Systematic Review: Using Magnetic Resonance Imaging to Screen Women at High Risk for Breast Cancer
Bibliographic record
Abstract
BACKGROUND: A sensitive and acceptable screening regimen for women at high risk for breast cancer is essential. Contrast-enhanced magnetic resonance imaging (MRI) of the breast is highly sensitive for diagnosis of breast cancer but has variable specificity. PURPOSE: To summarize the sensitivity, specificity, likelihood ratios, and posttest probability associated with adding MRI to annual mammography screening of women at very high risk for breast cancer. DATA SOURCES: English-language literature search of the MEDLINE, EMBASE, and Cochrane databases from January 1995 to September 2007, supplemented by hand searches of pertinent articles. STUDY SELECTION: Prospective studies published after 1994 in which MRI and mammography (with or without additional tests) were used to screen women at very high risk for breast cancer. DATA EXTRACTION: Methods and potential biases of studies were assessed by 2 reviewers, and data were extracted and entered into 2 x 2 tables that compared American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) scores of MRI plus mammography, mammography alone, or MRI alone with results of breast tissue biopsies. DATA SYNTHESIS: Eleven relevant, prospective, nonrandomized studies that ranged from small single-center studies with only 1 round of patient screening to large multicenter studies with repeated rounds of annual screening were identified. Characteristics of women that varied across study samples included age range, history of breast cancer, and BRCA1 or BRCA2 mutation status. Studies used dynamic contrast-enhanced MRI with axial or coronal plane images (European studies) or sagittal images (North American studies) that were usually interpreted without knowledge of mammography results. The summary negative likelihood ratio and the probability of a BI-RADS-suspicious lesion (given negative test findings and assuming a 2% pretest probability of disease) were 0.70 (95% CI, 0.59 to 0.82) and 1.4% (CI, 1.2% to 1.6%) for mammography alone and 0.14 (CI, 0.05 to 0.42) and 0.3% (CI, 0.1% to 0.8%) for the combination of MRI plus mammography, using a BI-RADS score of 4 or higher as the definition of positive. LIMITATIONS: Differences in patient population, center experience, and criteria for positive screening results led to between-study heterogeneity. Data on patients with nonfamilial high risk were limited, and no data were available on recurrence or survival. CONCLUSION: Screening with both MRI and mammography might rule out cancerous lesions better than mammography alone in women who are known or likely to have an inherited predisposition to breast cancer.
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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 | 0.014 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".