A Machine Learning Approach to Identify Patients With Resected Non-small-cell Lung Cancer With High Risk of Relapse (MIRACLE)

Toulouse University Hospital

Status: Enrolling

Conditions: Non-small Cell Lung Cancer Stage IIIA

Treatments: Other: Resected non small cell lung cancer

Study type: Observational

Funder types: Other

Identifiers

NCT05732974

RC31/21/0519

Details and patient eligibility

About

Early-stage non small cell lung cancer represents 20-30% of all non small cell lung cancer and is characterized by a high survival probability after surgical resection. However, considering stage IA-IIIA non small cell lung cancer, a relapse rate of about 50% is observed, with a different survival probability on the basis of tumor node metastasis status, although patients within the same tumor node metastasis stage exhibit wide variations in recurrence rate. There are currently no validated prognostic biomarkers able to identify patients with a high risk of relapse.

Full description

This study will use data from an already available cohort of patients enrolled in the Resting study (a project funded by TRANSCAN in 2018) as a training set and data from a new concurrent cohort as validation set.

Enrollment: 60 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patient with an early stage of non small cell lung cancer
• Indication of surgical resection
• Patient able to understand and give his consent
• Patient affiliated to the health insurance

Exclusion criteria

• Patient with another cancer in the last 5 years
• Patient with an allergy to the contrast medium
• Patient under legal protection

Trial design

60 participants in 1 patient group

Resected early stage non small cell lung cancer

Description:

Early stage (IA-IIIA) resectable non small cell lung cancer patients receiving surgery

Treatment:

Other: Resected non small cell lung cancer