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AI-HOPE Lung Cancer: Building a Predictive Tool for Metastatic Lung Cancer

Recruitingn/aAges 18 Years - anyAllIRCCS San Raffaele
NCT06788366 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

The goal of our project is building a predictive response algorithm for patients with metastatic lung cancer, exploiting an artificial intelligence platform. It will collect patient information from all areas (clinical, laboratory, radiological, pathological) and analyse them, understanding connections and correlations, both at baseline and at pre-specified timepoints. It would lead to the development of a reliable and constantly evolving predictive score, able to continuously re-weight the importance of each variable as new data come in. Since the greatest clinical need is identifying non-responders to immunotherapy and chemo-immunotherapy combination (30% of all treated patients), these two populations are defined as the starting cohorts (Cohort A, immunotherapy alone, Cohort B, chemo-immunotherapy combinations). For each cohort, three main questions are to be answered: Q1) Early pr

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📋 Eligibility rules (as published)
Inclusion criteria: * Patients with histological or cytological diagnosis of NSCLC * Stage IV according to investigator's staging procedures (or any locally advanced tumour not feasible for local radical treatment) * Treatment with at least 1 cycle of mono-immunotherapy or chemo-immunotherapy (as per clinical practice) * Availability of follow-up Exclusion criteria: * Patients with other thoracic tumours non-NSCLC (i.e. SCLC) * Stage other than IV or feasible for radical treatment upfront * Treatment within clinical trials (with combination regimens different from the aforementioned combinations) * Lost to follow-up
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What it tests

  • Immunotherapy
  • Chemotherapy
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Where

1 site
Francesca Rita Ogliari
Milan, Italy
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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