Is clinical breast examination an acceptable alternative to mammographic screening?
Bibliographic record
Abstract
Breast cancer screening and mammography have almost become synonymous in the public perception, yet this should not necessarily be the case. Ideally, a screening tool for breast cancer would reduce mortality from breast cancer while having a low false alarm rate and being relatively cheap. Screening should not be at the expense of the symptomatic services nor inappropriately divert scarce resources away from equally deserving areas of the NHS that are less politically sensitive.1 An ideal screening test would be simple, inexpensive, and effective. Of the three modalities of breast cancer screening—breast self examination, clinical breast examination, and mammography—breast self examination fulfils the first two criteria, but early results of two randomised trials conducted in Russia and China suggest that it would not be effective in reducing mortality from breast cancer. 2 3 Clinical breast examination is also relatively simple and inexpensive, but its effectiveness in reducing mortality from breast cancer has not been directly tested in a randomised trial. Mammography is complex, expensive, and only partially effective. We believe that there is sufficient circumstantial evidence to suggest that clinical breast examination is as effective as mammography in reducing mortality from breast cancer and that the time has come to compare these two screening methods directly in a randomised trial. #### Summary points The goal of breast screening is to prevent death and not simply to detect cancers by mammography Mammography does detect some cancers “early,” but many of these are not potentially lethal and their detection causes needless anxiety Clinical breast examination is more likely to detect cancers that are potentially lethal Results of the second Canadian national breast screening study suggest that mammographic detection of cancers that are not palpable does not affect mortality New GMC guidelines on informed consent state that women in the NHS breast screening programme should …
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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 | 0.018 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".