancer-specific death associated with 1 or more screening mammograms before age 50 was 1.10 (95% confidence interval: 0.86 to 1.40). CONCLUSIONS: Mammography in women 40-49 years of age is associated with a small but nonsignificant increase in the risk of dying of breast cancer before age 60. Caution should be exercised when recommending mammographic screening to women before age 50.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".