The Contribution of Clinical Breast Examination to the Accuracy of Breast Screening
Bibliographic record
Abstract
BACKGROUND: There is controversy about whether adding clinical breast examination (CBE) to mammography improves the accuracy of breast screening. We compared the accuracy of screening among centers that offered CBE in addition to mammography with that among centers that offered only mammography. METHODS: The cohort included 290 230 women aged 50-69 years who were screened at regional cancer centers or affiliated centers within the Ontario Breast Screening Program between January 1, 2002, and December 31, 2003, and were followed up for 12 months. The regional cancer centers offer screening mammography and CBE performed by a nurse. All affiliated centers provide mammography but not all provide CBE. Performance measures for 232 515 women who were screened by mammography and CBE at the nine regional cancer centers or 59 affiliated centers that provided CBE were compared with those for 57 715 women who were screened by mammography alone at 34 affiliated centers that did not provide CBE. RESULTS: Sensitivity of referrals was higher for women who were screened at regional cancer centers or affiliated centers that offered CBE in addition to mammography than for women screened at affiliated centers that did not offer CBE (initial screen: 94.9% and 94.6%, respectively, vs 88.6%; subsequent screen: 94.9% and 91.7%, respectively, vs 85.3%). Mammography sensitivity was similar between centers that offered CBE and those that did not. However, women without cancer who were screened at regional cancer centers or affiliated centers that offered CBE had a higher false-positive rate than women screened at affiliated centers that offered only mammography (initial screen: 12.5% and 12.4%, respectively, vs 7.4%; subsequent screen: 6.3% and 8.3%, respectively, vs 5.4%). CONCLUSIONS: Women should be informed of the benefits and risks of having a CBE in addition to mammography for breast screening.
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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 | 0.012 | 0.135 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".