A randomised trial of AI-generated treatment recommendations versus tumour boards
Test head to head whether an AI that reads the record and the evidence recommends treatments as well as a panel of experts, and whether patients do as well.
AI systems that propose treatment plans from the record and the literature have been compared with tumour boards only retrospectively, with concordance as the metric. The proposal is a prospective, randomised non-inferiority trial in a defined setting (for example, first-line metastatic NSCLC or colorectal cancer): patients are randomised to have their plan generated by the AI (with clinician sign-off and override) or by the standard board, with guideline concordance, time to treatment, trial enrolment and 12-month outcomes as endpoints, and full provenance logging for every AI recommendation.
- AI that is built but not validated or deployed · Thousands of cancer AI models are published; a handful are in clinical use, and fewer have shown they help patients.
- Not enough oncologists, nurses, pathologists, physicists · The number of people with cancer is rising faster than the workforce trained to treat them.
- Knowledge reaches practice too slowly · Knowledge diffusion is slow: it takes years for a proven result to change what most patients receive, and no one can keep up with the literature.
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