Effectiveness of clinical breast examination as a ‘stand-alone’ screening modality: an overview of systematic reviews
Bibliographic record
Abstract
BACKGROUND: There is uncertainty about the effectiveness of clinical breast examination (CBE) and conflicting recommendations regarding its usefulness as a screening tool for breast cancer. This paper provides an overview of systematic reviews that assessed the effectiveness of CBE as a 'stand-alone' screening modality for breast cancer compared to no screening and focused on its value in low- and middle-income countries (LMICs). METHODS: We searched MEDLINE, EMBASE, Scopus, Web of Science, and the Cochrane Database of Systematic Reviews for systematic reviews reporting the effectiveness of CBE published prior to October 29, 2019. The main outcomes assessed were mortality and down staging. The AMSTAR 2 checklist was used to assess the methodological quality of the reviews including risk of bias. RESULTS: Eleven systematic reviews published between 1993 and 2019 were identified. There was no direct evidence that CBE reduced breast cancer mortality. Indirect evidence suggested that a well-performed CBE achieved the same effect as mammography regarding mortality despite its apparently lower sensitivity (40-69% for CBE vs 77-95% for mammography). Greater sensitivity was recorded among younger and Asian women. Moreover, CBE contributed between 17 and 47% of the shift from advanced to early stage cancer. CONCLUSIONS: CBE merits attention from health system and service planners in LMICs where a national screening programme based on mammography would be prohibitively expensive. In particular, it is likely that considerable value would be gained from conducting implementation scientific research in countries with large numbers of Asian women and/or where younger women are at higher risk. REGISTRATION: PROSPERO, registration number CRD42019126798 .
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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 | 0.031 | 0.141 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.015 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".