AI-assisted breast cancer screening showed minor clinical benefits over DBT alone but was not cost-effective at standard willingness-to-pay thresholds.
Key Details
- 1Study published in Value in Health evaluated the cost-effectiveness of AI (Saige-DX) in breast cancer screening.
- 2Microsimulation compared digital breast tomosynthesis (DBT) alone and DBT plus AI for women aged 40–74 in biennial screening.
- 3AI reduced false negatives by 2.1 and false positives by 50 per 1,000 women; 0.13 fewer breast cancer deaths per 1,000.
- 4AI-assisted screening led to 3.09 additional QALYs but added $936,430 in lifetime costs per 1,000 women (ICER: $303,279/QALY).
- 5AI was not cost-effective at a $100,000/QALY threshold in 98% of simulations, mainly due to 21% increase in DCIS diagnoses.
- 6Cost-effectiveness did not improve even at very low AI pricing in most scenarios.
Why It Matters
Although AI can modestly improve accuracy in breast cancer screening, this study highlights persistent cost-effectiveness concerns, especially with increased DCIS detection. This underscores an economic and clinical challenge for broader AI adoption in screening workflows.
Source
AuntMinnie
Related News
•AuntMinnie
Deep Learning Model Predicts Brain Tumor MRI Enhancement Without Gadolinium
German researchers developed a deep learning approach to predict MRI contrast enhancement in brain tumors without the need for gadolinium-based agents.
•Radiology Business
Study Highlights Limitations of AI in Prostate MRI Screening
New research points to several shortcomings in implementing AI for MRI-based prostate cancer screening.
•Radiology Business
SimonMed Imaging Introduces Paid AI Add-Ons for Routine Exams
SimonMed Imaging is launching new AI-powered elective services for routine imaging exams with additional out-of-pocket costs for patients.