Is Clinical Breast Examination Important for Breast Cancer Detection?
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Screening clinical breast examination (cbe) is controversial; the use of cbe is declining not only as a screening tool, but also as a diagnostic tool. In the present study, we aimed to assess the value of cbe in breast cancer detection in a tertiary care centre for breast diseases. METHODS: This retrospective study of all breast cancers diagnosed between July 1999 and December 2010 at our centre categorized cases according to the mean of detection (cbe, mammography, or both). A cbe was considered "abnormal" in the presence of a mass, nipple discharge, skin or nipple retraction, edema, erythema, peau d'orange, or ulcers. RESULTS: During the study period, a complete dataset was available for 6333 treated primary breast cancers. Cancer types were ductal carcinoma in situ (15.3%), invasive ductal carcinoma (75.7%), invasive lobular carcinoma (9.0%), or others (2.2%). Of the 6333 cancers, 36.5% (n = 2312) were detected by mammography alone, 54.8% (n = 3470) by mammography and cbe, and 8.7% (n = 551) by physician-performed cbe alone (or 5.3% if considering ultrasonography). Invasive tumours diagnosed by cbe alone were more often triple-negative, her2-positive, node-positive, and larger than those diagnosed by mammography alone (p < 0.05). CONCLUSIONS: A significant number of cancers would have been missed if cbe had not been performed. Compared with cancers detected by mammography alone, those detected by cbe had more aggressive features. Clinical breast examination is a very low-cost test that could improve the detection of breast cancer and could prompt breast ultrasonography in the case of a negative mammogram.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 it