Ultrasound as an Adjunct to Mammography for Breast Cancer Screening: A Health Technology Assessment.
Bibliographic record
Abstract
BACKGROUND: Screening with mammography can detect breast cancer early, before clinical symptoms appear. Some cancers, however, are not captured with mammography screening alone. Ultrasound has been suggested as a safe adjunct screening tool that can detect breast cancers missed on mammography. We investigated the benefits, harms, cost-effectiveness, and cost burden of ultrasound as an adjunct to mammography compared with mammography alone for screening women at average risk and at high risk for breast cancer. METHODS: We searched Ovid MEDLINE, Ovid Embase, EBM Reviews, and the NHS Economic Evaluation Database, from January 1998 to June 2015, for evidence of effectiveness, harms, diagnostic accuracy, and cost-effectiveness. Only studies evaluating the use of ultrasound as an adjunct to mammography in the specified populations were included. We also conducted a cost analysis to estimate the costs in Ontario over the next 5 years to fund ultrasound as an adjunct to mammography in breast cancer screening for high-risk women who are contraindicated for MRI, the current standard of care to supplement mammography. RESULTS: No studies in average-risk women met the inclusion criteria of the clinical review. We included 5 prospective, paired cohort studies in high-risk women, 4 of which were relevant to the Ontario context. Adjunct ultrasound identified between 2.3 and 5.9 additional breast cancers per 1,000 screens. The average pooled sensitivity of mammography and ultrasound was 53%, a statistically significant increase relative to mammography alone (absolute increase 13%; P < .05). The average pooled specificity of the combined test was 96%, an absolute increase in the false-positive rate of 2% relative to mammography screening alone. The GRADE for this body of evidence was low. Additional annual costs of using breast ultrasound as an adjunct to mammography for high-risk women in Ontario contraindicated for MRI would range from $15,500 to $30,250 in the next 5 years. CONCLUSIONS: We found no evidence that evaluated the comparative effectiveness or diagnostic accuracy of screening breast ultrasound as an adjunct to mammography among average-risk women aged 50 years and over. In women at high risk of developing breast cancer, there is low-quality evidence that screening with mammography and adjunct ultrasound detects additional cases of disease, with improved sensitivity compared to mammography alone. Screening with adjunct ultrasound also increases the number of false-positive findings and subsequent biopsy recommendations. It is unclear if the use of screening breast ultrasound as an adjunct to mammography will reduce breast cancer-related mortality among high-risk women. The annual cost burden of using adjunct ultrasound to screen high-risk women who cannot receive MRI in Ontario would be small.
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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 | 0.015 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.019 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 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".