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

Recruiting
Conditions
Non-small Cell Lung Cancer Stage IIIA
Registration Number
NCT05732974
Lead Sponsor
University Hospital, Toulouse
Brief 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.

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
60
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

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Algorithm for disease free survival18 months

Analysis on a training cohort of resected early-stage non small cell lung cancer

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Julien MAZIERES

🇫🇷

Toulouse, France

Julien MAZIERES
🇫🇷Toulouse, France
Julien MAZIERES
Contact
0567771837
mazieres.j@chu-toulouse.fr
Julie MILIA
Contact
milia.j@chu-toulouse.fr

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