Can a normal mammogram predict breast cancer three years ahead? A UK model separated risk—but is not ready to set screening intervals

Cross-vendor performance weakened, and the US comparison was uncertain

On a separate UK Siemens cohort of 400 cases and 1,200 matched controls, BREST-AI's AUC fell to 0.719 but remained above Mirai's 0.685. That drop matters because scanner and site shifts are a common route by which imaging models lose performance. In a much smaller US test of 97 cases and 291 controls, BREST-AI reached 0.670 versus 0.633 for Mirai; the difference was not statistically significant, and the authors call the comparison exploratory and underpowered.

The UK datasets did not include race or ethnicity, and the US subgroup confidence intervals overlapped. The paper therefore does not establish equitable performance across population groups. Broader validation would need enough participants to estimate calibration, sensitivity and predictive value by age, density, ethnicity, vendor and site—not merely an overall AUC.[1]

The 8% predictive value is a projection, not a screening result

Because the external tests deliberately matched one case to three controls, they did not reproduce the prevalence of cancer in the English screening programme. The researchers reweighted results to eight cancers per 1,000 examinations. At a threshold set to 99% specificity, they estimated an 8.0% positive predictive value and a relative risk of 10.1 for the flagged group. Raw probabilities were substantially miscalibrated without adjustment, so local recalibration would be necessary before treating scores as absolute risk.

The model has not prospectively assigned extra imaging or shorter intervals, and the study measured no recalls, biopsies, anxiety, cost, interval cancers prevented or mortality benefit. The authors declared no competing interests and no specific funding. The evidence justifies a prospective NHS study with workload and equity safeguards; it does not justify changing a patient's screening interval today.

At the projected 8.0% positive predictive value, most people above the chosen high-risk threshold would still not develop cancer within three years. That does not make the signal useless: screening tools often trade sensitivity, specificity and workload. It does mean that any programme would need to specify what follows a flag and compare earlier detection with extra imaging, false alarms and capacity displaced from other patients.[1]