A Machine Learning Approach to Identify Patients With Resected Non-small-cell Lung Cancer With High Risk of Relapse
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity Hospital, Toulouse
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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
Disqualifiers
Patient with another cancer in the last 5 years
Patient with an allergy to the contrast medium
Patient under legal protection
Trial population
Patient with an early stage of non small cell lung cancer with an indication of surgical resection
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Resected non small cell lung cancer
Other interventionplasma sample, tissue sample and computed tomography scan images
Treatment groups
60 Participants
are divided into 1 treatment groupGroup A: Resected early stage non small cell lung cancer1 intervention
Trial outcomes
Primary outcomes
1
Algorithm for disease free survival
Analysis on a training cohort of resected early-stage non small cell lung cancer
Time frame
18 monthsSponsors and contacts
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Source ClinicalTrials.gov