SCOOT: Sample Collection for DART

Sample Collection for The Integration and Analysis of Data Using Artificial Intelligence to Improve Patient Outcomes With Thoracic Diseases

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05368298

Acronym

SCOOT

Enrollment

872

Registered

2022-05-10

Start date

2022-08-11

Completion date

2027-09-30

Last updated

2026-05-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Lung Cancer

Keywords

screening, lung health check, artificial intelligence, algorithm, diagnosis, detection, blood, blood test, early detection, lung, lung cancer, lung screening, AI, biomarker

Brief summary

The study will use a blood sample collected from participants to: * Develop new ways of finding and diagnosing lung health problems, such as lung cancer. * Develop tools which make it easier to screen people with possible lung health problems, diagnose problems earlier and with fewer tests, and start the best treatment faster. * Help improve the early diagnosis of lung cancer, as finding lung cancer early means that it can be treated more easily and successfully.

Detailed description

The results from this study will be linked with the data from the DART study (also collecting data through the Lung Health Check programme) to develop new ways of using computer technology (artificial intelligence) to improve lung health care. The studies use computer programs (called 'algorithms') which can be trained to analyse medical samples. Once developed, these algorithms can be used to support doctors by increasing their speed and accuracy of diagnosing issues.

Interventions

None listed

Study design

Observational model

OTHER

Time perspective

OTHER

Eligibility

Sex/Gender

ALL

Age

55 Years to 75 Years

Healthy volunteers

Inclusion criteria

Patient suitability will be assessed against the below criteria by the clinical teams managing the patients. Inclusion Criteria: 1. Patients with a pulmonary nodule or nodule(s) detected on a CT scan performed as part of Lung Cancer Screening from the Lung Health Check centres, that require further investigation with a PET-CT scan, and / or biopsy, and / or resection 2. Willing and able to give informed consent

Exclusion criteria

* None -

Design outcomes

Primary

Measure	Time frame
To develop an algorithm that gives a greater than chance improved ability to diagnose lung cancer using the blood biomarkers with or without the AI CT algorithm compared to not using them	by 30Sep2027

Secondary

Measure	Time frame
To develop an algorithm that gives a greater than chance improved ability to diagnose lung cancer using the blood biomarkers with or without the AI CT and blood markers algorithm compared to not using them	by 30Sep2027

Countries

United Kingdom

Contacts

PRINCIPAL_INVESTIGATORRichard Lee

Royal Marsden NHS Foundation Trust

Outcome results