Benchmarking Large Language Models Against Tumour Boards for Oncology Treatment Recommendations (BEACON)

July 28, 2026 updated by: Assistance Publique - Hôpitaux de Paris

Benchmarking AI for Clinical Oncology decisioNmaking (BEACON): A Prospective, Multicentre, Blinded Evaluation of Frontier Large Language Models Against Multidisciplinary Tumour Board Recommendations in Oncology Treatment Planning

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

BEACON is a prospective, multicentre, blinded benchmark using automated, criteria-based scoring. It is built on three design decisions that distinguish it from the existing literature: (i) synthetic, standardised cases remove the record-completeness variability that confounds retrospective comparisons and allow the identical input to be given to every board and every model; (ii) two independent tumour boards per localisation let human-human agreement be measured rather than assumed; and (iii) a guideline matrix, locked a priori, provides an objective anchor applied identically to human and model recommendations.

Reference standard. For each case-domain, a guideline matrix (guideline-recommended / acceptable / unsupported options per case-domain; ESMO, NCCN), locked and time-stamped before data collection, is applied identically to boards and models.

Five decision domains. Every recommendation is decomposed into D1 Intent, D2 Surgery, D3 Radiotherapy, D4 Systemic therapy (class + line), and D5 Work-up & biomarkers before any comparison.

Study Type

Observational

Enrollment (Estimated)

100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • France
      • Paris, France
        • Recruiting
        • Hôpital Européen Georges Pompidou
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

100 synthetic oncology treatment-planning cases (20 per localisation) across five localisations: breast, lung, urological (prostate, bladder / upper-tract urothelial, kidney), digestive and gynaecological. Each case is a structured JSON input specifying UICC 8th-edition stage, biomarkers, ECOG performance status, comorbidities and a standardised clinical question. No human participants, no patient data and no identifiable individuals. Recommendations are produced by two independent tumour boards per localisation and by five frontier LLMs (queried May 2026).

Description

Inclusion Criteria:

  • Synthetic oncology case within one of the five predefined localisations (breast, lung, urological, digestive, gynaecological).
  • Complete structured schema: UICC 8th-edition stage, biomarkers, ECOG performance status, comorbidities and a standardised clinical question.
  • A clinically answerable treatment-planning question that is mappable to the locked guideline matrix.

Exclusion Criteria:

  • Case outside the five predefined localisations.
  • Incomplete, internally inconsistent or ambiguous schema.
  • Duplicate or near-duplicate of an existing case in the set.
  • Question not resolvable by current guidelines.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Breast cancers
Other: Multidisciplinary tumour boards
Two independent tumour boards per localisation (10 boards in total) issue a categorical recommendation for every synthetic case. Where both boards agree, their consensus defines the reference standard; where they differ, the case-domain is classified as EQUIPOISE and analysed separately.
Other: Frontier large language models
Five frontier LLMs (GPT-5.6, Claude Fable 5, Gemini 3.1 Pro, DeepSeek V4 Pro, Llama 4 Maverick) each receive the identical structured input for every case, three times in independent sessions, under locked prompts, versions and settings.
Lung cancers
Other: Multidisciplinary tumour boards
Two independent tumour boards per localisation (10 boards in total) issue a categorical recommendation for every synthetic case. Where both boards agree, their consensus defines the reference standard; where they differ, the case-domain is classified as EQUIPOISE and analysed separately.
Other: Frontier large language models
Five frontier LLMs (GPT-5.6, Claude Fable 5, Gemini 3.1 Pro, DeepSeek V4 Pro, Llama 4 Maverick) each receive the identical structured input for every case, three times in independent sessions, under locked prompts, versions and settings.
Urological cancers
Other: Multidisciplinary tumour boards
Two independent tumour boards per localisation (10 boards in total) issue a categorical recommendation for every synthetic case. Where both boards agree, their consensus defines the reference standard; where they differ, the case-domain is classified as EQUIPOISE and analysed separately.
Other: Frontier large language models
Five frontier LLMs (GPT-5.6, Claude Fable 5, Gemini 3.1 Pro, DeepSeek V4 Pro, Llama 4 Maverick) each receive the identical structured input for every case, three times in independent sessions, under locked prompts, versions and settings.
Digestive cancers
Other: Multidisciplinary tumour boards
Two independent tumour boards per localisation (10 boards in total) issue a categorical recommendation for every synthetic case. Where both boards agree, their consensus defines the reference standard; where they differ, the case-domain is classified as EQUIPOISE and analysed separately.
Other: Frontier large language models
Five frontier LLMs (GPT-5.6, Claude Fable 5, Gemini 3.1 Pro, DeepSeek V4 Pro, Llama 4 Maverick) each receive the identical structured input for every case, three times in independent sessions, under locked prompts, versions and settings.
Gynaecological cancers
Other: Multidisciplinary tumour boards
Two independent tumour boards per localisation (10 boards in total) issue a categorical recommendation for every synthetic case. Where both boards agree, their consensus defines the reference standard; where they differ, the case-domain is classified as EQUIPOISE and analysed separately.
Other: Frontier large language models
Five frontier LLMs (GPT-5.6, Claude Fable 5, Gemini 3.1 Pro, DeepSeek V4 Pro, Llama 4 Maverick) each receive the identical structured input for every case, three times in independent sessions, under locked prompts, versions and settings.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Domain-level performance between LLM recommendations and the locked guidelines.
Time Frame: Assessed once at central scoring, after data collection (~October 2026)
For each recommendation domain and each LLM, proportion of LLM recommendation concordant with locked guidelines
Assessed once at central scoring, after data collection (~October 2026)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Proportion of recommendations carrying serious harm potential ( LLM and tumour boards)
Time Frame: Up to October 2026
Up to October 2026
Domain-level recommendation concordance between LLM and tumour-boards
Time Frame: Up to October 2026
Each recommendation domain, decomposed into the five decision domains and scored per domain on an ordinal scale (2 = complete concordance; 1 = partial concordance; 0 = discordance).
Up to October 2026
Inter-tumour board domain-level recommendation concordance
Time Frame: Up to October 2026
Agreement between the two independent tumour boards scored per recommendation domain
Up to October 2026
Equipoise rate
Time Frame: Up to October 2026
Proportion of case-domains where the two tumour boards give different categorical recommendations
Up to October 2026
Completeness
Time Frame: Up to October 2026
Proportion of required domains addressed (LLM and tumour boards)
Up to October 2026
Missingness
Time Frame: Up to October 2026
Proportion of critical omissions (LLM and tumour boards)
Up to October 2026
Intensity bias
Time Frame: Up to October 2026
Proportion of recommendation corresponding to over- or under-treatment
Up to October 2026

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Assistance Publique - Hôpitaux de Paris

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 1, 2026

Primary Completion (Estimated)

October 1, 2026

Study Completion (Estimated)

October 1, 2026

Study Registration Dates

First Submitted

July 28, 2026

First Submitted That Met QC Criteria

July 28, 2026

First Posted (Actual)

July 31, 2026

Study Record Updates

Last Update Posted (Actual)

July 31, 2026

Last Update Submitted That Met QC Criteria

July 28, 2026

Last Verified

July 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • APHP261032

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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