Digital Compared with Screen-Film Mammography: Measures of Diagnostic Accuracy among Women Screened in the Ontario Breast Screening Program
Bibliographic record
Abstract
PURPOSE: To compare measures of diagnostic accuracy between large concurrent cohorts of women screened with digital computed radiography (CR), direct radiography (DR), and screen-film mammography (SFM). MATERIALS AND METHODS: This study was approved by the University of Toronto Research Ethics Board; informed consent was not required. Three concurrent cohorts of women aged 50-74 years who were screened from 2008-2009 in the Ontario Breast Screening Program with SFM (487,334 screening examinations, 403,688 women), DR (254,758 screening examinations, 220,520 women), or CR (74,140 screening examinations, 64,210 women) were followed for 2 years or until breast cancer diagnosis. Breast cancers were classified as screening-detected or interval on the basis of the woman's final screening and assessment results. Interval cancer rate (per 10 000 negative screening examinations), sensitivity, and specificity were compared across the cohorts by using mixed-effects logistic regression analysis. RESULTS: Interval cancer rates were higher, although not significantly so, for CR (15.2 per 10,000; 95% confidence interval [CI]: 12.8, 17.8) and were similar for DR (13.7 per 10,000; 95% CI: 12.4, 15.0) compared with SFM (13.0 per 10,000; 95% CI: 12.1, 13.9). For CR versus SFM, specificity was similar while sensitivity was significantly lower (odds ratio [OR] = 0.62; 95% CI: 0.47, 0.83; P = .001), particularly for invasive cancers detected at a rescreening examination, for women with breast density of less than 75%, for women with no family history, and for postmenopausal women. For DR versus SFM, sensitivity was similar while specificity was lower (OR = 0.92; 95% CI: 0.87, 0.98; P = .01), particularly for rescreening examinations, for women aged 60-74 years, for women with breast density of less than 75%, for women with a family history, and for women who were postmenopausal. CONCLUSION: Given the 38% lower sensitivity of CR imaging systems compared with SFM, programs should assess the continued use of this technology for breast screening.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".