NCT05732974

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

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 60 (estimated)
• Sponsor: University Hospital, Toulouse · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

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.

Detailed 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.

Conditions

• Non-small Cell Lung Cancer Stage IIIA

Interventions

Type	Name	Description
OTHER	Resected non small cell lung cancer	plasma sample, tissue sample and computed tomography scan images

Timeline

• Start date: 2023-03-30
• Primary completion: 2025-11-30
• Completion: 2026-10-30
• First posted: 2023-02-17
• Last updated: 2023-09-21

Locations

1 site across 1 country: France