Detection Rate, Recall Rate, and Positive Predictive Value of Digital Compared to Screen-Film Mammography in the Quebec Population-Based Breast Cancer Screening Program
Bibliographic record
Abstract
PURPOSE: The study sought to compare performance indicators of computed radiography (CR) using different plate readers, digital direct radiography (DR), and screen-film mammography (SFM) in a population-based screening program. METHODS: This analysis involved women 50-69 years of age who participated in the breast screening program of Quebec (Canada) and who had screening mammogram between January 1, 2007, and September 30, 2012. The detection rate, recall rate, and positive predictive value of CR (n = 672,125 mammograms) and DR (n = 60,023) were compared to SFM (n = 782,894) using mixed-effect logistic regression, adjusting for potential confounders. No institutional review board approval was required. RESULTS: CR was not associated with change in cancer detection rate (odds ratio [OR]: 0.95; 95% confidence interval [CI]: 0.88-1.03), but with a small increase in recall rate (OR: 1.03; 95% CI: 1.01-1.06) compared to SFM. The association of CR with recall rate varies with the CR plate reader manufacturer (P < .0001). DR was not associated with change in detection rate (OR: 1.06; 95% CI: 0.89-1.25), but with an increase in the recall rate (OR: 1.25; 95% CI: 1.19-1.30) compared to SFM. CONCLUSIONS: In our screening program, digital mammograms gave detection rates equivalent to those of SFM, but with an increase of recall rate, particularly for DR. If this situation persists, the adoption of DR may increase the adverse effects of screening with little or no benefit for women.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".