Olivier Elemento: Real-world evidence on AI’s impact in clinical practice
Olivier Elemento, Director of Englander Institute for Precision Medicine at Weill Cornell Medicine, posted on LinkedIn about recent paper by Veronica Hernström et al., titled “Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study” published on The Lancet.
Authors: Veronica Hernström, Viktoria Josefsson, Hanna Sartor, David Schmidt, Anna-Maria Larsson, Prof Solveig Hofvind, Ingvar Andersson, Aldana Rosso, Oskar Hagberg, Kristina Lång
“AI Skeptic: ‘Randomized Clinical Trials for AI are too difficult to implement.’
Sweden: ‘Here’s a large-scale RCT with 105,934 participants, testing AI in real-world clinical practice within a national screening program’
The MASAI trial, a randomized, controlled, non-inferiority study, tested AI-supported mammography screening against standard double reading in Sweden’s national screening program. Published in The Lancet Digital Health, it provides real-world evidence on AI’s impact in clinical practice.
Key results:
- 29% increase in cancer detection (6.4 vs. 5.0 per 1,000 screened participants, p=0.0021)
- 44% reduction in screen-reading workload (61,248 vs. 109,692 total readings)
- No significant rise in false positives (1.5% vs. 1.4%, p=0.92)
Importantly, AI did not just detect more cancers – it detected more clinically relevant ones:
- More small, lymph-node negative invasive cancers (270 vs. 217)
- Increased detection of aggressive subtypes, including triple-negative and HER2-positive cancers
- No increase in low-grade ductal carcinoma in situ, reducing concerns about overdiagnosis
This trial is a landmark in demonstrating that AI in medicine can and should be tested under the same rigorous standards as new drugs and medical devices.
When the stakes are high, clinical evidence – not hype – should drive adoption!”
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