Benefits and Harms of Breast Cancer Screening
Bibliographic record
Abstract
IMPORTANCE: Patients need to consider both benefits and harms of breast cancer screening. OBJECTIVE: To systematically synthesize available evidence on the association of mammographic screening and clinical breast examination (CBE) at different ages and intervals with breast cancer mortality, overdiagnosis, false-positive biopsy findings, life expectancy, and quality-adjusted life expectancy. EVIDENCE REVIEW: We searched PubMed (to March 6, 2014), CINAHL (to September 10, 2013), and PsycINFO (to September 10, 2013) for systematic reviews, randomized clinical trials (RCTs) (with no limit to publication date), and observational and modeling studies published after January 1, 2000, as well as systematic reviews of all study designs. Included studies (7 reviews, 10 RCTs, 72 observational, 1 modeling) provided evidence on the association between screening with mammography, CBE, or both and prespecified critical outcomes among women at average risk of breast cancer (no known genetic susceptibility, family history, previous breast neoplasia, or chest irradiation). We used summary estimates from existing reviews, supplemented by qualitative synthesis of studies not included in those reviews. FINDINGS: Across all ages of women at average risk, pooled estimates of association between mammography screening and mortality reduction after 13 years of follow-up were similar for 3 meta-analyses of clinical trials (UK Independent Panel: relative risk [RR], 0.80 [95% CI, 0.73-0.89]; Canadian Task Force: RR, 0.82 [95% CI, 0.74-0.94]; Cochrane: RR, 0.81 [95% CI, 0.74-0.87]); were greater in a meta-analysis of cohort studies (RR, 0.75 [95% CI, 0.69 to 0.81]); and were comparable in a modeling study (CISNET; median RR equivalent among 7 models, 0.85 [range, 0.77-0.93]). Uncertainty remains about the magnitude of associated mortality reduction in the entire US population, among women 40 to 49 years, and with annual screening compared with biennial screening. There is uncertainty about the magnitude of overdiagnosis associated with different screening strategies, attributable in part to lack of consensus on methods of estimation and the importance of ductal carcinoma in situ in overdiagnosis. For women with a first mammography screening at age 40 years, estimated 10-year cumulative risk of a false-positive biopsy result was higher (7.0% [95% CI, 6.1%-7.8%]) for annual compared with biennial (4.8% [95% CI, 4.4%-5.2%]) screening. Although 10-year probabilities of false-positive biopsy results were similar for women beginning screening at age 50 years, indirect estimates of lifetime probability of false-positive results were lower. Evidence for the relationship between screening and life expectancy and quality-adjusted life expectancy was low in quality. There was no direct evidence for any additional mortality benefit associated with the addition of CBE to mammography, but observational evidence from the United States and Canada suggested an increase in false-positive findings compared with mammography alone, with both studies finding an estimated 55 additional false-positive findings per extra breast cancer detected with the addition of CBE. CONCLUSIONS AND RELEVANCE: For women of all ages at average risk, screening was associated with a reduction in breast cancer mortality of approximately 20%, although there was uncertainty about quantitative estimates of outcomes for different breast cancer screening strategies in the United States. These findings and the related uncertainty should be considered when making recommendations based on judgments about the balance of benefits and harms of breast cancer 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 | 0.042 | 0.206 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".