Benchmarking Large Language Models Against Tumour Boards for Oncology Treatment Recommendations

Recruiting now

Conditions studied: Breast Neoplasms, Lung Neoplasms, Urologic Neoplasms, Prostatic Neoplasms, Urinary Bladder Neoplasms, Kidney Neoplasms, Digestive System Neoplasms, Genital Neoplasms, Artifical Intelligence, Large Language Models, Decision Making, Decision Support Systems, Clinical

In brief

BEACON (Benchmarking AI for Clinical Oncology decisioNmaking) is a prospective, multicentre, comparative, blinded, non-interventional benchmark evaluating the treatment recommendations of five frontier large language models (LLMs) against the recommendations of multidisciplinary tumour boards (RCP) in oncology treatment planning. One hundred standardised synthetic cases (20 per localisation, across breast, lung, urological, digestive and gynaecological cancers) are submitted as identical structured input to two independent tumour boards per localisation and to five frontier LLMs. Each recommendation - human or model - is decomposed into five predefined decision domains (intent, surgery, radiotherapy, systemic therapy, work-up and biomarkers) and scored 0/1/2 for concordance against a two-tier reference: the consensus of the two tumour boards, complemented by an a priori locked guideline matrix (ESMO, NCCN). The primary endpoint is domain-level concordance between LLM and RCP consensus, expressed as a linearly weighted Cohen's kappa. A co-primary safety endpoint captures the proportion of recommendations carrying serious harm potential, because concordance alone can conceal dangerous errors. Because expert boards may disagree with one another on identical cases, model performance is always interpreted against the human consensus. BEACON is designed as reusable, openly licensed, pre-registered infrastructure: all synthetic cases, evaluation rubrics, the locked guideline matrix, scoring algorithms and verbatim prompts are released for full reproducibility.

Key facts

Study ID
NCT07739121
Run by
Assistance Publique - Hôpitaux de Paris
People needed
100
Starts
2026-05-01
Expected to finish
2026-10-01
Last updated by the study team
2026-07-31

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

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Where it is running

Full record on ClinicalTrials.gov

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