The Singapore National Breast Screening Programme: Principles and Implementation
Bibliographic record
Abstract
The Singapore Breast Screening Project (1993-1996) showed that mammographic screening in Singaporean women shifts the size and stage of screen-detected breast cancers downwards and markedly increases the rate of detection of ductal carcinoma in situ, with acceptable recall, needle biopsy and interval cancer rates. Breast cancer is the leading cause of death in Singaporean women. Singapore has one of the highest age-adjusted breast cancer incidences in Asia. Although this is much lower than in the West, for women aged 45-49 years, the breast cancer incidence in Singapore is the same as for women in Australia, Canada or the United States. The latest Singapore Cancer Registry data shows that the age of peak incidence of breast cancer in Singaporean women has risen from 45-49 years in the period 1993-1997 to 50-55 years in the period 1998-1999. This suggests that the age-specific incidence of breast cancer in Singaporean women is shifting more to a pattern usually seen in Western nations. These factors, together with reconfirmed evidence of mortality benefit from breast cancer screening trials, led the Singapore government to establish the first population-based mammographic breast screening programme in Asia, the Singapore National Breast Screening Programme (BreastScreen Singapore). It uses a distributed model of mammography service, with centralised reading and assessment, co-ordinated by the Singapore Health Promotion Board. It is unique in that women co-pay at each step of the screening and assessment process. The programme, launched in January 2002, has adopted international standards of breast screening practice and breast cancer detection. To date, the initial targets for the first year have been met. Several key policies and issues over the programme’s implementation are presented.
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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 | 0.045 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".