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

Обзор

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 progressors (defined as progressive disease or death within three months of treatment or at first radiological restaging) Q2) Toxicity (with a special focus on severe toxicities G≥3) Q3) Long survivors (defined as patients reaching an overall survival of at least 1.5x median overall survival in registrative trials) The early identification of non-responders, high-risk patients (or on the other hand, long survivors) would help their healthcare planning, providing individualised follow-up strategies or prompting their inclusion in alternative treatments (eg clinical trials). For all cohorts, first data entry will be retrospective and second data entry will be prospective (as validation set).

Вмешательства

• Препарат Immunotherapy
  First-line regimen according to clinical practice
• Препарат Chemotherapy
  First-line regimen according to clinical practice

Первичные конечные точки

• Early progressive disease [Срок оценки: From date of enrolment until the date of first documented disease progression or death, whichever comes first, assessed within 8 to 12 weeks from first-line treatment start]
• Lung toxicity [Срок оценки: From date of enrolment until the date of first documented immune-related pneumonitis of G3 or more, assessed up to 96 months]
• Long survivors [Срок оценки: At a 3-year cut-off]

Критерии участия

Критерии включения

• 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

Критерии исключения

• 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

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Италия · 1 центр

• Francesca Rita Ogliari — Milan

Идентификаторы

NCT: NCT06788366 · AI-HOPE

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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